Next-generation sequencing (NGS) technology has transformed the biomedical research landscape. Only a few years ago, high resolution genome or exome sequencing would be cumbersome and cost-restrictive, but current NGS technology platforms now allow for basic and clinical researchers to include these approaches for routine DNA and RNA sequencing needs. What are the different NGS sequencing approaches and how are they applied to oncology research?
Next-generation sequencing (NGS) technology has transformed the biomedical research landscape. Only a few years ago, high resolution genome or exome sequencing would be cumbersome and cost-restrictive, but current NGS technology platforms now allow for basic and clinical researchers to include these approaches for routine DNA and RNA sequencing needs. What are the different NGS sequencing approaches and how are they applied to oncology research?
1. Whole Genome Sequencing (WGS): NGS technology can be used for WGS of human genomes and tumor-specific genomes, as well as animal model and microbial genomes. WGS produces high resolution genomic sequences of expressed genomic regions as well as unexpressed regulatory regions. For preclinical oncology research, WGS is critical for characterizing genomic profiles associated with tumor progression or potential responsiveness to targeted drug therapies. WGS can detect single nucleotide variants, copy number variants, and insertions/deletions in tumor cells1. The comprehensive scope of WGS makes it well-suited for detecting mutations in both coding and non-coding regions2. WGS is also useful for population level oncology studies that evaluate genetic susceptibility to specific cancers and potential heritability3.
2. Whole Exome Sequencing (WES): WES techniques focus on sequencing the exome, which are comprised of protein expressing regions, or exons, within the genome. WES is an appropriate method for identifying genetic mutations that alter protein sequences, and WES data can be used toward measuring the tumor mutational burden (TMB) and predicting treatment efficacy4. WES data can also be used to identify potential new drug targets or mechanisms of drug resistance5.
3. Targeted Sequencing: This method focuses on defined gene regions and is typically used in diagnostic applications or for validation of WGS or WES results. Targeted sequencing works well for screening tumor samples for well characterized mutations, such as those associated with BCL2, BRCA-1/2, BRAF, and EGFR, and can be used for identifying appropriated targeted therapies6.
4. RNA sequencing: RNA sequencing is now emerging as powerful tool that complements NGS DNA methods because the transcriptional profile of a single cell can be measured and used to bridge genomic data with cellular phenotypes. Single-cell RNA sequencing (scRNA-seq) has specifically emerged as a powerful method for understanding the heterogeneity of cell populations within a tumor. Together with histological data, scRNA-seq data can be used to distinguish between neoplastic cells, immune cells, and healthy cells from the surrounding tissue, and it can also be used to evaluate how experimental treatments alter the tumor microenvironment7.
NGS methods are transforming both basic oncology research and clinical care, from identifying novel mutations to pinpointing personalized cancer therapies. Each method is suited to specific applications, so working with experts in NGS technology is critical to method selection and data analysis.
1 Bewicke-Copley F et al. Applications and Analysis of Targeted Genomic Sequencing in Cancer Studies. Comput. Struct. Biotechnol. 2019;17: 1348-1359.
2 Nakagawa H, Fujita M. Whole Genome Sequencing Analysis for Cancer Genomics and Precision Medicine. Cancer Sci. 2018;109(3):513-522.
3 Rotunno M et al. A Systematic Literature Review of Whole Exome and Genome Sequencing Population Studies of Genetic Susceptibility to Cancer. Cancer Epidemiology and Prevention Biomarkers. 2020;29(8):1519-34.
4 Klempner SJ et al. Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence. Oncologist. 2020 Jan;25(1): e147-e159.
5 Beltran H et al. Whole-Exome Sequencing of Metastatic Cancer and Biomarkers of Treatment Response. JAMA Oncol. 2015;1(4):466-474.
6 Vestergaard LK et al. Next Generation Sequencing Technology in the Clinic and Its Challenges. Cancers (Basel). 2021;13(8):1751.
7 Fan J et al. Single-Cell Transcriptomics in Cancer: Computational Challenges and Opportunities. Exp Mol Med. 2020; (52)1452–1465.
Pancreatic ductal adenocarcinoma (PDAC) is one of the most common and aggressive forms of pancreatic cancer that has remained difficult to diagnose early and treat successfully. PDAC has a five-year survival rate below 10% and is one of the leading causes of cancer death. Complete surgical resection is one of the few curative treatment modalities, and chemotherapy protocols have limited efficacy[1].
Unfortunately, most existing immunotherapy-based treatments are also associated with poor response rates[2]. Recent analyses of PDAC samples have provided critical insights into genetic alterations that drive tumorigenesis and have identified potential therapeutic targets. Here we highlight several of these key findings and how they may lead to advances in PDAC treatment.
PDAC arises in the epithelial cells of pancreatic duct, or ductules, and is thought to progress in a manner like other carcinomas, in which the normal epithelial cells transition into pre-invasive pancreatic intraepithelial neoplasia lesions that eventually form invasive PDAC[3]. Most PDAC tumors carry somatic mutations in oncogenes, particularly KRAS, TP53, CDKN2A, and SMAD4[4]. KRAS mutation is the most frequent event in PDAC. The assumption that KRAS is an undruggable target based on extensive drug screens that showed in vitro inhibition but limited or no efficacy in animal models[5] is finally being challenged by the very promising results obtained by administration of Sotoresib (KRAS p.G12C inhibitor) in patients with advanced pancreatic cancer (NCT03600883), and by the identification of small-molecules that inhibit KRAS p.G12D in preclinical studies[6,7].
The need for druggable targets or biomarkers for PDAC has led to more innovative approaches to identify unique molecule attributes. A recent comprehensive proteogenomic characterization of PDAC pancreatic ductal tissues compared against paired normal adjacent tissue, and the findings validated known mutations in oncogenes[8]. This study also defined previously unknown genomic alterations and analyzed differences in protein expression and protein phosphorylation status between tissues. This comprehensive analysis identified a panel of proteins linked to early stage PDAC, and phosphoproteomic analysis identified several signaling pathways downstream of KRAS, including PI3K/AKT/mTOR and MAPK/ERK, that may be targeted by existing kinase inhibitors. The PAK1/PAK2 kinases were also identified as dysregulated in PDAC tissues and have the potential to be targeted therapeutically.
Recent studies have also better characterized the tumor microenvironment (TME) of PDAC and how this may limit treatment efficacy[9]. PDAC tumors tend to be highly heterogenous with a dense stroma and disorganized blood vessels, which impair drug penetration. The TME is enriched for myeloid derived suppressor cells and regulatory T cells and displays a low mutational burden, thus making this a “cold” tumor immunophenotype that is resistant to existing immunotherapies. Current studies are examining immunotherapy or drug-based strategies to turn “cold” PDAC tumors into “hot” tumors that would be receptive to immune checkpoint blockade.
Further advances in PDAC research will require similar extensive proteogenomic studies that better define dysregulated pathways that trigger early events in tumor formation and may function as early biomarkers for disease. The search for novel therapeutic targets or combinations of targets is also essential to improving the currently dismal array of treatment options for PDAC patients. Champions Oncology has 81 highly characterized Pancreatic Cancer Models available for preclinical studies, click below to learn more about how these models can propel your research.
The field of oncology research has evolved significantly over the years, with new technologies constantly emerging to improve our understanding and treatment of cancer. One such technology is 4D proteomics, which utilizes four dimensions (retention time, mass, intensity, and ion mobility) to improve the detection of low-abundant peptides in complex biological samples. This powerful technique has proven to be particularly useful in personalized medicine and biomarker discovery for cancer research[1].
What is 4D Proteomics?
Proteomics is the study of all proteins present in a given sample or organism. Traditional proteomic methods have typically focused on identifying and quantifying proteins in a sample based on their mass and abundance. However, this approach often falls short when it comes to detecting low-abundant peptides, limiting our ability to fully understand the complexity of biological systems.
That's where 4D proteomics comes in. This technique adds an additional dimension (ion mobility) to the traditional three dimensions of mass, retention time, and intensity. Ion mobility measures the ability of a molecule to move through a buffer gas under an electric field, providing another valuable data point to improve peptide separation and identification[1].
The Benefits of 4D Proteomics in Oncology Research
The use of 4D proteomics has greatly improved the sensitivity and specificity of peptide identification, making it particularly useful in oncology research where small changes in protein levels can have significant implications. The addition of ion mobility as a fourth dimension has also improved peptide separation and identification, making it easier to analyze complex samples such as blood or tissue from cancer patients. This is especially crucial in personalized medicine, where individualized treatments are tailored to a patient's specific cancer and its unique molecular characteristics[2].
Additionally, ion mobility helps differentiate each phosphopeptide isoform, accurately identifying the phosphorylation site on the peptide and quantitating each peptide form. This is critical for example in measuring certain kinases whose activity or substrate selectivity is controlled by phosphorylation at specific sites[3].
Conclusion
In conclusion, the use of 4D proteomics has revolutionized the field of oncology research by improving our ability to detect low-abundant peptides and analyze complex samples. This technology has proven to be particularly valuable in personalized medicine and biomarker discovery for cancer research. As more studies continue to utilize 4D proteomics, we can expect further advancements in our fight against cancer.
Lung cancer is an aggressive malignancy that correspond to approximately 12% of newly diagnosed cases per year and that remains one of the leading causes of cancer-related deaths (21%)[1]. Non-small cell lung cancer (NSCLC) is the most common form of lung cancer and is typically diagnosed at advanced stages[2].
Extensive genomic studies of NSCLC have been essential to identifying mutations that drive oncogenesis and has been critical to the development of targeted therapies. Here we highlight progress in NSCLC treatment and identify areas of ongoing research.
Chemotherapy
For decades, chemotherapy was the primary treatment for NSCLC, and platinum-based chemotherapies are still used today in combination with radiotherapy and targeted therapies[3]. Platinum-based chemotherapies have been improved since their initial development in the late 20th century, and “platinum doublets” or “triplets”, which combine two or three different platinum-based cytotoxic compounds, have been shown to better target NSCLC and cause less toxicity[4]. Chemotherapy is still used as a first line treatment for advanced NSCLC, but overall effectiveness is limited when used alone. Advances in targeted therapies and immune checkpoint blockade have greatly enhanced the effectiveness of chemotherapy on overall survival and progression-free survival[5].
Targeted Therapies
Genetic analysis of NSCLC tumors has led to the use of targeted therapies. Mutations in the epidermal growth factor receptor (EGFR) were identified as the most prevalent defect in NSCLC patients across genders, ethnic groups, and smoking status[6]. Several common mutations have been characterized, but numerous rare mutations have also been identified, and most of these mutations target the tyrosine kinase domain, which results in unchecked cellular proliferation due to engagement of downstream MAKP, PI3K, and STAT signaling pathways. First (gefitinib and erlotinib) and second (afatinib and dacomitinib) generation tyrosine kinase inhibitors (TKIs) have been approved by the FDA to treat EGFR-mutated NSCLC. Unfortunately, treatment resistance and disease recurrence occur at a very high rate, and these TKIs are also associated with significant toxicity and undesirable side effects that result in adjustments of treatment regimens[5]. Third generation TKIs (e.g. osimertinib) that target specific EGFR mutations associated with acquired resistance to first and second generation TKIs have been approved and have been very successful in treating EGFR-mutated NSCLC as a first or a second line treatment. Because resistance to third generation TKIs eventually also arises, fourth generation TKIs are currently under development or are being used in ongoing clinical trials. Many of these next generation inhibitors have been carefully designed to optimize target specificity and reduce adverse events frequency and severity[7]. Mutations in other genes have also been observed at low frequency in NSCLC, and several clinical trials are now evaluating targeted therapies with inhibitors that target these genes, including, ALK, MET, ROS1, and BRAF among others[7, 8]. Capmatinib, an inhibitor targeting METex14 mutation, and adagrasib and sorotasib, both targeting KRAS G12C mutation, have recently been granted approval for treatment of NSCLC tumors presenting with the corresponding mutation[9, 10, 11]. In addition to small molecule inhibitors, Antibody-Drug Conjugates (ADC), a class of anti-cancer therapy capable of transporting cytotoxic drugs directly to tumor cells, are currently developed against NSCLC antigenic targets[12].
Immunotherapy
Immunotherapies that target the immune checkpoint molecules like Programmed Death (PD)-1 or its ligand PD-L1 have been shown to have therapeutic effects as second-line treatments in combination with chemotherapy[13] for patients lacking mutations that can be treated with approved targeted therapies. While several of these trials have shown improvements in overall survival, serious adverse events have also been elevated. In addition to immune checkpoint targeting, other immunotherapies are currently under development, and a bispecific antibody has been recently approved for the treatment of a subset of NSCLC patients[14].
Biomarkers
The availability of oncogenic driver mutations and of immune checkpoint targeted therapies have revolutionized NSCLC treatment and require the concomitant development of diagnostic tools to stratify patients and maximize the efficacy of these therapeutic options [15]. Oncogenic mutations are usually good companion biomarkers to indicate a patient as eligible to receive the associated treatment, however, diagnostic strategies need to be implemented to monitor patient response and anticipate or detect acquired resistance as early as possible. Immune checkpoint proteins are also currently tested as biomarkers to stratify patient, as an example a PD-L1 diagnostic test has been recently approved by FDA as companion biomarker to identify patients who are candidates for adjuvant treatment with atezolizumab [16].
Conclusion
Advances in NSCLC have shifted the median overall survival from 2-4 months in the 1960s to more than 2 years since advent chemotherapy combined with immunotherapy or targeted inhibitors in the 2010s. Our deeper understanding of mutations that drive NSCLC and our ever-expanding arsenal of targeted therapies or immune modulators will further improve survival and quality of life for NSCLC patients.
Chronic lymphocytic leukemia (CLL) is one of the most common forms of adult leukemia, and its chronic nature has made it a challenging blood cancer to completely cure. CLL affects B cells and is typically classified into two categories: little or no somatic hypermutation in the immunoglobulin heavy chain variable region (IGHV), called unmutated CLL, or high mutation levels in the IGHV gene, called mutated CLL.[1] Unmutated CLL is more aggressive than mutated CLL, and the presence of these abnormal IGHV sequences, a part of B cell receptors (BCR), leads to abnormal BCR signaling and the uncontrolled proliferation of leukemic cells.
Bruton’s tyrosine kinase (BTK) is an essential enzyme downstream from the BCR and is responsible for propagating the signaling cascade initiated by BCR engagement with pathogen-associated antigens.[2] Notably, BTK has been shown to be constitutively active in CLL and drives both leukemic cell proliferation and lymph node homing.[3] As antigen binds to the BCR, multiple protein tyrosine kinases are activated via interactions with the cytoplasmic domain of the BCR, including Lyn and Syk, as well as translocation of BTK to the plasma membrane through interactions with phosphatidylinositol-3,4,5 (PIP3).[4] Lyn and Syk phosphorylate BTK to activate multiple non-receptor protein tyrosine kinase signaling pathways, including NF-κB, MAPK, and phospholipase C gamma (PLCγ). Under normal conditions, this pathway leads to controlled B cell proliferation and differentiation, however, this same pathway leads to uncontrolled B cell proliferation in malignancies, such as CLL.
The role of BTK in CLL has drawn researchers to develop BTK inhibitors, such as ibrutinib - an FDA (Food and Drug Administration)[5] and EMA (European Medicines Agency)[6] - approved CLL treatment. Ibrutinib forms a covalent bond with a cysteine residue (C481) at BTK’s active site, and thus inhibits kinase activity, including autoactivation.[3] This kinase inhibition shuts down BCR signaling, reduces B cell proliferation, and promotes apoptosis of leukemic cells. Ibrutinib is effective as a standalone treatment for mutated and unmutated CLL and when combined with rituximab is an effective therapy for relapsed CLL.[1] In general, ibrutinib is well tolerated and shows continued efficacy during extended treatment periods.[7]
While ibrutinib has been a clinical success, there are a subset of CLL patients who develop resistance to this therapeutic. This resistance has been mapped to a C481S mutation that prevents ibrutinib from covalently binding to BTK resulting in continuous BCR signaling within leukemic cells.[3] Next-generation, reversible BTK inhibitors, such as ARQ 531, are currently being developed for relapsed/refractory CLL. ARQ-531 is a non-selective BTK inhibitor that suppresses signaling in cells with C481S BTK and PLCγ mutations. ARQ-531 also has an additional inhibitory activity against ERK signaling.[8] Furthermore, the FDA has recently approved LOXO-305, a non-covalent, reversible BTK inhibitor. LOXO-305 inhibits signaling in cells with wild-type or C481S-mutated BTK.[9, 10] In contrast, acalabrutinib, a second-generation irreversible BTK inhibitor has also been approved by the FDA. Acalabrutinib has a shorter half-life, allowing for variable dosages, and has increased C481 specificity that enhances its BTK inhibitory effects. The biochemical properties of acalabrutinib make it a suitable option for patients with treatment naïve CLL.[11]
In January 2023, the FDA and EMA approved an additional second-generation irreversible BTK inhibitor, zanubrutinib, for CLL.[12] Zanubrutinib’s design was guided by a structure-activity strategy to generate sustained BTK occupancy. Zanubrutinib exhibits reduced ITK and EGFR inhibition and has 4x longer half-life than acalabrutinib.[13] As such, it persists at high concentrations within the body making it available to re-inhibit newly synthesized BTK proteins, a unique difference from ibrutinib and acalabrutinib.[14]
In a phase I/II study, all CLL patients treated with zanubrutinib had complete and sustained BTK occupancy in peripheral blood mononuclear cells and lymph nodes.[15] Zanubrutinib’s performance supports the hypothesis that increased BTK selectivity maximizes BTK inhibition and drug efficacy. Additionally, zanubrutinib’s enhanced BTK specificity reduces the incidence of off-target toxicities which may reduce side effects commonly associated with ibrutinib, such as cardiac events, subdural hematomas, and gastrointestinal bleeding.[10, 16, 17] This is particularly relevant to CLL as this class of BTK inhibitors are used by CLL patients indefinitely.
BTK inhibitors have become an invaluable CLL treatment and will continue to improve and provide therapeutic benefits. Additional studies such as NCT03734016 are underway to evaluate the effects of zanubrutinib and BTK inhibitors with other targeted therapies, which may improve the efficacy and durability of these treatments.
Hepatocellular carcinoma (HCC) is one of the most prevalent types of liver cancer, and it usually develops in patients with underlying cirrhosis or chronic liver disease and metabolic syndrome.[1] HCC can spread to other body parts and affect patients' survival rates and outcomes severely. In this blog post, we will provide essential insights into HCC metastases and delve into the therapeutic options.
Over 60% of patients with HCC are diagnosed in advanced stages, leading to an overall 5-year survival rate of 21%. However, this rate is between 60% and 70% in patients with early diagnosis who undergo liver transplants.[2] Patients diagnosed with advanced-stage HCC, defined by the presence of vascular invasion or extrahepatic metastases, have a poor prognosis with a median survival of less than 1 year. [3] Early detection of HCC is vital in increasing therapeutic opportunities and improving patients’ outcomes, and new diagnostic biomarkers are under investigation to enhance HCC screening.[4]
Available treatments for HCC metastases depend on the tumor's location, the extent of the cancer, and the patient's general condition. Surgical resection, liver transplant, radiofrequency, and microwave ablation are all first-line treatments for tumors that have not spread to other body parts. Chemoembolization is commonly used and improves survival in asymptomatic patients with multifocal regional disease. [5]
Systemic therapies, such as sorafenib and lenvatinib have been shown to be effective in prolonging survival rates and outcomes in patients with advanced HCC. These agents are multikinase inhibitors that block tyrosine kinases involved in angiogenesis, cancer development and growth, and tumor microenvironment regulation. 
They are used as first-line therapy in advanced HCC with contraindications to VEGF and immune checkpoint inhibitors. Immune checkpoint inhibitors are instead used together with bevacizumab in patients without contraindication. Alternative tyrosine kinase inhibitors, such as regorafenib, cabozantinib, and ramucirumab are used as second-line treatments.[6]
Scientists are also researching new therapies for advanced HCC, including novel molecular-targeted therapies (such as STAT3 and CDK4 inhibitors) and immunotherapies to use as single agents or in combination. Several clinical trials are currently underway to investigate the efficacy and safety of these new therapies for advanced and metastatic HCC.[7]
Hepatocellular carcinoma is a critical concern for clinicians and patients, given the cancer progression and severity. Validating new diagnostic biomarkers and developing new therapeutic approaches to overcome drug resistance will be paramount in improving patients’ survival and quality of life.
Human epidermal growth factor receptor 2 (HER2; ERBB2) has been shown to induce oncogenesis in several cancers, particularly breast and gastric cancers. HER2 is estimated to be overexpressed in ~20% of all breast cancers, and outcomes for these breast cancers were poor before HER2-targeted therapies[1]. Our understanding of mechanisms by which HER2 drives tumor growth and metastasis led to one of the first targeted therapies for treating HER2+ breast cancers. Here we highlight what is known about HER2 and oncogenesis. and how this information can be applied to the development of new targeted therapies.
Gene amplification of the ERRB2 oncogene is one of the most common genetic defects detected in HER2+ tumors and typically causes overexpression of HER2 at the cell membrane[2]. HER2 proteins more readily dimerize with other HER2 proteins to form homodimers or with other ERRB members to form heterodimers. These complexes induce oncogenic signaling cascades, including MAPK and PI3K/AKT/mTOR, which cause cellular proliferation, angiogenesis, and resistance to apoptosis[3]. Due to the dominant role of HER2 in breast cancer, anti-HER2 antibodies were developed as one of the first targeted therapies. In 2006, clinical trial results of breast cancer patients treated with the anti-HER2 antibody trastuzumab showed significant improvements in progression-free survival and overall survival[4],[5]. Unfortunately, ~20-25% of metastatic breast cancer patients develop resistance to anti-HER2 therapies. More recent studies have focused on engineering new forms of anti-HER2 antibodies or developing HER1/2 inhibitors that can be used alone or in combination with other targeted therapies.
The current standard of care for HER2+ breast cancer includes chemotherapy with adjuvant HER2-targeted therapies and endocrine therapy as indicated. Advances in targeted therapies are further improving treatment protocols. The next-generation anti-HER2 monoclonal antibody margetuximab targets the same HER2 epitope as trastuzumab and is modified in its Fc domain to improve antibody-dependent cellular cytotoxicity.[6] Margetuximab was approved by the FDA in December 2020 for the treatment of metastatic breast cancer in patients who had received prior HER2 therapies[7]. Two different bispecific antibodies have also been developed and are in clinical trials: ZW25 is a bispecific antibody that targets two different HER2 epitopes, and PRS-343 is a bispecific antibody that targets a HER2 epitope and the 4-1BB costimulatory immunoreceptor[8]. Bispecific antibodies are under development for breast cancer and other cancers because they exploit the property that antibodies have two epitope binding sites and can be engineered to better target a single molecule or crosslink multiple molecules, like HER2 and immune checkpoint molecules.
Antibody-drug conjugates have also been evaluated as novel therapeutics that target HER2. Trastuzumab deruxtecan is an anti-HER2 antibody conjugated to a cytotoxic payload that is linked by a cleavable drug linker[9]. This treatment has been recently approved by the FDA and it shows superior targeting of cytotoxic drugs to HER2+ tumor cells and shows efficacy on individuals who have been treated previously with anti-HER2 mAbs.
HER2-specific tyrosine kinase inhibitors have also been successful in treating HER2+ tumors, especially brain metastases because these drugs can cross the blood-brain barrier. Lapatinib, neratinib, pyrotinib, and tucatinib are four HER2-specific tyrosine kinase inhibitors used to treat HER2+ breast cancers. Lapatinib is an oral, irreversible small molecule HER1/HER2/HER4 TKI that was first approved in 2007 for the treatment of metastatic breast cancer[10]. Neratinib is a similar, orally available irreversible small molecule HER1/HER2/HER4 TKI that showed better efficacy against EGFR mutants and has been approved for use as an adjuvant therapy following trastuzumab treatment[11]. The development of resistance is also a problem for HER2-targeted TKIs, and pyrotinib is an experimental HER1/HER2/HER4 TKI under investigation as a potential new drug that is less prone to resistance[12]. Tucatinib is a TKI that is highly selective for HER2 approved for use in combination with trastuzumab and capecitabine in HER2+ breast and colorectal cancers, including patients with metastases and who have received previous anti-HER2 treatment[13].
HER2+ breast cancers continue to be challenging to treat due to resistance and metastasis. Combination therapies with antibodies and targeted inhibitors have dramatically improved survival in HER2+ breast cancer patients, but individuals who relapse continue to be faced with limited treatment options. New antibody-drug conjugates, bispecific antibodies, and targeted inhibitors are under investigation and hold the promise of better, more durable treatment options for patients.
[1] Hudis CA. Trastuzumab--mechanism of action and use in clinical practice. N. Engl. J. Med. 2007 Jul 5;357(1):39-51.
[2] Slamon DJ, Clark GM, Wong SG, Levin WJ, Ullrich A, McGuire WL. Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene. Science. 1987 Jan 9;235(4785):177-82.
[3] Moasser MM. The oncogene HER2: its signaling and transforming functions and its role in human cancer pathogenesis. Oncogene. 2007 Oct 4;26(45):6469-87.
[4] Romond EH, Perez EA, Bryant J, Suman VJ, Geyer Jr CE, Davidson NE, Tan-Chiu E, Martino S, Paik S, Kaufman PA, Swain SM. Trastuzumab plus adjuvant chemotherapy for operable HER2-positive breast cancer. N. Engl. J. Med. 2005 Oct 20;353(16):1673-84.
[5] Smith I, Procter M, Gelber RD, Guillaume S, Feyereislova A, Dowsett M, Goldhirsch A, Untch M, Mariani G, Baselga J, Kaufmann M. 2-year follow-up of trastuzumab after adjuvant chemotherapy in HER2-positive breast cancer: a randomised controlled trial. Lancet. 2007 Jan 6;369(9555):29-36.
[6] Rugo HS, Im SA, Cardoso F, Cortés J, Curigliano G, Musolino A, Pegram MD, Wright GS, Saura C, Escrivá-de-Romaní S, De Laurentiis M. Efficacy of margetuximab vs trastuzumab in patients with pretreated ERBB2-positive advanced breast cancer: a phase 3 randomized clinical trial. JAMA Oncol. 2021 Apr 1;7(4):573-84
[7] https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-margetuximab-metastatic-her2-positive-breast-cancer.
[8] Kunte S, Abraham J, Montero AJ. Novel HER2-targeted therapies for HER2-positive metastatic breast cancer. Cancer. 2020 Oct 1;126(19):4278-4288.
[9] Doi T, Shitara K, Naito Y, Shimomura A, Fujiwara Y, Yonemori K, Shimizu C, Shimoi T, Kuboki Y, Matsubara N, Kitano A, Jikoh T, Lee C, Fujisaki Y, Ogitani Y, Yver A, Tamura K. Safety, pharmacokinetics, and antitumour activity of trastuzumab deruxtecan (DS-8201), a HER2-targeting antibody-drug conjugate, in patients with advanced breast and gastric or gastro-oesophageal tumours: a phase 1 dose-escalation study. Lancet Oncol. 2017 Nov;18(11):1512-1522.
[10] Ryan Q, Ibrahim A, Cohen MH, Johnson J, Ko CW, Sridhara R, Justice R, Pazdur R. FDA drug approval summary: lapatinib in combination with capecitabine for previously treated metastatic breast cancer that overexpresses HER-2. Oncologist. 2008 Oct;13(10):1114-9.
[11] Minami Y, Shimamura T, Shah K, LaFramboise T, Glatt KA, Liniker E, Borgman CL, Haringsma HJ, Feng W, Weir BA, Lowell AM, Lee JC, Wolf J, Shapiro GI, Wong KK, Meyerson M, Thomas RK. The major lung cancer-derived mutants of ERBB2 are oncogenic and are associated with sensitivity to the irreversible EGFR/ERBB2 inhibitor HKI-272. Oncogene. 2007 Jul 26;26(34):5023-7.
[12] Li Q, Guan X, Chen S, Yi Z, Lan B, Xing P, Fan Y, Wang J, Luo Y, Yuan P, Cai R, Zhang P, Li Q, Zhong D, Zhang Y, Zou J, Zhu X, Ma F, Xu B. Safety, Efficacy, and Biomarker Analysis of Pyrotinib in Combination with Capecitabine in HER2-Positive Metastatic Breast Cancer Patients: A Phase I Clinical Trial. Clin. Cancer Res. 2019 Sep 1;25(17):5212-5220.
[13] Murthy RK, Loi S, Okines A, Paplomata E, Hamilton E, Hurvitz SA, Lin NU, Borges V, Abramson V, Anders C, Bedard PL, Oliveira M, Jakobsen E, Bachelot T, Shachar SS, Müller V, Braga S, Duhoux FP, Greil R, Cameron D, Carey LA, Curigliano G, Gelmon K, Hortobagyi G, Krop I, Loibl S, Pegram M, Slamon D, Palanca-Wessels MC, Walker L, Feng W, Winer EP. Tucatinib, Trastuzumab, and Capecitabine for HER2-Positive Metastatic Breast Cancer. N Engl J Med. 2020 Feb 13;382(7):597-609.
Prostate cancer is one of the most common forms of cancer that affects the prostate gland in the male urogenital tract. Most prostate cancers are slow growing and are usually detected in individuals older than age 50. Although environmental factors contribute to the development of prostate cancer, risk is significantly associated with incidence among first-degree relatives. In recent years, several inherited and spontaneously mutated genes have been linked to prostate cancer. Here we highlight these findings and how they provide insight into the development of targeted prostate cancer therapies.
Prostate cancer tumors are typically characterized by a wide range of genomic aberrations including somatic copy number alterations (SCNAs), structural rearrangements, and point mutations. Metastatic prostate tumors may have hundreds of these aberrations throughout the genome, but recent studies of primary prostate tumors have been critical to defining mutations associated with tumor development. Most primary prostate tumors have SCNAs, typically in the form of deletions that target a small area of the genome1. Deletions are often seen in the tumor suppressor genes BRCA2, NKX3.1, PTEN, and RB12.
Structural rearrangements are another source of genomic variation observed in primary prostate tumors, for which the TMPRSS2:ERG rearrangement is most common and causes the androgen-responsive TMPRSS2 serine protease to drive expression of the ERG oncogene3. Other rearrangements have been linked to prostate cancer, including TMPRSS2 fusions with other ETS family members beyond ERG (ETV1 and ETV4)4. Some studies have suggested a link between ERG rearrangements and SCNA incidence, although it is not yet clear if rearrangements lead to destabilization of the genome and increased occurrence of SCNAs1.
Somatic mutations occur on relatively high frequency primary prostate tumors, and this has been linked to mutations DNA mismatch repair proteins, tumor suppressors and oncogenes. The tumor suppressor TP53 is consistently identified as mutated in prostate tumors5. Mutations in the tumor suppressor genes BRCA1 and BRCA2 are well known for their association with breast and ovarian cancer but have also been linked to prostate cancer, and recent studies have shown that certain BRCA2 pathogenic sequence variants are associated with an elevated risk for aggressive prostate cancer6,7. PALB2 is a protein that interacts with BRCA2, and a recent study indicated that individuals who have certain PALB2 variants are more predisposed to aggressive forms of prostate cancer8. In addition, mutations in genes associated with DNA mismatch repair (MMR), such as MSH2, MSH6, and MLH1, are associated with greater prostate cancer risk9, and individuals with Lynch syndrome, which is caused by a germline mutation in one of these MMR genes, are also at greater risk of developing an aggressive form of prostate cancer10.
One of the most important genes involved in prostate cancer progress is the gene expressing the androgen receptor (AR). Dozens of somatic mutations have been identified in the AR, and many of these mutations target the ligand binding domain11. Some prostate cancers can be treated successfully with drugs that inhibit AR signaling, such as enzalutamide, but resistance frequently occurs and is associated with worse outcomes. AR promotes prostate cancer cell survival by regulating several cellular programs. Although AR activity inhibition through androgen deprivation therapy (ADT) results in the suppression of AR-related pathways and durable clinical remission12, the disease may recur as castration-resistant prostate cancer (CRPC), typically with reactivated AR signaling. In this case, patients are treated with second-generation AR pathway inhibitors such as enzalutamide and abiraterone. Unfortunately, durable complete responses under these treatments are rare, and a substantial number of CRPC tumors progress under treatment despite loss of AR signaling. CRPC with AR-null phenotype are classified as tumors with diffuse small cell or neuroendocrine (NE) characteristics (SCNPC) or as double-negative (DNPC) phenotype that lacks both NE and AR activity13. A recently described genome-wide CRISPR-Cas9 screen was used to identify kinases that could be inhibited in the presence of enzalutamide. BRAF or downstream MAPK signaling molecules were identified as targets that could be co-inhibited with enzalutamide to improve overall therapeutic effects of these drugs14.
Genomic alterations in prostate cancer are highly variable and can impact many critical cellular processes. By understanding which genes drive disease progression, potential therapeutic targets can be identified, and disease outcomes under different treatment regimens can be better predicted.
[1] Taylor BS, Schultz N, Hieronymus H, et al. Integrative genomic profiling of human prostate cancer. Cancer Cell. 2010 Jul 13;18(1):11-22.
[2] Wallis CJ, Nam RK. Prostate Cancer Genetics: A Review. EJIFCC. 2015 Mar 10;26(2):79-91.
[3] Tomlins SA, Rhodes DR, Perner S et al. Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science. 2005 Oct 28;310(5748):644-8.
[4] Rubin MA, Maher CA, Chinnaiyan AM. Common gene rearrangements in prostate cancer. J. Clin. Oncol. 2011 Sep 20;29(27):3659-68.
[5] Ecke TH, Schlechte HH, Schiemenz K et al. TP53 gene mutations in prostate cancer progression. Anticancer Res. 2010 May 1;30(5):1579-86.
[6] Patel VL, Busch EL, Friebel TM, et al. Association of Genomic Domains in BRCA1 and BRCA2 with Prostate Cancer Risk and Aggressiveness. Cancer Res. 2020 Feb 1;80(3):624-638.
[7] Oh M, Alkhushaym N, Fallatah S, et al. The association of BRCA1 and BRCA2 mutations with prostate cancer risk, frequency, and mortality: A meta-analysis. Prostate. 2019 Jun;79(8):880-895.
[8] Wokołorczyk D, Kluźniak W, Stempa K, Rusak B, Huzarski T, Gronwald J, Gliniewicz K, Kashyap A, Morawska S, Dębniak T, Jakubowska A. PALB2 mutations and prostate cancer risk and survival. Br. J. Cancer. 2021 May 18:1-7.
[9] Ritch E, Fu SY, Herberts C, Wang G, et al. Identification of hypermutation and defective mismatch repair in ctDNA from metastatic prostate cancer. Clin. Cancer Res. 2020 Mar 1;26(5):1114-25.
[10] Haraldsdottir S, Hampel H, Wei L, et al. Prostate cancer incidence in males with Lynch syndrome. Genet. Med. 2014 Jul;16(7):553-7.
[11] Ferraldeschi R, Welti J, Luo J, Attard G, de Bono JS. Targeting the androgen receptor pathway in castration-resistant prostate cancer: progresses and prospects. Oncogene. 2015 Apr 2;34(14):1745-57.
[12] Heinlein CA, Chang C. Androgen receptor in prostate cancer. Endocr Rev. 2004;25(2):276–308.
[13] Bluemn EG, Coleman IM, Lucas JM et al. Androgen receptor pathway-independent prostate cancer is sustained through FGF signaling. Cancer Cell. 2017;32(4):474–489.
[14] Palit SAL, van Dorp J, Vis D, Lieftink C, Linder S, Beijersbergen R, Bergman AM, Zwart W, van der Heijden MS. A kinome-centered CRISPR-Cas9 screen identifies activated BRAF to modulate enzalutamide resistance with potential therapeutic implications in BRAF-mutated prostate cancer. Sci. Rep. 2021 Jul 1;11(1):13683.
Preclinical oncology research is a critical component in the development of new cancer therapeutics, and it is essential that drug candidates are carefully screened before they are tested in human clinical trials. One valuable tool in preclinical oncology research is the use of cell line-derived xenograft (CDX) models. In this blog post, we will explore the benefits of CDX models for preclinical oncology screening and how they can be used to improve our understanding of cancer and the development of new treatments.
CDX models are created by implanting human cancer cells into immunocompromised mice. These cells develop into tumors that resemble their human counterparts and can be used to study the biology of cancer and test new treatments. One significant advantage of CDX models is that they are relatively easy and fast to establish, making them a cost-effective alternative to other preclinical screening models.[1]
CDX models allow researchers to study the response of tumors to treatments in vivo, replicating the conditions of human cancer. Additionally, they can be used to evaluate the pharmacodynamics and pharmacokinetics (PD/PK) of candidate drugs. These models allow researchers to evaluate how drugs impact tumor growth over time, and how the drug is distributed throughout the body. This information is critical in determining the optimal dosing regimen for cancer patients.[2-4]
CDX models have been widely used in preclinical research for several decades and can provide valuable insights into the underlying biology of cancer. Tumors grown in CDX models can be analyzed in depth to identify biological markers that can inform the development of targeted therapies. The use of CDX models can help researchers better understand the complexity of cancer and identify new therapeutic targets.[5-6]
In conclusion, CDX models offer several advantages for preclinical oncology screening, including their ease of establishment, ability to replicate human conditions, and ability to provide insights into the biology of cancer. By incorporating CDX models into their preclinical screening strategies, researchers can more accurately predict the efficacy of cancer drugs and improve the development of new cancer therapies.
1. Long Y, Xie B, Shen HC, Wen D. Translation Potential and Challenges of In Vitro and Murine Models in Cancer Clinic. Cells. 2022 Nov 30;11(23):3868. doi: 10.3390/cells11233868. PMID: 36497126; PMCID: PMC9741314.
2. Qin L, Wang L, Zhang J, Zhou H, Yang Z, Wang Y, Cai W, Wen F, Jiang X, Zhang T, Ye H, Long B, Qin J, Shi W, Guan X, Yu Z, Yang J, Wang Q, Jiao Z. Therapeutic strategies targeting uPAR potentiate anti-PD-1 efficacy in diffuse-type gastric cancer. Sci Adv. 2022 May 27;8(21):eabn3774. doi: 10.1126/sciadv.abn3774. Epub 2022 May 25. PMID: 35613265; PMCID: PMC9132454.
3. Chen Y, Chen HN, Wang K, Zhang L, Huang Z, Liu J, Zhang Z, Luo M, Lei Y, Peng Y, Zhou ZG, Wei Y, Huang C. Ketoconazole exacerbates mitophagy to induce apoptosis by downregulating cyclooxygenase-2 in hepatocellular carcinoma. J Hepatol. 2019 Jan;70(1):66-77. doi: 10.1016/j.jhep.2018.09.022. Epub 2018 Oct 1. PMID: 30287340.
4. Kendsersky NM, Lindsay J, Kolb EA, Smith MA, Teicher BA, Erickson SW, Earley EJ, Mosse YP, Martinez D, Pogoriler J, Krytska K, Patel K, Groff D, Tsang M, Ghilu S, Wang Y, Seaman S, Feng Y, Croix BS, Gorlick R, Kurmasheva R, Houghton PJ, Maris JM. The B7-H3-Targeting Antibody-Drug Conjugate m276-SL-PBD Is Potently Effective Against Pediatric Cancer Preclinical Solid Tumor Models. Clin Cancer Res. 2021 May 15;27(10):2938-2946. doi: 10.1158/1078-0432.CCR-20-4221. Epub 2021 Feb 22. PMID: 33619171; PMCID: PMC8127361.
5. Oduwole OO, Poliandri A, Okolo A, Rawson P, Doroszko M, Chrusciel M, Rahman NA, Serrano de Almeida G, Bevan CL, Koechling W, Huhtaniemi IT. Follicle-stimulating hormone promotes growth of human prostate cancer cell line-derived tumor xenografts. FASEB J. 2021 Apr;35(4):e21464. doi: 10.1096/fj.202002168RR. PMID: 33724574.
6. Tang N, Cheng C, Zhang X, Qiao M, Li N, Mu W, Wei XF, Han W, Wang H. TGF-β inhibition via CRISPR promotes the long-term efficacy of CAR T cells against solid tumors. JCI Insight. 2020 Feb 27;5(4):e133977. doi: 10.1172/jci.insight.133977. PMID: 31999649; PMCID: PMC7101140.
Signal transduction networks are essential to normal cell growth and function, but signaling abnormalities, such as those caused by spontaneous mutations in signaling components, are the leading causes of tumor growth. The extracellular signal-regulated kinase (ERK) signaling pathway contributes to normal cell proliferation, differentiation, and survival, but components of the ERK pathway are upregulated in many tumor types, including those associated with melanoma, lung, colon and pancreatic cancers.
The critical role of the ERK pathway in cancer has resulted in the development of drugs and therapeutics that can inhibit overactivation of ERK signaling molecules or target aberrant signaling pathways upstream of ERK. The emergence of precision medicine-driven cancer treatments has advanced the ERK pathway inhibitor field. Breakthroughs in cancer genomics has enabled researchers to analyze tumor sequences derived from patient data and identify novel targets in the ERK pathway. This type of computational analysis coupled with large scale in vitro screening is essential to narrowing down which novel inhibitors are studied further during preclinical development.
The use of patient-derived xenograft (PDX) mouse models is critical to the discovery of next-generation ERK inhibitors. PDX models involve the use of mice that are engrafted with tumor tissue derived from patient samples. These mice typically have suppressed immune systems in order to tolerate tumor grafts and can be engineered to express other components of the human immune system, such as immune checkpoint inhibitors. PDX models that use tumors with mutations in ERK signaling, such as a colorectal tumor with a V600-mutated BRAF molecule, can be used in the preclinical screening of novel ERK pathway inhibitors. Novel inhibitors can be screened simultaneously in different PDX models, and the safety and efficacy of these molecules can also be assessed in combination with other therapeutics.
We are entering an era when cancer patients will have access to precision medicine treatments informed by the genetic analysis of their tumors, and the strategic deployment of new and improved ERK pathway inhibitors in patients with specific ERK mutations will improve treatment efficacy and overall survival. PDX models are essential to the development of these new ERK pathway inhibitors and many other novel immunotherapies.
The quality of data received from clinical specialty testing labs is largely dependent on the integrity of the samples tested. One critical aspect of this is the proper isolation of PBMCs - peripheral blood mononuclear cells - often used in high-complexity flow cytometry research. To get the best quality results, researchers must use the most optimal tubes to isolate these cells. Three main types of tubes are commonly used: SepMate tubes, CPT tubes, and Manual Ficoll Gradient tubes. Each of these tubes has advantages and disadvantages that researchers must consider carefully. In this blog post, we will look at the pros and cons of each tube type and what you should consider before selecting one for your clinical trial.
SepMate Tubes:
SepMate tubes come in different sizes that enable researchers to isolate PBMCs from different numbers of tubes at once. These tubes work by using an inserted plastic separation technology that helps remove unwanted clumps of cells. One of the most significant advantages of these tubes is that they can be used for small to medium-sized samples with ease. The technology also separates cells significantly, making it easy to measure the concentration of cells after the separation procedure accurately. Furthermore, the tube also allows for rapid and consistent layering and easy collection of PBMCs, making it ideal for research. However, obtaining a high percentage of neutrophils is not possible, as they would be trapped below the barrier inside the tube. SepMate tubes are disposable, which makes them less financially sensible in the long run.
CPT Tubes:
CPT tubes are anticoagulant-based layered tubes that allow for the collection directly to cell separation without any additional processing. CPT tubes simplify the separation process and reduce the risk of contamination. They offer a more robust PBMC isolation process, and specific manufacturers produce four types to suit different research needs regarding testing human cells. The tubes generate high PBMC yields with high cell viability, making them an optimal option where quality is paramount. The primary disadvantage of CPT tubes is that they are quite expensive when compared to other tube types for PBMC isolation.
Manual Ficoll Gradient Tubes:
Manual Ficoll Gradient tubes require manual handling and processing, so they aren't automated. Due to this, the individual processing of Ficoll gradient tubes can cause variability in the manual layering steps, leading to variation in the final cell yield. The biggest issue with this type of isolation tube is that it takes longer to obtain the actual PBMCs than using SepMate or CPT tubes, which may create more significant delays in your research. Additionally, due to the manual nature of this type of PBMC isolation, final PBMC recovery rates are usually dependent on the experience of the researcher.
In conclusion, the right tube type will depend on your primary requirements for your research. Regardless of your choice, there is still a need to make sure you select a tube type that meets the technical requirements of your studies and delivers high-quality results. Champions Oncology has expertise in GCLP-compliant PBMC isolation using SepMate, CPT, and manual Ficoll Gradient tube types and can advise the best choice for your upcoming clinical trial.
Sarcomas are a group of aggressive heterogeneous tumors for which more than 100 histological subtypes have been defined1. Sarcomas are found in a variety of solid tissues, including bone and gastrointestinal stromal cells. Current treatment options include radiotherapy, surgical resection, targeted therapies, and chemotherapy, but these treatments have had limited efficacy on intermediate to high-grade tumors. Investigations into the molecular and cellular mechanisms that drive sarcomas have helped identify potential biomarkers that can serve as potential therapeutic targets. In addition, recent studies have also focused on the tumor microenvironment (TME) within sarcomas and the roles of different immune cell subsets creating an immunosuppressive microenvironment. These observations directly inform novel immunotherapeutic approaches that are being examined in preclinical and clinical studies.
In general, sarcoma TMEs are highly immunosuppressive environments, and a recent analysis of the Ewing’s sarcoma family of tumors (ESFT) showed poor overall survival correlated with tumors that had a TME with elevated expression of hypoxia-inducible factor 1-α and were enriched with immunosuppressive M2 macrophages and neutrophils2. The presence of tumor-associated macrophages has also been linked to sarcoma growth and metastasis, and elevated expression of the immune checkpoint molecule PD-L1 also correlated with metastasis and poor overall survival3,4. These observations led to clinical trials that evaluated the efficacy of immune checkpoint blockade for treating sarcomas, but treatments that targeted PD-1/PD-L1 or CTLA-4 showed limited clinical efficacy and did not meet primary endpoints for overall survival5,6.
Genomic studies of sarcomas have been critical to identifying mutations associated with tumor growth, angiogenesis, and metastasis. These findings led to clinical trials examining the efficacy of tyrosine kinase inhibitors or inhibitors that target vascular endothelial growth factor or insulin-like growth factor-1, but most of these trials failed to meet overall survival endpoints7,8. More recent genomic studies have indicated that mutations associated with different tumors occur in the same genes as some of the targeted therapies, but the mutations differ sufficiently to render these therapies ineffective9.
Cell-based immunotherapies have shown great promise in treating hematologic malignancies and are being explored for solid tumors. Chimeric antigen receptor (CAR) T cells have been of particular interest as they are patient-derived T cells engineered to express a tumor-specific receptor and thus can target tumors without being detected as foreign cells. Preclinical studies suggested that sarcoma-specific CAR T cells may be effective, but clinical trials have failed due to poor penetration and function of CAR T cells in the immunosuppressive TME10.
Recent and ongoing studies are exploring the effects of multi-CAR T cell strategies that target different tumor antigens, as well as the effects of using modified dendritic cells or natural killer cells or combining treatment modalities11.
Effective and lasting treatment options for sarcomas continue to be elusive but advances in genomic analysis and immune-based treatments are slowly improving outcomes. Like other cancers, clinical studies exploring treatment combinations are also showing promise and may provide critical breakthroughs for some of the most aggressive sarcomas.
1 Doyle LA. Sarcoma classification: an update based on the 2013 World Health Organization Classification of Tumors of Soft Tissue and Bone. Cancer. 2014 Jun 15;120(12):1763-74.
2 Stahl D, Gentles AJ, Thiele R, Gütgemann I. Prognostic profiling of the immune cell microenvironment in Ewing’s Sarcoma Family of Tumors. Oncoimmunology. 2019 Dec 2;8(12):e1674113.
3 Xiao W, Klement JD, Lu C, Ibrahim ML, Liu K. IFNAR1 controls autocrine type I IFN regulation of PD-L1 expression in myeloid-derived suppressor cells. J. Immunol. 2018 Jul 1;201(1):264-77.
4 Zhu Z, Jin Z, Zhang M, Tang Y, Yang G, Yuan X, Yao J, Sun D. Prognostic value of programmed death-ligand 1 in sarcoma: a meta-analysis. Oncotarget. 2017 Aug 29;8(35):59570.
5 Maki RG, Jungbluth AA, Gnjatic S, Schwartz GK, D’Adamo DR, Keohan ML, Wagner MJ, Scheu K, Chiu R, Ritter E, Kachel J. A pilot study of anti-CTLA4 antibody ipilimumab in patients with synovial sarcoma. Sarcoma. 2013 Oct;2013.
6 Zuo W and Lingdi Z. Recent advances and application of PD-1 blockade in sarcoma." Oncotargets and Therapy 2019; 12:6887.
7 Ray-Coquard IL, Domont J, Tresch-Bruneel E, Bompas E, Cassier PA, Mir O, Piperno-Neumann S, Italiano A, Chevreau C, Cupissol D, Bertucci F. Paclitaxel given once per week with or without bevacizumab in patients with advanced angiosarcoma: a randomized phase II trial. J. Clin. Oncol. 2015 Sep 1;33(25):2797-802.
8 Tap WD, Demetri G, Barnette P, Desai J, Kavan P, Tozer R, Benedetto PW, Friberg G, Deng H, McCaffery I, Leitch I. Phase II study of Ganitumab, a fully human anti–type-1 insulin-like growth factor receptor antibody, in patients with metastatic ewing family tumors or desmoplastic small round cell tumors. J. Clin. Oncol. 2012 May 20;30(15):1849-56.
9 Trédan O, Wang Q, Pissaloux D, Cassier P, de la Fouchardière A, Fayette J, Desseigne F, Ray-Coquard I, de la Fouchardière C, Frappaz D, Heudel PE. Molecular screening program to select molecular-based recommended therapies for metastatic cancer patients: analysis from the ProfiLER trial. Ann. Oncol. 2019 May 1;30(5):757-65.
10 Thanindratarn P, Dean DC, Nelson SD, Hornicek FJ, Duan Z. Chimeric antigen receptor T (CAR-T) cell immunotherapy for sarcomas: From mechanisms to potential clinical applications. Cancer Treatment Reviews. 2020 Jan 1; 82:101934.
11 Patel S, Burga RA, Powell AB, Chorvinsky EA, Hoq N, McCormack SE, Van Pelt SN, Hanley PJ, Cruz CR. Beyond CAR T cells: other cell-based immunotherapeutic strategies against cancer. Front. Onc. 2019 Apr 10; 9:196.
Ovarian cancer remains one of the leading causes of mortality for women with gynecological cancers and continues to be associated with stubbornly low 5-year survival rates. Depending on the stage or type of ovarian cancer, localized treatments including surgical resection or radiation may be sufficient. Treatment of metastatic ovarian cancer may include surgery and radiation combined with chemotherapy. Hormone therapy is also typically combined with chemotherapy for targeted reduction of estrogen and/or stimulation of progesterone for the targeted treatment of ovarian stromal tumors that produce high levels of estrogen. Nonetheless, many of these treatments have limited efficacy for treating metastatic ovarian cancer.
Advances in targeted ovarian cancer treatments have been facilitated by identification of cellular replication machinery in some cancer subtypes, including defects in the breast cancer-associated protein (BRCA)1 and BRCA2 genes, which play critical roles in DNA repair and transcription regulation[1]. Poly (ADP-ribose) polymerases (PARP) are a family of enzymes that can repair single strand DNA breaks through the base excision repair pathway[2]. PARPs can work together with normal BRCA1/2 to repair double strand DNA breaks by the homologous recombination (HR) pathway. Preclinical studies have shown that PARP inhibitors are effective in cells with BRCA1/2 mutations because these mutations combined with PARP inhibition cause synthetic lethality due to blockade of multiple DNA repair pathways.
Olaparib was the first PARP inhibitor approved for the treatment of germline BRCA1/2-mutated metastatic ovarian cancer in 2014[3]. This treatment was recommended for patients who had undergone three or more rounds of chemotherapy. Olaparib was later approved as a first-line maintenance therapy for germline or somatic BRCA1/2 mutations as well for the treatment of advanced ovarian cancers that have partial or complete responses to first-line platinum-based chemotherapies. Two other PARP inhibitors are also currently approved for different ovarian cancer diagnoses including rucaparib, which is approved for the treatment of germline BRCA1/2 mutations following two rounds of chemotherapy and for maintenance therapy following platinum-based therapies regardless of BRCA mutation status. Similarly, niraparib is approved to treat ovarian cancers with BRCA1/2 mutations or genomic instability and disease progression following platinum-based chemotherapies.
Like many other targeted therapies, some patients are completely unresponsive to treatment or develop resistance to PARP inhibitor monotherapy. Recent studies have described promising results associated with combined treatments, including PARP inhibitors combined with anti-angiogenic drugs like bevacizumab[4] or immune check point inhibitors like pembrolizumab[5]. There are currently three ongoing phase III first-line trials comparing the efficacy of combining PARP inhibitors and immune checkpoint blockade with VEGF inhibitors. Several thousand women are being enrolled in these studies with a goal of trying to determine if these combinations improve outcomes[6].
PARP inhibitors continue to be effective for treating hormone receptor-negative tumors but are less effective in treating hormone-receptor-positive ovarian tumors. Current trials are exploring the use of hormone inhibitors to disrupt hormone receptor signaling in ovarian tumors and render them sensitive to PARP inhibition[7].
PARP inhibitors have provided clinical benefits to ovarian cancer patients who previously had limited treatment options. Future studies will likely improve the efficacy of PARP inhibition as a monotherapy or in combination with other targeted therapies.
[1] Venkitaraman AR. Functions of BRCA1 and BRCA2 in the biological response to DNA damage. J Cell Sci. 2001 Oct;114(Pt 20):3591-8.
[2] D'Amours D, Desnoyers S, D'Silva I, Poirier GG. Poly(ADP-ribosyl)ation reactions in the regulation of nuclear functions. Biochem J. 1999 Sep 1;342 ( Pt 2)(Pt 2):249-68.
[3] Franzese E, Centonze S, Diana A, Carlino F, Guerrera LP, Di Napoli M, De Vita F, Pignata S, Ciardiello F, Orditura M. PARP inhibitors in ovarian cancer. Cancer Treatment Reviews. 2019 Feb 1;73:1-9.
[4] Ray-Coquard I, Pautier P, Pignata S, Pérol D, González-Martín A, Berger R, Fujiwara K, Vergote I, Colombo N, Mäenpää J, Selle F. Olaparib plus bevacizumab as first-line maintenance in ovarian cancer. New England Journal of Medicine. 2019 Dec 19;381(25):2416-28.
[5] Konstantinopoulos PA, Waggoner S, Vidal GA, Mita M, Moroney JW, Holloway R, Van Le L, Sachdev JC, Chapman-Davis E, Colon-Otero G, Penson RT, Matulonis UA, Kim YB, Moore KN, Swisher EM, Färkkilä A, D'Andrea A, Stringer-Reasor E, Wang J, Buerstatte N, Arora S, Graham JR, Bobilev D, Dezube BJ, Munster P. Single-Arm Phases 1 and 2 Trial of Niraparib in Combination with Pembrolizumab in Patients With Recurrent Platinum-Resistant Ovarian Carcinoma. JAMA Oncol. 2019 Aug 1;5(8):1141-1149.
[6] Elyashiv, Osnat, Yien Ning Sophia Wong, and Jonathan A. Ledermann. "Frontline Maintenance Treatment for Ovarian Cancer." Current Oncology Reports 23.8 (2021): 1-10.m
[7] Matulonis UA, Wulf GM, Barry WT, Birrer M, Westin SN, Farooq S, Bell-McGuinn KM, Obermayer E, Whalen C, Spagnoletti T, Luo W. Phase I dose escalation study of the PI3kinase pathway inhibitor BKM120 and the oral poly (ADP ribose) polymerase (PARP) inhibitor olaparib for the treatment of high-grade serous ovarian and breast cancer. Annals of Oncology. 2017 Mar 1;28(3):512-8.
With advances in next-generation sequencing (NGS) technologies, gene expression analysis has become an increasingly popular area of research. Two common methods used for this purpose are RNA sequencing (RNAseq) and whole transcriptome sequencing (WTS). Both techniques provide valuable insights into the molecular mechanisms of individual cells and organisms. However, when should one use RNAseq versus WTS for gene expression analysis? In this post, we will explore the advantages and disadvantages of both methods and provide guidance on which one to use.
RNAseq
RNAseq is a method of sequencing RNA molecules and measuring the abundance of each transcript. This method is capable of identifying all types of RNA, including messenger RNA (mRNA), noncoding RNA, and small RNA. It requires high-quality RNA and can detect alternative splicing, fusion genes, and post-transcriptional modifications. RNAseq is particularly useful for identifying novel transcripts and quantifying gene expression levels in low-abundance genes[1].
However, RNAseq has some disadvantages. Its high sensitivity may lead to high levels of noise when dealing with lowly expressed genes. The method can also be expensive, and the data analysis process can be complex. Additional bioinformatic tools are required to accurately quantify gene expression levels, identify differential expression, and perform pathway analysis[1].
Whole Transcriptome Sequencing
WTS is a newer approach that can comprehensively analyze the transcriptome of an organism without relying on annotation. This method sequences the entire complement of RNA sequences, including both known and unknown transcripts. WTS can provide greater resolution for splice variants and more accurate gene expression quantification compared to RNAseq[2].
WTS has several advantages, including the elimination of the need for gene annotation. The technique is also cost-effective since the sequencing depth can be adjusted based on the number of samples analyzed. The method is flexible and can be used in a variety of applications such as identifying regulatory noncoding RNAs and studying alternative splicing events[2].
However, WTS comes with a few drawbacks. The technique requires higher sequencing depth for accurate gene expression quantification, which can increase the cost of the experiment. Additionally, WTS can detect unexpected transcripts or splice variants, creating new challenges for data analysis and interpretation[2].
When to use RNAseq versus WTS
Choosing between RNAseq and WTS depends on the goals of the experiment, the type of RNA to be analyzed, and the available resources. Researchers should consider the complexity of their sample and the genotypic variation, as WTS is better suited for samples with a higher degree of variability. RNAseq is a better choice for studies involving differential expression of known protein-coding genes. In contrast, WTS can identify novel transcripts and regulatory noncoding RNA without relying on a predetermined set of annotated transcripts[3-4].
In conclusion, RNAseq and WTS are both powerful techniques for gene expression analysis. RNAseq is better suited for identifying differentially expressed genes in complex samples with low-abundance genes, while WTS is more effective when searching for novel transcripts and studying alternative splicing events. Both techniques require careful experimental design and bioinformatic analysis for accurate results. Ultimately, researchers should choose the method that aligns with their experimental goals and available resources. Understanding the advantages and disadvantages of each method can help optimize experimental design and result interpretation.
At Champions Oncology, we offer both RNAseq and WTS. We use an enrichment-based RNAseq method when the input RNA is of high quality, while we opt for a depletion-based WTS method when the input RNA quality is lower, with an integrity score as low as 2.0. This approach allows us to utilize different methods in different situations to obtain gene expression results from a broader range of samples.
[1] Martin JA, Wang Z. Next-generation transcriptome assembly. Nat Rev Genet. 2011 Sep 7;12(10):671-82. doi: 10.1038/nrg3068. PMID: 21897427.
[2] Jobanputra V, Wrzeszczynski KO, Buttner R, Caldas C, Cuppen E, Grimmond S, Haferlach T, Mullighan C, Schuh A, Elemento O. Clinical interpretation of whole-genome and whole-transcriptome sequencing for precision oncology. Semin Cancer Biol. 2022 Sep;84:23-31. doi: 10.1016/j.semcancer.2021.07.003. Epub 2021 Jul 10. PMID: 34256129.
[3] Fu X, Fu N, Guo S, Yan Z, Xu Y, Hu H, Menzel C, Chen W, Li Y, Zeng R, Khaitovich P. Estimating accuracy of RNA-Seq and microarrays with proteomics. BMC Genomics. 2009 Apr 16;10:161. doi: 10.1186/1471-2164-10-161. PMID: 19371429; PMCID: PMC2676304.
[4] Ruan M, Liu J, Ren X, Li C, Zhao AZ, Li L, Yang H, Dai Y, Wang Y. Whole transcriptome sequencing analyses of DHA treated glioblastoma cells. J Neurol Sci. 2019 Jan 15;396:247-253. doi: 10.1016/j.jns.2018.11.027. Epub 2018 Nov 22. PMID: 30529802.
Gastrointestinal cancers are a heterogeneous group of cancers that can be caused by H. pylori bacterial or Epstein-Barr virus infection, chronic inflammation, or inherited or spontaneous genetic mutations. Advances in solid tumor immunotherapy for gastrointestinal cancers include the development of methods that improve the screening, evaluation, and development of more precise and robust treatments. Breakthroughs in basic and translational research are leading to better treatment options for gastrointestinal cancer, and CRISPR/Cas9-based (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) gene editing technology is at the forefront of these discoveries.
CRISPR/Cas9-based gene editing technology was originally identified in bacteria and archaea as an antiviral defense mechanism[1]. As a gene editing application, CRISPR/Cas9 uses the Cas9 nuclease to cleave specific sequences in the target DNA and introduces modifications such as knock-in or knock-out mutations[2]. The DNA sequence is targeted using a single-guide RNA (sgRNA) comprised of CRISPR RNA (crRNA) and trans-activating CRISPR RNA (tracRNA), and these RNAs can be expressed on the same plasmid as the Cas9 nuclease upon delivery into target cells. The crRNA/tracrRNA duplex can bind to the complementary sequence in the genomic DNA and recruit Cas9, which cleaves the target sequence and allows for DNA repair by either homology-directed repair or non-homologous end pairing. This repaired sequence is now a part of the genomic DNA and leaves virtually no trace of gene editing.
CRISPR/Cas9 gene editing has been used for several applications in oncology research and more recently to improve immune-oncology strategies. One of the earliest applications involves knockout screens in which a library of sgRNAs is used to transfect a pool of knockouts that can be used for gain-of-function or small molecule/drug screens. Genome-wide screens of cancer cell lines have been useful in identifying genes that are essential to cancer cell growth but can be prone to false-positive hits if the screens are not correctly designed or analyzed[3]. Genome-wide screens have also been used to identify genes linked to resistance, and such gene hits have been identified in a melanoma library screen when treating with the inhibitor vemurafenib[4]. Combinatorial CRISPR/Cas9 screens are now being used to target multiple genes, and this approach can be used for defining genetic or cellular pathways involved in cancer or characterizing drugs that target multiple genes[5].
CRISPR/Cas9 has moved beyond in vitro cell culture and can be used for human organoid models for studying oncogenesis. ARID1A is one of the most frequently mutated genes in solid tumors, including gastric tumors[6]. ARID1A encodes a BAF complex subunit that normally targets BAF to AT-rich DNA sequences to regulate transcription. Mouse studies have suggested that ARID1A is involved in gastrointestinal cancer oncogenesis, but this was not validated in humans until a recent study that used CRISPR/Cas9-mediated depletion of ARID1A wild-type human gastric organoids. This ARID1A-knockout organoid system established a forward genetics model of gastric cancer that resembled gastric cancer phenotypically and identified BIRC5/Survivin as a key player in early tumorigenesis. This type of organoid model is not only useful for basic oncogenesis studies but can be used for small molecule inhibitor screens.
CRISPR/Cas9 screens can be used to validate mutations found in patients with gastrointestinal tumors. Activin A receptor type 2A (ACVR2A) is frequently mutated in patients with microsatellite instability-high gastric cancer, and a 2021 study used CRISPR/Cas9 to generate ACVR2A-knockout human gastric cancer cells[7]. These cells exhibited less aggressive proliferation, migration, and invasion in vitro, and patients with ACVR2A mutations had better prognoses than patients with wild-type ACVR2A. Gastrointestinal stromal tumors (GIST) have been typically characterized by activation mutations in the receptor tyrosine kinase KIT, but a 2022 study using genome-wide CRISPR screening identified the complementary chromatin-modifying complexes MOZ and Menin-MLL as being essential to GIST[8]. This finding highlights a trend in oncology research elucidating a role for chromatin regulation in tumorigenesis, which has the potential to be targeted therapeutically.
Beyond basic research, CRISPR/Cas9 is starting to be used in applications for clinical trials. A Phase II trial has recently launched that is using CRISPR/Cas9 to delete an intracellular checkpoint molecule called cytokine-induced SH2 (CISH) protein[9]. Preclinical studies have shown that CRISPR/Cas9-mediated deletion of CISH enhanced antitumor responses, and the Phase II trial is using patient-derived CRISPR-modified T cells to treat individuals with metastatic gastrointestinal tumors.
CAR T-cells (Chimeric Antigen Receptor) have been an incredible progress in personalized therapy targeting cancer.[10] However, different challenges hampered the availability, efficacy, and safety of this promising cell therapy. CRISPR-Cas9 technology can address many of these limitations. Desired genetic modification can be achieved with cellular precision engineering, leveraging CRISPR-Cas9-based gene editing. In addition, this approach can be exploited to overcome T-cell exhaustion, lack of CAR T-cell persistence, and toxicity related to cytokine release.
In particular, the implementation of CRISPR-Cas9 technology generated universal CAR T Cells resistant to PD1 Inhibition; or enhanced T cell function against bladder cancer disrupting CTLA-4.[11] In the oncolytic therapy field, it has been demonstrated that HSV-1-derived CD40L-armed oncolytic therapy by CRISPR-Cas9-based gene editing boosted endogenous immunity in pancreatic ductal adenocarcinoma.[12]
CRISPR/Cas9 gene editing will continue to transform basic and clinical research, immunotherapy, and cellular therapy providing effective and safe therapeutic strategies. Regulatory agencies are now developing frameworks to allow for the use of this revolutionary tool in a wide range of diseases.
[1] Wiedenheft B, Sternberg SH, Doudna JA. RNA-guided genetic silencing systems in bacteria and archaea. Nature. 2012 Feb 15;482(7385):331-8.
[2] Barrangou R, Doudna JA. Applications of CRISPR technologies in research and beyond. Nat. Biotechnol. 2016;34(9):933-941.
[3] Munoz DM, Cassiani PJ, Li L, Billy E, Korn JM, Jones MD, Golji J, Ruddy DA, Yu K, McAllister G, DeWeck A. CRISPR screens provide a comprehensive assessment of cancer vulnerabilities but generate false-positive hits for highly amplified genomic regions. Cancer Discovery. 2016 Aug 1;6(8):900-13.
[4] Shalem O, Sanjana NE, Hartenian E, Shi X , Scott DA , et al. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science. 2014. 343:84–87.
[5] Han K, Jeng EE, Hess GT, Morgens DW, Li A, Bassik MC. Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions. Nat. Biotechnol. 2017 May;35(5):463-74.
[6] Lo YH, Kolahi KS, Du Y, Chang CY, Krokhotin A, Nair A, Sobba WD, Karlsson K, Jones SJ, Longacre TA, Mah AT, Tercan B, Sockell A, Xu H, Seoane JA, Chen J, Shmulevich I, Weissman JS, Curtis C, Califano A, Fu H, Crabtree GR, Kuo CJ. A CRISPR/Cas9-Engineered ARID1A-Deficient Human Gastric Cancer Organoid Model Reveals Essential and Nonessential Modes of Oncogenic Transformation. Cancer Discov. 2021 Jun;11(6):1562-1581.
[7] Yuza K, Nagahashi M, Ichikawa H, Hanyu T, Nakajima M, Shimada Y, Ishikawa T, Sakata J, Takeuchi S, Okuda S, Matsuda Y, Abe M, Sakimura K, Takabe K, Wakai T. Activin a Receptor Type 2A Mutation Affects the Tumor Biology of Microsatellite Instability-High Gastric Cancer. J. Gastrointest. Surg. 2021 Jan 8. doi: 10.1007/s11605-020-04889-9. Epub ahead of print.
[8] Hemming ML, Benson MR, Loycano MA, Anderson JA, Andersen JL, Taddei ML, Krivtsov AV, Aubrey BJ, Cutler JA, Hatton C, Sicinska E. MOZ and Menin-MLL Complexes are Complementary Regulators of Chromatin Association and Transcriptional Output in Gastrointestinal Stromal Tumor. Cancer Discovery. 2022 May 2.
[10] Jogalekar MP, Rajendran RL, Khan F, Dmello C, Gangadaran P, Ahn BC.Front Immunol. 2022 Jul 22;13:925985. doi: 10.3389/fimmu.2022.925985. eCollection 2022.
[11] Zhang W, Shi L, Zhao Z, Du P, Ye X, Li D, Cai Z, Han J, Cai J. Disruption of CTLA-4 expression on peripheral blood CD8 + T cell enhances anti-tumor efficacy in bladder cancer. Cancer Chemother Pharmacol. 2019;83:911–20.
[12] Wang R, Chen J, Wang W, Zhao Z, Wang H, Liu S, et al. CD40L-armed oncolytic herpes simplex virus suppresses pancreatic ductal adenocarcinoma by facilitating the tumor microenvironment favorable to cytotoxic T cell response in the syngeneic mouse model. J Immunother Cancer. 2022;10(1):e003809.
The development of new oncology treatments has focused on strategies that alter immune responses. Many of these novel therapies use antibodies that bind to receptors on different immune cell subsets and either activate or suppress their functions depending on the immune response being targeted. Antibody-drug conjugates are also becoming more widely used for improved targeting of drugs to specific cell subsets. Flow cytometry-based receptor occupancy (RO) assays are a valuable tool for quantifying cell surface expression of target molecules and are used to generate pharmacodynamic (PD) data, which can be used with pharmacokinetic (PK) data to guide dosing strategies. Consider these different types of receptor occupancy assays as you develop the most useful tools for screening therapeutic molecules.
Total receptor assay: The evaluation of a potential therapeutic target usually begins with an assessment of how many receptors are expressed by a given cell subset. If a receptor is abundantly expressed, it may be a difficult target to use due to potential off-target effects or the requirement of high doses of a therapeutic antibody. Measurement of total receptor involves using a fluorescently labeled antibody that binds to a receptor at a site that is different from the binding site of the therapeutic antibody of interest. Combining data from free and total receptor assays over time is a useful method for measuring the kinetics of antibody binding and calculating potential half-lives of these molecules for therapeutic applications. Consider the type of assay you need for your phase of development. Engage with RO experts who can help you develop validated assays that can be used in preclinical and clinical settings. Flow cytometry-based RO assays will continue to be an essential tool in the development of novel oncology therapeutics.
Recent advances in immunotherapy have led to the development of targeted therapies for treating lymphoma and leukemia. One such therapy is CD19-targeted therapy, which is widely used as a frontline treatment for B cell lymphoma and leukemia. However, despite many patients initially respond well to this therapy relapse remains the major obstacle to be addressed. In this blog post, we will explore the various mechanisms underlying relapse to CD19-targeted therapies in patients with B cell lymphoma and leukemia.
Antigen-positive Relapse:
Early relapse is usually associated with short CAR-T cell persistence. This can be due to poor T cell quality, but, more importantly, it is determined by the costimulatory domain in the CAR. In fact, domains such as 4-1BB have been proven to significantly prolong the persistence of CAR-T cells[1]. In addition, the gene editing technology used to engineer the T cells can make a difference in CAR-T cell persistence. Combination therapies with checkpoint inhibitors have also been shown to prolong response duration and remission[1,2].
Immune Evasion Mechanisms:
One of the primary mechanisms of acquired resistance to CD19-targeted therapies is immune evasion. Cancer cells can develop various mechanisms to evade immune surveillance and avoid being targeted by the therapy. For example, cancer cells may downregulate the expression of CD19 on their surface, thereby reducing the effectiveness of the therapy. Alternatively, they may upregulate other immune checkpoint molecules or express inhibitory proteins that prevent immune cells from recognizing and eliminating them[3].
Antigen Loss Mechanisms:
Another mechanism of acquired resistance is antigen loss. CD19-targeted therapies are designed to bind to and eliminate cancer cells that express the CD19 antigen. However, cancer cells can develop mutations that lead to loss of CD19 expression, rendering the therapy ineffective. This mechanism of resistance has been observed in both lymphoma and leukemia patients, and it is a significant challenge in the development of novel therapies[4].
Development of Alternative Pathways:
Cancer cells that survive CD19-targeted therapies can develop alternative pathways for survival and growth. These pathways can bypass the effects of the therapy and allow cancer cells to continue to proliferate. Examples of such mechanisms include the activation of alternative signaling pathways and the upregulation of survival factors. Understanding these adaptive mechanisms is crucial in devising new therapeutic strategies to overcome acquired resistance[1,3].
Tumor Microenvironment:
The tumor microenvironment (TME) plays a critical role in acquired resistance to CD19-targeted therapies. The TME is a complex milieu of immune and stromal cells that interact with cancer cells to promote tumor growth and survival. The TME can also influence the response of cancer cells to therapy. For example, the presence of immunosuppressive cells in the TME can reduce the effectiveness of CD19-targeted therapies[1,5].
Genetic Factors:
Genetic factors also play a role in acquired resistance to CD19-targeted therapies. For example, mutations in genes involved in DNA repair pathways can increase genomic instability and promote drug resistance. Identifying genetic factors that contribute to resistance can help to personalize therapy and improve outcomes[6].
Disease relapse and development of acquired resistance to CD19-targeted therapies in patients with B cell lymphoma and leukemia pose a significant clinical challenge. To overcome this challenge, we need to find ways to optimize CAR-T cell design to produce more effective therapies and understand the various mechanisms of resistance to be able to develop new therapeutic strategies that target these mechanisms. Research efforts are underway to identify novel therapeutic targets and personalized treatment approaches that can overcome acquired resistance and improve outcomes for patients[7].
Continuous improvements in our understanding of acquired resistance and relapse to CD19-targeted therapies will pave the way for the development of more effective and durable treatments for these diseases. To overcome this challenge, access to relevant preclinical models is key to develop alternative or synergistic therapeutic approaches. Champions Oncology offers a large cohort of B-cell lymphoma and leukemia models, including primary samples from patients who progressed after CD19-targeted therapies, to accelerate the development of novel therapeutic approaches to improve B-cell lymphoma and leukemia patients' lives.
Advances in preclinical oncology research are dependent on gaining insights into tumor biology and applying these insights to the development of novel diagnostics or therapeutics. Next-generation sequencing (NGS) technology has been instrumental in bridging basic immuno-oncology findings and preclinical applications. Here we provide an overview of NGS applications that are transforming preclinical oncology research.
Solid tumors are now understood to have dynamic and unique tumor microenvironments (TMEs) that influence the immune response as well as tumor progression. Combined with flow cytometry and immunohistochemistry, single-cell NGS methods such as scRNA sequencing (scRNA-seq) and Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) allow scientists to measure and understand which cells are present in the TME. These findings may characterize how different stromal cells are present and contributing to tumorigenesis[1] and how the TME can create an immunosuppressive environment[2].
Liquid biopsies have gained popularity as a method to measure circulating tumor cells (CTCs) related to either solid tumor metastasis or hematological malignancies. 
NGS methods have greatly improved insights gained from this sampling method[3]. Previous bulk sampling methods for quantifying CTCs were hampered by sample contamination with leukocytes and the extremely low frequency of CTCs. Single-cell NGS methods, including methods to measure single nucleotide variations as well as large-scale mutations such as copy number variations or chromosomal rearrangements, have provided unprecedented information about CTC specimens in different anatomical locations or over time. These methods have also driven the development of liquid biopsy methods that can be used to track treatment efficacy and the emergence of resistance.
Tumor mutation burden (TMB) is a measurement of mutations within a tumor’s genomic sequence and has emerged as a potential biomarker associated with immune checkpoint inhibitor (ICI) efficacy. Numerous studies have now applied NGS methods to measure TMB in relation to ICI efficacy[4], and robust methods are now being validated for use clinically[5]. These findings have consistently found that high TMB correlates with ICI efficacy, and other NGS-based studies have been used to compare TMB with other genomic aberrations like microsatellite instability[6].
NGS data will continue to provide critical insights into preclinical oncology research and is certain to drive the development of better diagnostics and therapeutics.
[1] Lambrechts D, Wauters E, Boeckx B, et al. (2018). Phenotype molding of stromal cells in the lung tumor microenvironment. Nature Medicine, 24(8), 1277-1289.
[2] Devalaraja S, To TK, Folkert IW, et al. (2020). Tumor-derived retinoic acid regulates intratumoral monocyte differentiation to promote immune suppression. Cell.180(6):1098-114.
[3] Lim SB, Di Lee W, Vasudevan J, et al. (2019). Liquid biopsy: one cell at a time. NPJ Precision Oncology. 3(1):1-9.
[4] Goodman AM, Kato S, Bazhenova L, et al. (2017). Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers. Mol Cancer Ther. 16(11):2598-2608.
[5] Fenizia F, Alborelli I, Costa JL, et al. (2021). Validation of a Targeted Next-Generation Sequencing Panel for Tumor Mutation Burden Analysis: Results from the Onconetwork Immuno-Oncology Consortium. J. Mol. Diagn. S1525-1578(21)00117-3.
[6] Goodman AM, Sokol ES, Frampton GM, et al. Microsatellite-Stable Tumors with High Mutational Burden Benefit from Immunotherapy. (2019). Cancer Immunol. Res. 10:1570-1573.
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TumorGraft3D models are Champions’ three-dimensional (3D) ex vivo tissue cultures that mimic the structure and function of tumors in vivo. They are innovative tools for studying tissue physiology, pathophysiology, and drug discovery. These models can be derived from various tissues, such as the brain, liver, intestine, etc., and can self-organize into complex structures resembling their respective tumor locations and are cultured in a matrix-free environment. The establishment and growth of 3D tissue culture models require the models to interact with the myriad of cellular and structural components within the tumor microenvironment. In this blog, we will explore the differences between matrix and matrix-free conditions in 3D tissue cultures.
Traditionally, 3D tissue culture models have been cultured using a matrix-based approach, where the supportive extracellular matrix (ECM) is derived from natural or synthetic sources. Commonly used matrices include Matrigel, laminin, collagen, and hyaluronic acid. Matrigel is the most commonly used matrix for 3D tissue cultures due to its ability to mimic the natural basement membrane of the tissue. However, using matrices can also pose several challenges, such as batch-to-batch variability, limited scalability, high costs, and difficulty in downstream analysis. Additionally, animal-derived matrices, such as Matrigel, can introduce xenobiotic components that may impact the reproducibility and translatability of the results across the different species.
Matrix-free approaches, on the other hand, offer an alternative to matrix-based assays. These approaches allow the self-organization of 3D tissue culture models without the use of an exogenous matrix. Matrix-free approaches are based on the principle that extracellular matrix components can be provided by the models themselves, where the cellular component of the 3D structure secretes and organizes the matrix components in a more physiological way generating a supportive microenvironment. There are several matrix-free approaches available, including hanging drop and rotary culture. These approaches offer several advantages over matrix-based assays, such as scalability, reproducibility, and compatibility with downstream analysis. In addition, this technique overcomes the species-specific differences between the cells and the matrix which will negatively influence the human translatability of the findings.
Hanging drop cultures involve the formation of 3D tissue culture models in a droplet of culture medium suspended upside down. This method provides a low-adhesion environment for the models to organize and secrete their own matrix components. Rotary culture is another matrix-free approach that involves the constant rotation of a culture vessel, allowing the models to grow and form a 3D structure without the need for a supporting matrix.
Both matrix-based and matrix-free assays have pros and cons for 3D tissue cultures. Matrix-based assays mimic the ECM of the tissue providing an artificial microenvironment for model growth. Beyond batch-to-batch variability, limited scalability, and high costs; including matrix in your ex vivo cultures can also represent a biological problem. Given the artificial architecture of the matrix, it imposes unnatural stiffness and pre-defined structures that will influence the hierarchical organization of the cells during 3D structure generation. Matrix-free assays offer an alternative that eliminates the need for exogenous matrix components and provides a low-adhesion environment for the 3D tissue culture growth for a fully human and more physiological microenvironment. While matrix-free approaches are promising, they are not without their challenges. Specifically, there is the need for ad-hoc development of various protocols for each different tumor type, including rigorous procedures for optimization and standardization to ensure results are reproducible.
In summary, the decision to use matrix or matrix-free culture conditions in 3D tissue culture assays can influence the downstream translatability of your assay. Researchers should evaluate the differences and understand how using a matrix or matrix-free culture conditions can impact their research.
References:
1) Loewa, A., Feng, J.J. & Hedtrich, S. Human disease models in drug development. Nat Rev Bioeng (2023). https://doi.org/10.1038/s44222-023-00063-3
2) Proietto M, Crippa M, Damiani C, Pasquale V, Sacco E, Vanoni M, Gilardi M. Tumor heterogeneity: preclinical models, emerging technologies, and future applications. Front Oncol. 2023 Apr 28;13:1164535. doi: 10.3389/fonc.2023.1164535. PMID: 37188201; PMCID: PMC10175698.
3) LeSavage BL, Suhar RA, Broguiere N, Lutolf MP, Heilshorn SC. Next-generation cancer organoids. Nat Mater. 2022 Feb;21(2):143-159. doi: 10.1038/s41563-021-01057-5. Epub 2021 Aug 12. PMID: 34385685.
4) Kozlowski MT, Crook CJ, Ku HT. Towards organoid culture without Matrigel. Commun Biol. 2021 Dec 10;4(1):1387. doi: 10.1038/s42003-021-02910-8. PMID: 34893703; PMCID: PMC8664924.
Advances in precision medicine have transformed treatments for many types of solid tumors, but similar treatment options have been more limited for hematologic oncology. Now, new ex vivo models are being developed that use patient-derived lymphoma or leukemia cells for screening experimental drugs or biologics.
The lower cost associated with ex vivo studies compared to in vivo ones makes these platforms ideal for large scale screening of therapeutic agents before progressing to in vivo studies with the most promising drug candidates. In addition, lymphoma and leukemia primary cell cultures closely recapitulate the tumor of origin and can provide valuable information about the variability of drug response in a cohort of patients.
In expert hands, these platforms are well-suited to preclinical drug screening and can inform preclinical research decisions as well as clinical care. Some unique aspects of ex vivo hematologic oncology models need to be considered as you advance your research.
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Hematologic oncology models have advanced significantly as ex vivo systems have emerged. Contract research organizations that work in this area have the right expertise and are well poised to help you advance your preclinical therapeutic screening or help you narrow down your drug candidates for potential clinical investigation.
Clinical flow cytometry is now a standard tool used by clinical researchers in numerous fields, especially immuno-oncology. Consider these “Do’s & Don’ts” of clinical flow cytometry as you decide to use this tool for clinical research.
Do Perfect Your Panel - A staining panel includes the set of antibodies used to identify different cell subsets within a sample and depends on the use of multiple antibodies conjugated with different fluorochromes. These fluorochromes are excited by specific light wavelengths from the cytometer’s lasers, and the emitted light is analyzed and interpreted as different cell types. Researchers take time to develop staining panels that can reasonably distinguish between cell types and avoid aberrations such as spectral overlap.
Do Vigilant Validation - Clinical flow cytometry assay development must satisfy certain criteria, including accuracy, specificity, limit of detection, reproducibility, precision, linearity, and stability. By satisfying these criteria, researchers are able to have confidence in their clinical data, even if experiments were done at different times or in different locations.
Do Maintenance - Reliable flow cytometry data requires a well-designed and validated protocol as well as a properly maintained cytometer. Routine maintenance is carried out by cytometer users to assure that fluidic systems flow properly, lasers are firing correctly, and the emitted light is detected at the expected wavelength. Infrequent, but more involved, maintenance is carried out by technicians and is essential to the long-term functionality of a cytometer.
Don’t Pick the Wrong Test Tube - The very first step of a clinical flow cytometry protocol is collecting a sample, which is typically peripheral blood, cord blood, or tissue biopsy. These samples can be collected in tubes with preservatives or anti-clotting agents, but some of these additives can alter cell viability. It is worthwhile to evaluate different sample tube types to assure that your cells of interest are not being lost or damaged due to test tube effects.
Don’t Lose your Cells - Clinical flow cytometry protocols rely on the acquisition of thousands to millions of cells per sample in order to have a reasonable number of events to analyze. One essential step to acquiring usable data is the inclusion of a viability dye that discriminates between live and dead cells. Viability dyes come in different formats that work with specific flow cytometer configurations, so it is critical to determine which dye will work with your cytometer.
Don’t Screw Up Your Analysis - After you have completed the laborious process of sample staining and data acquisition on a cytometer, it is essential to execute the appropriate data analysis. Be sure you understand how to use the software needed for analysis, and this may mean including certain controls in your staining and acquisition protocols. Errors in analysis may result in your data being inaccurate or undetected.
There are many considerations needed for a clinical flow cytometry protocol, and it may be worthwhile to work with experts in protocol development, assay validation, or general clinical flow cytometry.
Bladder cancer is a relatively common form of cancer that is defined as either pre-invasive or invasive, and non-muscle invasive bladder cancer (NMIBC) is the most commonly diagnosed subtype[1]. NMIBC is typically treated by surgical resection and/or intravesical delivery of chemo- or immunotherapy-based adjuvant treatment, and long-term efficacy is monitored by urine testing or cystoscopy. Muscle-invasive bladder cancer (MIBC) is relatively resistant to current treatment options and occurs more frequently in men. MIBC also has high rates of morbidity and mortality, and novel therapies or combination therapies are being developed to better treat this form of bladder cancer.
Here we highlight recent findings about invasive bladder cancer biology and how these observations are informing the development of new therapies.
Analysis of MIBC genomes has revealed a high mutation rate in tumors that approaches rates seen in melanoma and lung cancer[2]. The mutational signature of many MIBC tumors is consistent with mutations associated with APOBEC (apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like) cytidine deaminase, and many of the mutations are clonal, which suggests that the effects of APOBEC expression in bladder tissue occurs early in tumorigenesis. Non-invasive and invasive bladder tumors are also often classified as being highly heterogeneous, and tumor histology can be extremely variable and includes squamous, plasmacytoid, micropapillary, and small-cell carcinoma. This molecular and histological heterogeneity presents a challenge in subtyping tumors based on gene expression profiles and provides insight into why it can be difficult to identify targeted therapies that are effective against bladder cancers.
Several genes are commonly mutated in both NMIBC and MIBC, but mutation rates for some of these genes, including MLL2 and TP53, are higher in invasive tumors[3]. TP53 mutations appear to be a critical factor associated with the transition to its invasive form. Mutations have also been identified in genes associated with the sister chromatid cohesion and segregation process (STAG2, ESPL1, FGFR3, and TACC3)[3] and chromatin remodeling (UTX, MLL-MLL3, CREBBP-EP300, NCOR1, ARID1A, and CHD6)[4].
NIMBC is one of the first forms of cancer treated with an immunotherapy approach in which the attenuated tuberculosis bacterial vaccine, Bacillus Calmette-Guérin (BCG), is delivered intravesically to the bladder and triggers an immune response that inhibits tumor growth[5]. Recently, immune checkpoint inhibitor-based treatments have been examined as therapeutic options for different bladder cancers. Expression of the PD-L1 immune checkpoint molecule has been detected on both NIMBC and MIBC tumor cells and tumor-infiltrating mononuclear cells. Antibody-based blockade of PD-1/PD-L1 interactions restores anti-tumor responses mediated by T cells. Atezolizumab was the first PD-L1 inhibitor approved for the treatment of locally advanced/ metastatic urothelial carcinoma (LA/mUC) that has progressed or after cisplatin-based chemotherapy[6], and five different PD-L1/PD-1 inhibitors have been approved for this form of bladder cancer. Other checkpoint inhibitors that target different molecules have not shown significant improvements in overall survival or progression-free survival. Clinical trials currently underway are examining the efficacy of combinations of checkpoint inhibitors or the use of these inhibitors as an adjuvant therapy to surgical resection or chemotherapy. In addition, therapies that target specific mutations, such as FGFR, HER2, or chromatin-modifying genes, are also under investigation, and the FGFR inhibitor erdafitinib was recently approved for the treatment of LA/mUC[7][8].
Bladder cancer treatment outcomes continue to advance because of insights into the basic biology of bladder cancer, and a better understanding of molecular and immunological mechanisms associated with anti-tumor responses. The many preclinical and clinical studies currently underway for bladder cancer will contribute valuable information to new therapeutic options, especially for patients with refractory or invasive forms of bladder cancer.
[1] Knowles MA, Hurst CD. Molecular Biology of Bladder Cancer: New Insights into Pathogenesis and Clinical Diversity. Nat Rev Cancer. 2015;15:25–41.
[2] Robertson AG, Kim J, Al-Ahmadie H, et al. Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. Cell. 2017;171(3):540-556.e25.
[3] Guo G, Sun X, Chen C, et al. Whole-Genome and Whole-Exome Sequencing of Bladder Cancer Identifies Frequent Alterations in Genes Involved in Sister Chromatid Cohesion and Segregation. Nat Genet. 2013;45(12):1459-1463.
[4] Gui Y, Guo G, Huang Y, et al. Frequent Mutations of Chromatin Remodeling Genes in Transitional Cell Carcinoma of the Bladder. Nat Genet. 2011;43(9):875-878.
[5] Herr HW and Morales A. History of Bacillus Calmette-Guerin and Bladder Cancer: An Immunotherapy Success Story. J Urol. 2008;179.1: 53-56.
[6] Bellmunt J, Powles T, Vogelzang NJ. A Review on the Evolution of PD-1/PD-L1 Immunotherapy for Bladder Cancer: The Future is Now. Cancer Treat. Rev. 2017;54:58-67.
[7] Osterman CK, Milowsky MI. New and Emerging Therapies in the Management of Bladder Cancer. F1000Res. 2020;9:F1000 Faculty Rev-1146. 1
[8] Loriot Y, Necchi A, Park SH, et al. Erdafitinib in Locally Advanced or Metastatic Urothelial Carcinoma. N Engl J Med. 2019 Jul 25;381(4):338-348.
Head and neck squamous cell carcinoma (HNSCC) is one of the most common forms of cancer in the world. This heterogeneous disease is most often seen in men and is closely linked to tobacco usage, which can be enhanced by alcohol usage. Human papillomavirus (HPV) infection is an independent risk factor for HNSCC[1], and most HPV- HNSCCs occur in the larynx and oral cavity, and HPV+ HNSCCs typically arise in the oropharynx[2]. Both HPV+ and HPV- HNSCCs are typically diagnosed at advanced disease stages and are often treated with an aggressive combination of surgery, radiotherapy (RT), and chemotherapy[3]. More recently, cetuximab, an IgG1 monoclonal antibody that targets epidermal growth factor receptor (EGFR) has been used in combination with radiotherapy and has shown some improvements in progression-free survival (PFS) and overall survival (OS)[4].
Advances in genomic technology have provided critical insights into the pathology of HNSCC subtypes. Some HNSCCs are now known to have high mutational burdens, which is like other cancers associated with carcinogen exposure. Analysis of HPV- and HPV+ HNSCCs in The Cancer Genome Atlas (TGCA) network has been instrumental in identifying genome defects common to both HPV+ and HPV- HNSCCs, as well as defects that are unique to each of these subtypes. Global analysis of all HNSCC subtypes identified TP53 as the most commonly mutated gene, but there tends to be a lower percentage of TP53 mutations in HPV+ tumors versus HPV- tumors, likely related to HPV infection[5]. Activating mutations in PIK3CA and inactivating mutations in NOTCH1 are associated with both types of HNSCC. HPV- HNSCCs show inactivating mutations in TP53 and CDKN2A cell cycle suppressor genes and amplification of CCND1, which can all contribute to unchecked cell cycle progression. In contrast, HPV+ HNSCCs show expression of the E6 and E7 viral oncogenes, which can inhibit TP53 and RB1, as well as activation of cell cycle regulator E2F1[6]. Mutations in the MAPK signaling component HRAS have also been identified in a fraction of HNSCC specimens for which treatment options are limited. A recent clinical trial demonstrated encouraging efficacy in patients with recurring or metastatic HNSCCs carrying HRAS mutations[7] treated with tipifarnib, which is a farnesyltransferase inhibitor that can inhibit farnesylation of HRAS and membrane targeting and downstream signaling.
In addition to targeted therapies, recent studies suggest that PD-1/PD-L1 blockade alone or in combination with chemotherapy can improve overall survival in patients with recurrent or metastatic HNSCC[8],[9]. PD-1 blockade has shown better survival, toxicity, and response duration compared with cetuximab treatment combined with chemotherapy, but these responses are dependent on patients having HNSCC tumors that are positive for PD-L1. Tumor mutational burden and the expression of inflammatory biomarkers also correlated directly with responses to PD-1 blockade.
Recent insights into genomic variations associated with HNSCC subtypes are providing valuable information with respect to basic tumor biology as well as identifying potential therapeutic targets for preclinical development.
[1] Cognetti DM, Weber RS, Lai SY. Head and neck cancer: an evolving treatment paradigm. Cancer. 113(7 Suppl):1911-1932 (2008).
[2] Mehanna H, Beech T, Nicholson T, El-Hariry I, McConkey C, Paleri V, Roberts S. Prevalence of human papillomavirus in oropharyngeal and nonoropharyngeal head and neck cancer--systematic review and meta-analysis of trends by time and region. Head Neck. 35(5):747–55 (2013).
[3] Pignon J P, le Maître A, Maillard E, Bourhis J. & MACH-NC Collaborative Group. Meta-analysis of chemotherapy in head and neck cancer (MACH-NC): An update on 93 randomized trials and 17,346 patients. Radiother. Oncol. 92(1), 4–14 (2009).
[4] Bonner JA, et al. Radiotherapy plus cetuximab for locoregionally advanced head and neck cancer: 5-year survival data from a phase 3 randomized trial, and the relation between cetuximab-induced rash and survival. Lancet Oncol. 11, 21–28 (2010).
5] Westra, W. H. et al. The inverse relationship between human papillomavirus-16 infection and disruptive p53 gene mutations in squamous cell carcinoma of the head and neck. Clin. Cancer Res. 14, 366–369 (2008)
[6] Beck TN, Golemis EA. Genomic insights into head and neck cancer. Cancers Head Neck 1, 1 (2016).
[7] Ho AL, Brana I, Haddad R. et al. Tipifarnib in Head and Neck Squamous Cell Carcinoma with HRAS Mutations. J. Clin. Oncol. JCO2002903 (2021).
[8] de Sousa LG, Ferrarotto R. Pembrolizumab in the first-line treatment of advanced head and neck cancer. Expt. Rev. Anticanc. Ther. 21.12: 1321-1331 (2021).
[9] Haddad RI, Seiwert TY, Chow LQM et al. Influence of tumor mutational burden, inflammatory gene expression profile, and PD-L1 expression on response to pembrolizumab in head and neck squamous cell carcinoma. J. Immunother. Cancer. 2022 Feb;10(2):e003026.
Acute myeloid leukemia (AML) is an aggressive hematological malignancy and the most common leukemia among the adult population. Despite the development of novel targeted therapies, resistance to treatments and disease relapse remain unsolved. New interest in the role of circular RNA in AML biology has opened the way for the development of new approaches in the management of AML.
Somatic mutations in the additional sex comb-like 1 (ASXL1) gene have been identified in multiple hematologic malignancies, including acute myeloid leukemia (AML), and are associated with poor prognoses1. ASXL1 encodes a nuclear protein that regulates epigenetic remodeling and transcription through interactions with polycomb complex proteins and transcriptional activators and repressors. Several ASXL1 mutations have been associated with loss of protein expression that leads to myeloid transformation2. In contrast, gain-of-function mutations in ASXL1 result in expression of a truncated ASXL1 protein that can bind to BRCA-1 associated protein 1 (BAP1) and cause leukemogenesis3,4. Targeted reduction of BAP1 activity is sufficient to prevent this malignancy process5.
A recent study has shown that the ASXL1 gene locus undergoes alternative splicing to produce circular RNAs (circRNAs) in addition to linear protein-coding mRNAs6. CircRNAs are non-coding RNAs that normally function as regulators of gene expression and translation by acting as sponges for microRNAs or forming complexes with RNA-binding proteins. Here they identified two isoforms of circular ASXL1 (circASXL1), and they showed that circASXL1-1 can bind to BAP-1 and regulate BAP1-mediated deubiquitinase activity, which targets H2AK119 ubiquitination and regulates myeloid differentiation of hematopoietic stem cells. These findings suggest that circRNAs may be developed as novel therapeutics for treating hematologic malignancies like AML.
Resistance to anti-cancer treatments is a significant therapeutic challenge and is typically associated with mutations in signaling pathways that are involved in cell proliferation, survival, and tumorigenesis. Genomic analyses of relapsed pediatric acute myeloid leukemia (AML) patients have identified mutations, deletions, and changes in promoter methylation associated with Wnt-β-catenin signaling[1],[2]. Mutations in the PI3K-Akt pathway are also frequently associated with treatment resistance in AML and many other cancers[3],[4]. Hematopoietic stem cells are particularly sensitive to mutations in these signaling pathways and numerous studies have shown that targeting each of these pathways separately is associated with poor efficacy and the emergence of resistance[5]. AML resistance not only emerges from chemotherapy but can also be seen in response to immunotherapy[6].
Combined therapies are emerging as a strategy to overcome treatment resistance. Numerous clinical trials are examining the efficacy of combining chemotherapy and immunotherapy-based approaches or using differing immunotherapy combinations to enhance anti-tumor immunity. Other studies are seeking to use existing drugs in different ways to avoid resistance. A recent study has shown that the anthracycline antibiotic doxorubicin (DXR) can be repurposed as a β-catenin inhibitor that targets leukemia stem cells (LSCs)[7]. 
DXR has typically been used as a chemotherapeutic agent at high doses but is associated with significant toxicity. In this study, activation of both the Wnt-β-catenin and PI3K-Akt pathways are associated with the expansion of LSCs. A high throughput screening of a small molecule library identified DXR as an inhibitor of β-catenin activation mediated by interactions with Akt, and low-dose DXR treatment was sufficient to inhibit LSC expansion, even in chemo-resistant pS552-β-cat+ LSCs. DXR could also reduce the expression of the immune checkpoint molecules PD-L1, TIM3, and CD24 on LSCs and thus reverse immune checkpoint-mediated resistance. Findings from a pilot clinical trial indicated that low-dose treatment with the DXR analogue daunorubicin of adult patients with relapsed or refractory AML can specifically target chemo-resistant pS552-β-cat+ LSCs.
Future studies using next-generation sequencing technology, computational analysis, and high throughput screening will continue to advance the development of treatments for relapsed or refractory cancers. Progress also continues to be made in advancing combined treatments for both hematological malignancies and solid tumors.
1. Hogan, L. E. et al. Integrated genomic analysis of relapsed childhood acute lymphoblastic leukemia reveals therapeutic strategies. Blood. 2011; 118: 5218–5226.
2. Bolouri, H. et al. The molecular landscape of pediatric acute myeloid leukemia reveals recurrent structural alterations and age-specific mutational interactions. Nat. Med. 2018; 24: 103–112.
3. Koren, S. & Bentires-Alj, M. Tackling resistance to PI3K inhibition by targeting the epigenome. Cancer Cell. 2017; 31: 616–618.
4. Lindblad, O. et al. Aberrant activation of the PI3K/mTOR pathway promotes resistance to sorafenib in AML. Oncogene. 2016; 35: 5119–5131.
5. Fruman, D. A. & Rommel, C. PI3K and cancer: lessons, challenges and opportunities. Nat. Rev. Drug Discovery. 2014. 13; 140–156.
6. Sharma, P. et al. Primary, adaptive, and acquired resistance to cancer immunotherapy. Cell. 2017. 168; 707–723.
7. Perry, J.M. et al. Overcoming Wnt-β-catenin dependent anticancer therapy resistance in leukemia stem cells. Nat Cell Biol. 2020. 22(6); 689-700.
Renal cell carcinoma (RCC) is a common cancer of the genitourinary tract that has very poor survival outcomes if metastatic. RCC is now understood to be composed of several different types of cancer with different genetic features and varied clinical responses. Histological diagnosis has been the primary method to diagnose RCC and has been used to define three major RCC subtypes, including the most common subtype, clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (PRCC; further divided into two subtypes), and chromophobe renal cell carcinoma (ChRCC)[1]. More recent comparative genomic and phenotypic analysis has identified mutations and epigenetic modifications associated with different histological subtypes[2]. Across all subtypes, increased DNA hypermethylation and gene alterations in CDKN2A were associated with a poor prognosis as was an increased Th2 immune gene signature. For ccRCC, increased levels of mRNA transcripts associated with ribose metabolism and the immune response were associated with poor survival. ccRCC is also defined by the early loss of chromosome 3p, which in turn causes a loss of heterozygosity for the VHL, PBRM1, SETD2, and BAP1 tumor suppressor genes and subsequent mutation of these genes that leads to tumorigenesis[3]. There is also a subset of ChRCC with a unique metabolic expression pattern that is associated with extremely poor survival[2]. PRCC can be classified as type 1, for which PBRM1 mutations are linked to poor survival but type 2 PRCC has increased expression of glycolysis and metabolism-related mRNA transcripts[2].
ccRCC tumors with VHL mutations show overexpression of vascular endothelial growth
factor (VEGF) and hypoxia-inducible factors (HIFs) can contribute to angiogenesis and cancer progression. Similarly, some RCCs show hyperactivation of the serine/threonine kinase mammalian target of rapamycin (mTOR), which can lead to the overproduction of VEGF. VEGFR inhibitors and anti-VEGF antibodies have been tested as therapies for RCC, and the anti-VEGF antibody bevacizumab has been approved for use in combination with IFN-α for metastatic RCC[4]. The mTOR inhibitors everolimus and temsirolimus have also been approved for the treatment of RCC, typically in combination with tyrosine kinase inhibitors (TKIs)[5]. Combination therapies that target VEGF and mTOR are considered more effective since they work in concert to target tumor growth and vascularization, whereas sequential treatments are typically associated with a greater likelihood of tumors developing resistance[6]. Unfortunately, these combination therapies are associated with undesirable toxicities and have not been linked with durable responses[7].
Advances in immunotherapy have led to transformative treatment options for RCC. Immune checkpoint blockade (ICB) has been one promising treatment strategy, and the FDA approved the use of anti-PD-1/PD-L1 (nivolumab) for the treatment of advanced ccRCC in 2015[8]. A follow-up study showed that anti-PD-1 was associated with the best clinical benefit in ccRCC carrying loss-of-function mutations in PBRM1, which appears to affect tumor expression profiles in such a way to maintain responsiveness to checkpoint blockade[9]. Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) is another checkpoint molecule targeted for checkpoint blockade with the monoclonal antibody ipilimumab. Similar to PD-L1 blockade, CTLA-4 blockade was associated with a partial response against metastatic RCC. Combination therapies have shown much more durable responses in patients with advanced RCC, and the FDA approved the use of nivolumab plus ipilimumab for the treatment of intermediate or high-risk metastatic RCC in 2018[10]. ICB blockade in combination with TKI are also under investigation as alternative first or second-line treatments. Unfortunately, PD-1/PD-L1 blockade has been less successful for PRCC[11] and ChRCC[12], and further studies are needed to identify therapeutic targets in these forms of RCC. Clinical studies with other checkpoint blockade targets are currently underway and are likely to provide new treatment options to RCC patients[13].
The future of RCC therapies relies on the identification of new molecules or pathways in tumor cells that can be targeted therapeutically without causing toxicity or promoting resistance. Advances in single-cell omics are leading the way in terms of target identification and understanding how different forms of RCC progress.
[1] Hsieh JJ, Purdue MP, Signoretti S, Swanton C, Albiges L, Schmidinger M, Heng DY, Larkin J, Ficarra V. Renal cell carcinoma. Nat Rev Dis Primers. 2017;3:17009.
[2] Ricketts CJ, De Cubas AA, Fan H, et al. The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma [published correction appears in Cell Rep. 2018 Jun 19;23(12):3698]. Cell Rep. 2018;23(1):313-326.e5.
[3] Turajlic S, Swanton C, Boshoff C. Kidney cancer: The next decade. J Exp Med. 2018;215(10):2477-2479. doi:10.1084/jem.20181617
[4]Rini BI, Halabi S, Rosenberg JE, et al. Phase III trial of bevacizumab plus interferon alfa versus interferon alfa monotherapy in patients with metastatic renal cell carcinoma: final results of CALGB 90206. J Clin Oncol. 2010;28(13):2137-2143.
[5] Leonetti A, Leonardi F, Bersanelli M, Buti S. Clinical use of lenvatinib in combination with everolimus for the treatment of advanced renal cell carcinoma. Ther Clin Risk Manag. 2017 Jun 30;13:799-806.
[6] Gore ME, Larkin JM. Challenges and opportunities for converting renal cell carcinoma into a chronic disease with targeted therapies. Br J Cancer. 2011 Feb 1;104(3):399-406.
[7] Escudier B: Emerging immunotherapies for renal cell carcinoma. Ann Oncol 23:viii35-viii40, 2012 (suppl 8).
[8] Motzer RJ, Escudier B, McDermott DF, et al. Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma. N Engl J Med. 2015;373(19):1803-1813.
[9] Miao D, Margolis CA, Gao W, Voss MH, Li W, Martini DJ, Norton C, Bossé D, Wankowicz SM, Cullen D, Horak C, Wind-Rotolo M, Tracy A, Giannakis M, Hodi FS, Drake CG, Ball MW, Allaf ME, Snyder A, Hellmann MD, Ho T, Motzer RJ, Signoretti S, Kaelin WG Jr, Choueiri TK, Van Allen EM. Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma. Science. 2018 Feb 16;359(6377):801-806.
[10] Hammers HJ, Plimack ER, Infante JR, Rini BI, McDermott DF, Lewis LD, Voss MH, Sharma P, Pal SK, Razak ARA, Kollmannsberger C, Heng DYC, Spratlin J, McHenry MB, Amin A. Safety and Efficacy of Nivolumab in Combination With Ipilimumab in Metastatic Renal Cell Carcinoma: The CheckMate 016 Study. J Clin Oncol. 2017 Dec 1;35(34):3851-3858.
[11] de Vries-Brilland, Manon, et al. Are immune checkpoint inhibitors a valid option for papillary renal cell carcinoma? A multicentre retrospective study. European Journal of Cancer 2020; 136:76-83.
[12] Schwartzman, William, et al. "Safety and efficacy of immune checkpoint inhibitors (ICI) in metastatic non-clear cell renal cell carcinoma (nccRCC): An institutional experience." J. Clin Oncol. 2020: 640.
[13] Mollica V, Di Nunno V, Gatto L, Santoni M, Cimadamore A, Cheng L, Lopez-Beltran A, Montironi R, Pisconti S, Battelli N, Massari F. Novel Therapeutic Approaches and Targets Currently Under Evaluation for Renal Cell Carcinoma: Waiting for the Revolution. Clin Drug Investig. 2019 Jun;39(6):503-519.
Tumor-infiltrating lymphocyte (TIL)-based immunotherapy is currently at the forefront of cutting-edge immuno-oncology treatments. TILs are a type of adoptive cellular therapy (ACT) using lymphocytes that are found within tumor tissues; most of these lymphocytes are T cells that can specifically target tumor cells. For TIL-based therapies, these T cells are harvested from a tumor biopsy, expanded ex vivo, and infused back into the patient. Advances in TIL-based therapies are driven by preclinical characterization and screening of TILs against a wide array of tumor types.
Consider these factors related to preclinical TIL therapy studies as you develop new research protocols:
Cell Selection: Optimal TIL culture conditions should enhance the expansion of tumor-specific T cells but may also involve a step to deplete other cells prior to expansion. This may involve the depletion of adherent cell subsets with immunosuppressive characteristics such as myeloid-derived suppressor cells (MDSCs). Removing these cells from ex vivo culture allows TILs to expand and differentiate into T cells with tumor-specific cytotoxic activity.
Preclinical TIL studies are continuing to expand the usage of TIL-based therapies against a wide range of solid tumors, and this field of study will advance further as ex vivo culture and analysis techniques improve.
Flow cytometry is a semi-quantitative method that is widely used for preclinical and clinical studies. Preclinical flow cytometry experiments rely on users who understand the fundamentals of setting up appropriate standards and controls, but these protocols do not need to typically meet specific clinical standards. In contrast, clinical flow cytometry protocols require adherence to good clinical laboratory practice (GCLP) standards. Here we provide an overview of GCLP standards with respect to clinical flow cytometry.
GCLP guidelines were developed in the early 2000s to provide a regulatory framework for labs performing assays for HIV-1 clinical trials. A large portion of these assays were flow cytometry-based[1] and were being conducted on flow cytometers at multiple global sites, thus necessitating standardization. GCLP guidelines are a type of regulatory standard, with similarities to good laboratory practice (GLP) and clinical laboratory improvement amendments (CLIA) and have become essential to harmonizing clinical laboratory work taking place at different sites and times for clinical trials. GCLP standards can be applied to labs carrying out safety, diagnostic, or endpoint assays, and have been critical to the evaluation of immuno-oncology drugs and biologics being evaluated in clinical trials.
GCLP guidelines include personnel organization and training, equipment maintenance and validation, the development and validation of standard operating procedures (SOPs), assay development and validation, and audits to identify discrepancies in any of these areas[2]. GCLP procedures for clinical flow cytometry assure that flow cytometers at different sites are performing consistently and within standards. Flow cytometry reagents are parallel tested with previous lot to assure their eligibility for use in an assay. Throughout the implementation of GCLP guidelines, a laboratory must maintain a document control plan that includes all SOPs currently in use and an archive system for SOPs that are no longer in use.
A quality control (QC) program is essential to a GCLP framework as it allows for the monitoring, documentation, and recognition of QC problems. QC programs track test standards, positive and negative controls, reagent performance, QC data analysis and logs, and parallel testing. QC is especially important for clinical flow cytometry to assure that the appropriate cell populations are being analyzed in a consistent and reproducible manner.
A proficiency testing program is another critical component of GCLP program because it involves analysis of a common set of samples by multiple laboratory sites to assure that performance can meet specific criteria[3]. Clinical flow cytometry assays typically lack “gold standard” samples for evaluation because cells that are being analyzed in this manner are subject to intra- and inter-sample variability. Nonetheless, samples can be expected to fall within a specific predetermined range, thus assuring that the GCLP-compliant protocol, users, and equipment are performing proficiently.
GCLP standards for clinical flow cytometry are now being applied in different ways, including complex immunophenotyping of multiple immune cell subsets, comprehensive measurement of immune checkpoint molecule expression on T cells, and receptor occupancy assessment of therapeutic antibodies. The development of GCLP guidelines is often carried out with GCLP professionals who can advise on all aspects of this complex undertaking. Alternatively, individual assays, such as clinical flow cytometry experiments can be carried out by contract research organizations who are already GCLP compliant and experienced with running these assays.
[1] Todd CA, Sanchez AM, Garcia A, Denny TN, Sarzotti-Kelsoe M. Implementation of Good Clinical Laboratory Practice (GCLP) guidelines within the External Quality Assurance Program Oversight Laboratory (EQAPOL). J. Immunol. Methods. 2014;409:91-98.
[2] Sarzotti-Kelsoe M, Cox J, Cleland N, et al. Evaluation and recommendations on good clinical laboratory practice guidelines for phase I-III clinical trials. PLoS Med. 2009;6(5):e1000067.
[3] O'Hara, Denise M., et al. Recommendations for the validation of flow cytometric testing during drug development: II assays. J. Immunol. Methods. 363.2 (2011): 120-134.
Biliary tract cancers, which are also known as cholangiocarcinomas (CCA), describe malignancies that occur in the biliary tract and include the pancreas, gallbladder, and bile ducts. These are relatively rare cancers but are associated with a poor prognosis given that these cancers are difficult to detect and are usually diagnosed at later stages of the disease.
CCAs are classified by growth pattern as mass forming, intraductal, or periductal, anatomical location as intrahepatic or extrahepatic (perihilar, or distal), and histology (predominantly adenocarcinomas with mixed hepatocellular CCAs are defined as a separate subtype of primary hepatic cancer) [1].
CCAs can arise de novo with no discernable risk factors, but a variety of genetic and nongenetic risk factors are associated with CCA, including liver cirrhosis, obesity, type 2 diabetes, chronic hepatitis B or C infection, or infection with hepatobiliary flukes [2]. Individuals with primary sclerosing cholangitis have higher levels of chronic liver inflammation and increased incidence of CCA [3] as well. CCAs are typically aggressive cancers with a median overall survival of < 24 months. The only treatment options have been surgical resection or liver transplantation for early-stage patients or aggressive chemotherapy for patients with advanced stages of the disease [4].
Next-generation sequencing technology has allowed the identification of molecular subtypes associated with several gene mutations that are linked to increased CCA risk, including mutations in chromatin remodeling genes (ARID1A, BAP1, and PBRM1) [5,6]. IDH1 mutations have been linked to intrahepatic CCA and mutations in ERBB2 are more closely associated with extrahepatic CCA [7].
Mutations in the fibroblast growth factor (FGF) signaling pathway, including mutations or translocations in FGF receptor (FGFR) genes, have also been identified in CCA, and an FGFR fusion has been linked specifically to intrahepatic CCA [8]. Moreover, patients with IDH1/2 mutations also exhibit elevated FGFR expression, even without FGFR mutations or fusions, further affirming a role for FGF/FGFR signaling in CCA progression[9]. In addition to tumor cell alterations, the tumor microenvironment is also being extensively explored and has led to the identification of an inflamed intrahepatic CCA subtype potentially treatable with checkpoint blockade immunotherapy [10].
The FGF/FGFR pathway has become one of the most encouraging targets for novel
CCA therapeutics. As FGFRs are receptor tyrosine kinases, nonselective FGFR inhibitors that target the conserved ATP-binding domain were the first drugs to be tested in clinical trials. A recent trial exploring the use of the nonselective FGFR kinase inhibitor pazopanib combined with a MEK inhibitor showed little efficacy [11].
Pemagatinib is the first FDA-approved targeted therapy for advanced CCA with FGFR2 fusions or rearrangements. Pemagatinib is a selective inhibitor of FGFR1, 2, and 3 and was approved in 2020 and given breakthrough therapy designation as the first drug to specifically treat CCA [12].
In 2021, Ivosidenib (Tibsovo), a small molecule IDH1 inhibitor, was approved by the FDA for treating IDH1 mutated locally advanced or metastatic CCA [13].
Very recently, the FDA has granted accelerated approval to two FGFR inhibitors: Infigratinib (Truseltiq), for the treatment of previously treated, unresectable, locally advanced or metastatic cholangiocarcinoma with FGFR2 fusion (and a companion diagnostic to identify patients eligible to receive this treatment) [14,15]; and Futinatinib (TAS-120) for patients with previously treated, unresectable, locally advanced or metastatic intrahepatic CCA with FGFR2 gene fusions or other rearrangements [16,17].
Alternative FGF/FGFR inhibitors are also under development and target the extracellular domain or function as FGF ligand traps [18]. These alternative inhibitors can be used potentially in combination with FGFR kinase inhibitors that have lost efficacy due to the development of resistance [19].
In addition to mutation-driven therapeutic approaches, immune checkpoint inhibitors are currently tested in combination with chemotherapy to improve efficacy. A very recent study conducted on patients with advanced biliary tract cancer showed that Durvalumab, a PD-L1 inhibitor, significantly improves survival compared to chemotherapy alone [20].
New research on novel inhibitors and combination therapies will likely identify other therapeutic options for CCA, and these cancers will not be the terminal diagnoses they once were.
Razumilava N, Gores Cholangiocarcinoma. Lancet. 2014;383(9935):2168- 79.
Yao KJ, Jabbour S, et al. Increasing mortality in the United States from cholangiocarcinoma: an analysis of the National Center for Health Statistics Database. BMC Gastroenterol. 2016;16(1):117.
Hirschfield GM, Karlsen TH, et Primary sclerosing cholangitis. Lancet. 2013;382(9904):1587-99.
Yazici C, Niemeyer DJ, et al. Hepatocellular carcinoma and cholangiocarcinoma: an Expert Rev Gastroenterol Hepatol. 2014;8(1):63-82.
Jusakul A, Cutcutache I, et al. Whole‐genome and epigenomic landscapes of etiologically distinct subtypes of cholangiocarcinoma. Cancer Discov 2017;7:1116‐1135
Jiao Y, Pawlik TM, et al. Exome sequencing identifies frequent inactivating mutations in BAP1, ARID1A, and PBRM1 in intrahepatic Nat Genet. 2013;45:1470–3.
Churi CR, Shroff R, et Mutation profiling in cholangiocarcinoma: prognostic and therapeutic implications. PLoS One. 2014;9:e115383.
Graham RP, Barr Fritcher EG, et al. Fibroblast growth factor receptor 2 translocations in intrahepatic Hum Pathol. 2014;45(8):1630- 1638.
Wang P, Dong Q, et Mutations in isocitrate dehydrogenase 1 and 2 occur frequently in intrahepatic cholangiocarcinomas and share hypermethylation targets with glioblastomas. Oncogene. 2013;32(25):3091-3100.
Job S, Rapoud D, et al.. Identification of Four Immune Subtypes Characterized by Distinct Composition and Functions of Tumor Microenvironment in Intrahepatic Cholangiocarcinoma. Hepatology. 2020 Sep;72(3):965-981
Shroff RT, Yarchoan M, O’Connor A, et The oral VEGF receptor tyrosine kinase inhibitor pazopanib in combination with the MEK inhibitor trametinib in advanced cholangiocarcinoma. Br J Cancer. 2017;116(11):1402-1407.
Patel TH, Marcus L, et al. FDA Approval Summary: Pemigatinib for Previously Treated, Unresectable Locally Advanced or Metastatic Cholangiocarcinoma with FGFR2 fusion or other rearrangements. Clin Cancer Res. 2022 Oct 7:CCR-22-2036.
Sumbly V, Landry I, Rizzo V. Ivosidenib for IDH1 Mutant Cholangiocarcinoma: A Narrative Review. Cureus. 2022 Jan 7;14(1):e21018
Javle M, Roychowdhury S, et al. Infigratinib (BGJ398) in previously treated patients with advanced or metastatic cholangiocarcinoma with FGFR2 fusions or rearrangements: mature results from a multicentre, open-label, single-arm, phase 2 study. Lancet Gastroenterol Hepatol. 2021 Oct;6(10):803-815.
https://www.fda.gov/drugs/resources-information-approved-drugs/fda-grants-accelerated-approval-infigratinib-metastatic-cholangiocarcinoma
Goyal L, Meric-Bernstam F, et al. Futibatinib for FGFR2-Rearranged Intrahepatic Cholangiocarcinoma. N Engl J Med. 2023 Jan 19;388(3):228-239. doi: 10.1056/NEJMoa2206834. PMID: 36652354.
https://www.fda.gov/drugs/resources-information-approved-drugs/fda-grants-accelerated-approval-futibatinib-cholangiocarcinoma
Tolcher AW, Papadopoulos KP, Patnaik A, et A phase I, first in human study of FP-1039 (GSK3052230), a novel FGF ligand trap, in patients with advanced solid tumors. Ann Oncol. 2016;27(3):526-532.
Touat M, Ileana E, et Targeting FGFR signaling in cancer. Clin Cancer Res. 2015;21(12):2684-2694.
https://meetings.asco.org/abstracts-presentations/204876
Immunohistochemistry (IHC) is based on antigen–antibody binding to directly visualize the status of markers of interest in tissues. IHC provides a huge amount of information and is now indispensable in many fields including pathology, cancer biology, and drug discovery.
IHC has been and continues to be analyzed by pathologists using microscopy. For pathologists in everyday practice or in the research context, IHC is an essential tool to interpret the pathophysiology of diseased tissues. Furthermore, IHC is also a crucial tool for biomarker discovery validation leading to personalized medicine. It provides information about the localization and the abundance of the target protein, both within tissue and at the sub-cellular level.
More recently, growing evidence of the importance of spatial information enclosed in the tissue for patient stratification leading to improved clinical outcomes further boosted the development and standardization of many different and improved image analysis methods.
This is particularly true in the field of immune-oncology and checkpoint inhibitors therapeutic development, where the presence of immune cells in the tumor correlated with positive clinical outcomes in many different types of cancer.
IHC results can be variable in both the percentage of positive detected cells as well as in protein expression intensity. The spatial distribution of the staining is also very variable. Sometimes the staining is widely spread out across the tissue while other times it is localized in small specific areas. The heterogeneity of the tissues reflected in the IHC staining needs to be classified, and more standardized scoring methods were needed to use this powerful tool in the clinic to stratify patients and improve outcomes.
In fact, to have a diagnostic and prognostic value, the biomarkers detected by IHC need to be quantified and expressed in numerical values. Different methods have been developed to quantify IHC biomarker staining for diagnostic and therapy design. So far, a universally accepted standardized unbiased method to quantify IHC does not exist. Instead, for each tumor type and correlated therapeutic regimen a specific method with a defined antibody and protocol has been developed.
The most common quantification methods are combinative semi-quantitative and percentage scoring methods.1
In the percentage scoring method, the relative immune-positive cell percentage in relation to the total number of cells is evaluated and reported using numbers from 0 to 9 where each unit increase represents 10% positive staining increments. For example, if the percentage of positive cells is between 0% and 9%, the score will be 0; if it is between 10% and 19%, the score will be 1; and so on. This method is preferable in large studies to avoid batch effects and can overcome interpretation errors in the evaluation of the positive cells. A limitation is that it does not include the staining intensity which in some cases could be important for patients’ stratification.2
Combinative semi-quantitative scoring is the most used method in the current prognostic biomarker research, providing a combined positive score incorporating both quantitative and qualitative assessments. In addition to the quantitative assessment of the relative immune-positive cell percentage described above, staining intensity is also assessed. Using the combinative semi-quantitative scoring method, the intensity is usually scored from 0 to 3 with 0 indicating negative staining, 1+ weakly positive staining, 2+ moderately positive, and 3+ strongly positive staining.2
Although IHC can be evaluated both quantitatively and qualitatively, an enormous number of variations is possible. This is due to the high number of diverse staining localization and spatial combinations. This leads to divergent interpretations among pathologists and discrepancies within pre-clinical and clinical studies evidencing the need for a more uniform system to interpret and quantify IHC data.
PD-L1 expression is estimated in different manners depending on the type of cancer. Interestingly, in different indications, the presence of PD-L1 is not alone indicative of therapeutic efficacy. Different clinical trials demonstrated that, for different tumor types, PD-L1 localization correlated with treatment efficacy if PD-L1 is expressed in only immune cells, only cancer cells, or both. Thus, the IHC’s ability to localize the staining is fundamental.3
As an example of IHC use in the clinic, evaluation of PD-L1 expression helps identifying metastatic NSCLC patients who are eligible for treatment with pembrolizumab. In fact, in NSCLC, PD-L1 is a proven biomarker for patient response to pembrolizumab.3,4
In general, PD-L1 staining by IHC is evaluated using a combined positive score (CPS) and tumor proportion score (TPS) depending on the cancer type. The CPS score is calculated by counting the PD-L1 positive tumor cells and mononuclear inflammatory cells, then dividing this number by the total tumor cells, and multiplying by 100.4 CPS is used in the clinic to identify candidates for treatment with pembrolizumab in indications such as gastric cancer.3
In advanced NSCLC,4 the TPS scoring method is preferred to evaluate PD-L1 expression. TPS is calculated as the number of PD-L1 positive tumor cells divided by the total number of tumor cells and then multiplied by 100.
Interestingly, to determine the eligibility of a patient for pembrolizumab treatment, only PD-L1 membrane staining is scored while staining intensity is not included in the score, and only the tumor cells and not the immune cells are evaluated. In this case, a competent, trained pathologist is critical to evaluate tumor heterogeneity and discriminate between tumor cells and infiltrating macrophages that are usually positive for PD-L1. For this PD-L1 staining scoring method to be reliable, at least 100 viable tumor cells must be evaluated within the patient’s tissue.2, 4
IHC has proven to be a powerful tool for oncology clinical practice. However, in order to fully leverage the information enclosed within the tissue in a clinical setting, and given the complexity of the IHC staining interpretation, crucial are both the pathologist’s training and expertise in the specific disease evaluation.
[1] Dabbs DJ. 2014. Diagnostic immunohistochemistry: theranostic and genomic applications. 4th ed. Philadelphia: Elsevier Saunders.
[2] Kim S, Roh J, Park C. 2016. Immunohistochemistry for Pathologists: Protocols, Pitfalls, and Tips, J Pathol Transl Med 50(6):411-418.
[4] Inamura K. 2018. Update on Immunohistochemistry for the Diagnosis of Lung Cancer, Cancers10(3), 72;
[3] Davis AA, Patel VG. 2019. The role of PD-L1 expression as a predictive biomarker: an analysis of all US Food and Drug Administration (FDA) approvals of immune checkpoint inhibitors, j. immunotherapy cancer 7, 278
.
Mouse models have been the workhorses of preclinical immuno-oncology (IO) research, and advances in mouse model development have expanded to applications for nearly all types of solid tumors and hematological malignancies. Preclinical evaluation of experimental immunotherapies has been advanced by syngeneic and humanized mouse models. Syngeneic mice are one of the most established types of models used in cancer research, whereas humanized mice are a contemporary mouse model that has been critical to the screening of immunotherapeutic agents. Here we highlight features of syngeneic and humanized mouse models and define which models are most relevant to different phases of preclinical IO research.
Syngeneic tumor models are created by transplantation of tumor cell lines into immunocompetent mice with the same genetic background as the cell line[1]. Tumors can be transplanted intravenously or subcutaneously into mice and typically grow rapidly over several weeks. Different types of tumor cell lines can be used in this type of model, including spontaneous, transgenic, or carcinogen-induced tumor cell lines. Syngeneic mouse models are best suited for screening novel IO agents or gaining insight into anti-tumor responses in the context of an intact immune system. Given the rapid growth of tumors in syngeneic mice, these models are less well suited to studying early events in tumor growth associated with cancer stem cells or understanding the contributions of heterogeneous tumor microenvironments, and these models typically do not recapitulate the mutational heterogeneity observed in human tumors[2].
Humanized tumor models are a more recent addition to preclinical IO research that provide valuable insight into how individual tumors from patients (xenografts) respond to experimental therapies. Prior to the development of humanized mouse models, human xenograft models were used for screening cytotoxic or immunotherapeutic agents like chimeric antigen receptor (CAR) T cells[3], and these models use human tumor cell lines or patient-derived specimens transplanted into immunocompromised host mice. Different immunocompromised models can be used, including athymic mice that lack T cells or severe combined immunodeficiency (SCID) models that lack all adaptive immune responses. Humanized mice have been engineered from immunocompromised mouse strains that include genetic mutations in other adaptive immune functions that allow for engraftment of human hematopoietic cells. The NOD/SCID IL2rγ chain knockout (NSG) mouse (NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ) is one of the most used combined immunodeficiency models that can be engrafted with human hematopoietic cells and primary human tumors[4]. These patient-derived xenograft (PDX) models are useful for evaluated experimental IO therapies in the context of the human immune system and can use human immune cells from the same or different donor as the tumor source. PDX models are suited to evaluating experimental therapies in the context of a genetically heterogeneous tumor and better recapitulates aspects of the tumor microenvironment. Tumors can be grafted either orthotopically or subcutaneously and this also impacts how tumors grow and respond to experimental treatments[5]. Given the heavily modified nature of the NSG immune system, these models do not always reflect responses observed in humans during clinical trials. Nonetheless, NSG mice and similarly modified humanized mice offer valuable insights into the efficacy of IO candidates.
Mouse models are constantly being refined and improved to better reflect human physiology. Both syngeneic and humanized mouse models serve as valuable tools to preclinical IO research and accelerate the screening and evaluation of novel therapeutics.
[1] Olson B, Li Y, Lin Y, Liu ET, Patnaik A. 2018. Mouse Models for Cancer Immunotherapy Research. Cancer Discov. 8(11):1358-1365.
[2] Hanahan D, Weinberg RA. 2011. Hallmarks of cancer: the next generation. Cell. 144:646–74.
[3] Siegler EL, Wang P. (2018). Preclinical models in chimeric antigen receptor–engineered T-cell therapy. Hum. Gene Ther., 29(5), 534-546.
[4] Okada S, Vaeteewoottacharn K, Kariya R. 2019. Application of Highly Immunocompromised Mice for the Establishment of Patient-Derived Xenograft (PDX) Models. Cells. 8(8):889.
[5] Byrne AT, Alférez DG, Amant F, Annibali D, Arribas J, Biankin AV, Bruna A, Budinská E, Caldas C, Chang DK, Clarke RB. 2017. Interrogating open issues in cancer precision medicine with patient-derived xenografts. Nature Reviews Cancer. 17(4):254.
DNA damage is one of the primary triggers of cancer development and has been linked to many types of cancers, including prostate, stomach, liver and skin cancers as well as leukemia. Within cells, the DNA sequence encodes all the instructions required for building proteins that are needed for cellular functions such as metabolism, replication, tissue and organ maintenance. The fidelity of the DNA sequence in a cell is maintained by multiple mechanisms but errors and mutations can occur, which sets off a chain of events that lead to tumor growth.
DNA damage can be caused by exogenous sources, such as UV radiation, chemical carcinogens, and infection with human papillomavirus or Helicobacter pylori. Endogenous DNA damage can also be caused by multiple factors, including unchecked metabolites like reactive oxygen species (ROS) and defects in DNA damage repair enzymes. Since DNA damage mechanisms have been known to cause numerous cancers, several drugs, particularly small molecule inhibitors, have been developed to target DNA repair pathways.
Improvements in animal models for cancer have revolutionized how anti-cancer drugs are evaluated and developed. Patient-derived xenograft (PDX) models have been particularly powerful tools since they use patient-derived tumor tissue engrafted into mice. Tumor cell lines, solid tumor tissue, or hematological tumors can be transplanted into immunodeficient mice. These immunocompromised mice can also be made to have “humanized” immune systems or express components of the human immune system, like immune checkpoint inhibitors, to better screen for the effectiveness of various anti-cancer treatments.
In this era of rapid, high-throughput DNA sequencing, individual tumors can be sequenced and specific defects in DNA damage repair pathways can be defined. This same tumor tissue can be engrafted into a PDX mouse model for screening of drugs or therapeutics that tackle the appropriate DNA damage repair defect. This approach is powerful for screening preclinical drug candidates for efficacy against a range of tumors and it also provides insights into potential off-target effects or toxicities. From the patient perspective, pre-screening potential treatment options in mice can lead to the selection of the most appropriate drug or therapeutic and helps avoid treatments that may be ineffective.
DNA damage events can lead to tumor growth and this area of research continues to inform drug development on the bench and patient care in the clinic.
Colorectal cancer (CRC) is a leading cause of cancer deaths globally. Advances in early detection have improved survival rates, but patients diagnosed with metastatic CRC still have stubbornly poor 5-year survival rates. Standard treatments for CRC include surgery, chemotherapy, and radiotherapy, but alternative immuno-oncology therapies are showing promising results in CRC patients. Here we highlight advances in immuno-oncology therapies that are being used to treat CRC patients or are being pursued in preclinical and clinical studies.
Molecular genetic analysis of CRC tumors is a critical diagnostic tool for classifying and treating this cancer. CRC tumors are typically classified as mismatch repair-deficient/microsatellite instability-high (dMMR—MSI-H) tumors, which have a high overall mutation burden, or mismatch repair-proficient/microsatellite instability-low (pMMR—MSI-L) tumors, which have a lower mutation burden[1]. Defects in MMR are associated with the accumulation of mutations and are caused by defects in mismatch repair proteins, and these defects are typically detected by frame-shift mutations in DNA repeat regions known as microsatellites. Mutations in the BRAF oncogene, particularly the activating V600E mutation, comprise a distinct subset of CRC. BRAF is a component of the mitogen activated protein kinase (MAPK) pathway that normally functions downstream of the epidermal growth factor receptor to regulate transcription of genes involved in cellular growth and survival, but the BRAF-V600E mutation results in constitutive activation of BRAF and uncontrolled cellular proliferation and tumor growth[2].
Immuno-oncology approaches that target immune checkpoint blockade have proven effective for several cancers, including CRC. T cells can initiate effective anti-tumor responses under ideal conditions, but the immunosuppressive tumor microenvironment of some cancer types inhibits T cell activation, usually through engagement of immune checkpoint molecules like PD-1 and CTLA4. For more than a decade, the development and use of immune checkpoint inhibitors (ICIs) has transformed treatment of melanoma[3,4] and non-small cell lung cancer[5,6]. The first FDA-approved treatments include a monoclonal antibody (mAb) that targets CTLA4 (ipilimumab) and two mAbs that target PD-1 (pembrolizumab and nivolumab). These early studies suggested that tumors with high mutation burdens respond well to ICI, which may be due in part to the generation and presentation of tumor neoantigens that are recognized as non-self and can be targeted by cytotoxic T cells[7].
CRC tumors with the dMMR—MSI-H signature have a high mutational burden and typically have a high level CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs). These cells have shown elevated expression of PD-1, PD-L1 and CTLA4, which suggests that they may respond well to ICIs[8]. Indeed, several recent clinical studies have shown improvements with overall survival and progression-free survival in patients treated with individual or combined ICIs that target PD-1. Of note, interim results from a phase II trial that enrolls patients with MMRd locally advanced rectal cancer to receive neoadjuvant dostarlimab, a PD-1 inhibitor, showed sustained complete response 1 year after the end of treatment in all patients[9]. Other current studies are evaluating next-generation PD-1 inhibitors combined with chemotherapy and/or other biologics such as an anti-VEGF and anti-EGFR mAb[10].
In contrast, patients with pMMR–MSI-L have shown poor responses to PD-1 or CTLA4 blockade alone or in combination, which has led to the development of trials that explore different treatment combinations, including inhibitors of the MAPK pathway or angiogenesis[11]. Promising results have been presented in a phase I/II clinical trial (NCT04017650) in which patients with MSI-L and BRAFV600E were treated with BRAF+EGFR inhibitors, to induce a transient MSI-H phenotype, plus anti-PD-1 antibody[12].
Several cutting-edge immuno-oncology therapies are being explored for the treatment of CRC. Beyond combinations of individual antibodies, researchers are engineering bispecific antibodies that bind to tumor cells and T cells simultaneously to enhance anti-tumor T cell responses. One such bispecific antibody, CEA-TCB, is being tested in phase I trials alone or in combination with anti-PD-L1 to treat metastatic CRC[13]. Another novel approach includes adoptive cell therapies like chimeric antigen receptor (CAR) T cells, which are T cells collected from the tumor tissue or peripheral blood of a patient and engineered to bind to tumor antigens and potentiate anti-tumor responses. Oncolytic virus and bacteria-based vaccines are also being studied as potential CRC treatments.
Besides treatments designed on the tumor intrinsic genetic background, a lot of effort is being put to decipher tumor microenvironment, with particular focus on its interplay with the gut microbiota to modulate inflammation and immune response, known to be involved in the metastatic onset. These studies are leading to the identification of inflammatory/immune signatures that inform the therapeutic agents to be used to target the pro-oncogenic microenvironment and reactivate the immune system[14].
The advancement of immuno-oncology is already transforming the treatment of CRC and will contribute to better outcomes for all types of CRC in the decades to come.
1. Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487(7407):330-337.
2. Bond CE, Whitehall VLJ. How the BRAF V600E mutation defines a distinct subgroup of colorectal cancer: molecular and clinical implications. Gastroenterol Res Pract. 2018; 2018:9250757.
3. Hodi FS, O'Day SJ, McDermott DF, et al. Improved survival with ipilimumab in patients with metastatic melanoma [published correction appears in N Engl J Med. 2010 Sep 23;363(13):1290]. N Engl J Med. 2010;363(8):711-723.
4. Robert C, Long GV, Brady B, Dutriaux C, et al. Nivolumab in previously untreated melanoma without BRAF mutation. N Engl J Med. 2015 Jan 22;372(4):320-30.
5. Garon EB, et al. Pembrolizumab for the treatment of non-small-cell lung cancer. N. Engl. J. Med. 2015; 372:2018–2028.
6. Brahmer J, et al. Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer. N. Engl. J. Med. 2015; 373:123–135.
7. Rizvi NA, et al. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science. 2015; 348: 124-128.
8. Llosa NJ, et al. The vigorous immune microenvironment of microsatellite instable colon cancer is balanced by multiple counter-inhibitory checkpoints. Cancer Discovery. 2015; 43-51.
9. Cercek A, Lumish M, Sinopoli J, Weiss J, et al. PD-1 Blockade in Mismatch Repair-Deficient, Locally Advanced Rectal Cancer. N Engl J Med. 2022 Jun 23;386(25):2363-2376.
10. Ciardiello D, Vitiello PP, Cardone C, Martini G, et al. Immunotherapy of colorectal cancer: Challenges for therapeutic efficacy. Cancer Treat Rev. 2019 Jun;76:22-32.
11. Golshani G, Zhang Y. Advances in immunotherapy for colorectal cancer: a review. Therap Adv Gastroenterol. 2020; 13:1756284820917527.
12. Van K. Morris, Christine Megerdichian Parseghian, Michelle Escano, Benny Johnson, et al. Phase I/II trial of encorafenib, cetuximab, and nivolumab in patients with microsatellite stable, BRAFV600E metastatic colorectal cancer. Journal of Clinical Oncology 2022 40:4_suppl, 12-12.
13. Segal NH, et al. Phase I studies of the novel carcinoembryonic antigen T-cell bispecific (CEA-CD3 TCB) antibody as a single agent and in combination with atezolizumab: Preliminary efficacy and safety in patients (pts) with metastatic colorectal cancer (mCRC). Annals of Oncology. 2017; 28.suppl5.
14. Hou X, Zheng Z, Wei J, Zhao L. Effects of gut microbiota on immune responses and immunotherapy in colorectal cancer. Front Immunol. 2022 Nov 8;13:1030745.
Western blotting is a decades-old laboratory technique that is used to detect specific proteins from cell culture, tissue, or blood specimen. The term “western blot” is a twist on the Southern blotting method developed by Edwin Southern, which is used to detect DNA and shares methodological similarities with western blotting. The western blot method was first described by Harry Towbin in 1979 but the term “western blot” was coined by W. Neal Burnette in 1981[1],[2]. Since its initial description, western blotting has been used in all fields of biological and biomedical research because it is a straightforward and robust method for detecting specific proteins. Here we provide an overview of the western blot method and highlight its current applications in preclinical oncology research.
Western Blot Basics
The western blot technique can be used to separate and identify a specific protein using three major steps: 1. Size separation using gel electrophoresis, 2. Transfer to a solid membrane, and 3. Detection with a specific antibody. Most western blot methods begin with a lysate of cells or tissue, which releases a mix of proteins that are separated by molecular weight using gel electrophoresis. Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) is the most common type of gel electrophoresis for western blotting and includes a protein denaturation step prior to gel electrophoresis such that proteins are separated by molecular weight. The SDS buffer causes proteins to become negatively charged so electrophoresis allows for migration of proteins from smallest to largest weight towards a positive charge. After gel electrophoresis, proteins are transferred to a solid membrane, usually polyvinylidene difluoride or nitrocellulose, using electroblotting or a slower alternative method based on capillary action. This membrane can now be probed with a primary antibody specific to a protein of interest and the primary antibody is visualized using a secondary antibody that recognizes a species-specific region of the primary antibody and is conjugated with a chemiluminescence substrate for visualization. Other less common visualization methods use colorimetric substrates or radioactive labels on secondary antibodies.
Western Blot and Preclinical Studies
Why is western blotting a method that is still used after more than forty years since its development? Western blotting remains a reliable, affordable, and practical method for detecting specific proteins. In preclinical oncology research, western blotting is used to validate high throughput single-cell RNA sequencing or proteomics methods that detect elevated proteins associated with specific cancers[3]. Western blotting can also validate tissue microarray and immunohistochemistry findings with respect to specific proteins that are overexpressed in tumor tissue. Together these data can be used toward developing prognostic biomarkers for cancers, such as measuring overexpression of Kin of IRRE-like Protein 1 (KIRREL) in breast cancer and precancerous tissue[4]. Western blotting is also a useful tool for understanding molecular mechanisms that drive cancer progression by measuring expression of critical proteins such as HMGB1, cyclins, and various oncogenes[5],[6].
Western blot has made a leap into the twenty-first century with advancements in process workflow and sensitivity using new platforms like ProteinSimple’s JESS System. Western blot will continue to be a workhorse for detecting and monitoring specific protein expression and continues to have broad applications in preclinical and clinical oncology studies related to understanding oncogenesis and defining potential tumor biomarkers.
[1] Towbin H, Staehelin T, Gordon J. Electrophoretic transfer of proteins from polyacrylamide gels to nitrocellulose sheets: procedure and some applications. Proc. Natl. Acad. Sci. USA. 1979 Sep;76(9):4350-4.
[2] Burnette WN. "Western blotting": electrophoretic transfer of proteins from sodium dodecyl sulfate--polyacrylamide gels to unmodified nitrocellulose and radiographic detection with antibody and radioiodinated protein A. Anal. Biochem. 1981 Apr;112(2):195-203.
[3] Meftahi GH, Bahari Z, Zarei Mahmoudabadi A, Iman M, Jangravi Z. Applications of western blot technique: From bench to bedside. Biochem. Mol. Biol. Educ. 2021 Jul;49(4):509-517.
[4] Chen K, Zhao R, Yao G, Liu Z, Shi R, Geng J. Overexpression of kin of IRRE-Like protein 1 (KIRREL) as a prognostic biomarker for breast cancer. Pathol. Res. Pract. 2020 Jul;216(7):153000.
[5] Yang G, Xu Q, Wan Y, Zhang L, Wang L, Meng F. Circ-CSPP1 knockdown suppresses hepatocellular carcinoma progression through miR-493-5p releasing-mediated HMGB1 downregulation. Cell Signal. 2021 Oct;86:110065. doi: 10.1016/j.cellsig.2021.110065.
[6] Hou Y, Ding M, Wang C, Yang X, Ye T, Yu H. TRIM11 promotes lymphomas by activating the β-catenin signaling and Axin1 ubiquitination degradation. Exp. Cell Res. 2020 Feb 15;387(2):111750.
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In vivo models for numerous diseases and conditions have endpoints that have involved animals being gravely ill or dying. As researchers have sought to utilize animal models in more humane and practical ways, surrogate endpoints have been developed that prevent animals from suffering and provide critical research data. Flow cytometry has been instrumental to these advances. Consider these aspects of preclinical flow cytometry endpoint analysis as you develop new protocols.
Flow cytometry provides the most useful data when the cell subsets of interest are well-defined and robust. You may need to analyze existing research literature or do pilot studies to define the immune cell subsets of interest for a particular disease state, be it changes in regulatory T cells in the tumor microenvironment, or the proliferation of plasmablasts in different leukemias. You must identify which profound changes in different cell populations are most closely correlated with morbidity and mortality in your animal model.
Preclinical studies with surrogate endpoints are valuable for screening potential therapeutic candidates. These drugs or biologics may have undesirable off target effects as well. In designing a flow cytometry assay for alternative endpoints, it is critical to identify the changes in immune cell subsets that reflect therapeutic improvements or indicate potential toxicity or off target effects.
Flow cytometry endpoint analysis not only advances the humane use of animal models but can be translated into informative clinical protocols that are critical for the evaluation of potential therapies.
Next-generation sequencing (NGS) technology has transformed the biomedical research landscape. Only a few years ago, high resolution genome or exome sequencing would be cumbersome and cost-restrictive, but current NGS technology platforms now allow for basic and clinical researchers to include these approaches for routine DNA and RNA sequencing needs. What are the different NGS sequencing approaches and how are they applied to oncology research?
1. Whole Genome Sequencing (WGS): NGS technology can be used for WGS of human genomes and tumor-specific genomes, as well as animal model and microbial genomes. WGS produces high resolution genomic sequences of expressed genomic regions as well as unexpressed regulatory regions. For preclinical oncology research, WGS is critical for characterizing genomic profiles associated with tumor progression or potential responsiveness to targeted drug therapies. WGS can detect single nucleotide variants, copy number variants, and insertions/deletions in tumor cells[1]. The comprehensive scope of WGS makes it well suited for detecting mutations in both coding and non-coding regions[2]. WGS is also useful for population level oncology studies that evaluate genetic susceptibility to specific cancers and potential heritability[3].
2. Whole Exome Sequencing (WES): WES techniques focus on sequencing the exome, which are comprised of protein expressing regions, or exons, within the genome. WES is an appropriate method for identifying genetic mutations that alter protein sequences, and WES data can be used toward measuring the tumor mutational burden (TMB) and predicting treatment efficacy[4]. WES data can also be used to identify potential new drug targets or mechanisms of drug resistance[5].
3. Targeted Sequencing: This method focuses on defined gene regions and is typically used in diagnostic applications or for validation of WGS or WES results. Targeted sequencing works well for screening tumor samples for well characterized mutations, such as those associated with BCL2, BRCA-1/2, BRAF, and EGFR, and can be used for identifying appropriate targeted therapies[6].
4. RNA sequencing: RNA sequencing is now emerging as a powerful tool that complements NGS DNA methods because the transcriptional profile of a single cell can be measured and used to bridge genomic data with cellular phenotypes. Single-cell RNA sequencing (scRNA-seq) has specifically emerged as a powerful method for understanding the heterogeneity of cell populations within a tumor. Together with histological data, scRNA-seq data can be used to distinguish between neoplastic cells, immune cells, and healthy cells from the surrounding tissue, and it can also be used to evaluate how experimental treatments alter the tumor microenvironment[7].
NGS methods are transforming both basic oncology research and clinical care, from identifying novel mutations to pinpointing personalized cancer therapies. Each method is suited to specific applications, so working with experts in NGS technology is critical to method selection and data analysis.
1 Bewicke-Copley F et al. Applications and Analysis of Targeted Genomic Sequencing in Cancer Studies. Comput. Struct. Biotechnol. 2019;17: 1348-1359.
2 Nakagawa H, Fujita M. Whole Genome Sequencing Analysis for Cancer Genomics and Precision Medicine. Cancer Sci. 2018;109(3):513-522.
3 Rotunno M et al. A Systematic Literature Review of Whole Exome and Genome Sequencing Population Studies of Genetic Susceptibility to Cancer. Cancer Epidemiology and Prevention Biomarkers. 2020;29(8):1519-34.
4 Klempner SJ et al. Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence. Oncologist. 2020 Jan;25(1): e147-e159.
5 Beltran H et al. Whole-Exome Sequencing of Metastatic Cancer and Biomarkers of Treatment Response. JAMA Oncol. 2015;1(4):466-474.
6 Vestergaard LK et al. Next Generation Sequencing Technology in the Clinic and Its Challenges. Cancers (Basel). 2021;13(8):1751.
7 Fan J et al. Single-Cell Transcriptomics in Cancer: Computational Challenges and Opportunities. Exp Mol Med. 2020; (52)1452–1465.
Importance of the Dataset
Sarcoma is a malignant tumor of the mesenchymal cells forming the connective tissue. Champions Oncology currently has 135 Sarcoma PDX models available to oncology pharmacology studies and drug development. Champions’ Sarcoma models represent several disease subtypes, both pediatric and adult, including Ewing Sarcoma, Leiomyosarcoma, Liposarcoma, Angiosarcoma, Synovial Sarcoma, and others. These models are well characterized with patient clinical annotations, disease status, treatment history, and in vivo and ex vivo drug responses to standard of care therapies, such as cisplatin, doxorubicin, docetaxel, ifosfamide, and many more. Champions’ Sarcoma model cohort encompass mutations in numerous key pathways including DNA repair, cell cycle, cell proliferation and invasion, and angiogenesis.
Experimental Design
Each model included in this cohort was characterized by NGS sequencing (WES and RNA-Seq), proteomics and phospho-proteomics analyses. Our NGS workflow is a multi-step procedure; specifically, a primary sample undergoes preparation by thawing and subsequent extraction of gDNA and RNA. A library is then prepared and NGS sequencing (WES and RNA-Seq) is performed using Illumina Nextseq2000. Subsequently, raw data is collected, processed, and analyzed. The data must meet Champions’ Quality Control requirements, including sample QC, library QC and sequencing data QC. Finally, data is uploaded and stored in the user’s unique Lumin instance, where it can be visualized and further analyzed in various modules.
Champions has partnered with BGI Genomics to obtain proteomics and phospho-proteomics data; specifically, proteins are extracted from cells and/or tissues to obtain a protein mixture, which are broken down by digestion enzymes to yield a peptide mixture. This peptide mixture undergoes phospho-peptide enrichment to give a phospho-peptide mixture, which is then analyzed by LC/MS, using either data-dependent acquisition (DDA) or label-free data-independent acquisition (DIA) for data quantification.
Applications of the Dataset
The Sarcoma model cohort dataset has been integrated into our revolutionary visualization and data analytics software, Lumin Bioinformatics. With a Lumin Bioinformatics or Workspaces subscription, you can access multi-omic data from our Sarcoma model cohort.
The following modules can be used in Lumin Bioinformatics to access proteomics and phospho-proteomics data:
Watch our quick video to discover more about Champions’ Sarcoma Models in Lumin Bioinformatics:
Renal cell carcinoma (RCC) is a common cancer of the genitourinary tract that has very poor survival outcomes if metastatic. RCC is now understood to be composed of several different types of cancer with different genetic features and varied clinical responses. Histological diagnosis has been the primary method to diagnose RCC and has been used to define three major RCC subtypes, including the most common subtype, clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (PRCC; further divided into two subtypes), and chromophobe renal cell carcinoma (ChRCC)[1]. More recent comparative genomic and phenotypic analysis has identified mutations and epigenetic modifications associated with different histological subtypes[2]. Across all subtypes, increased DNA hypermethylation and gene alterations in CDKN2A were associated with a poor prognosis as was an increased Th2 immune gene signature. For ccRCC, increased levels of mRNA transcripts associated with ribose metabolism and the immune response were associated with poor survival. ccRCC is also defined by the early loss of chromosome 3p, which in turn causes a loss of heterozygosity for the VHL, PBRM1, SETD2, and BAP1 tumor suppressor genes and subsequent mutation of these genes that leads to tumorigenesis[3]. There is also a subset of ChRCC with a unique metabolic expression pattern that is associated with extremely poor survival2. PRCC can be classified as type 1, for which PBRM1 mutations are linked to poor survival but type 2 PRCC has increased expression of glycolysis and metabolism related mRNA transcripts2.
ccRCC tumors with VHL mutations show overexpression of vascular endothelial growth
factor (VEGF) and hypoxia-inducible factors (HIFs), which can contribute to angiogenesis and cancer progression. Similarly, some RCC show hyperactivation of the serine/threonine kinase mammalian target of rapamycin (mTOR), which can lead to overproduction of VEGF. VEGFR inhibitors and anti-VEGF antibodies have been tested as therapies for RCC, and the anti-VEGF antibody bevacizumab has been approved for use in combination with IFN-α for metastatic RCC[4]. The mTOR inhibitors everolimus and temsirolimus have also been approved for the treatment of RCC, typically in combination with tyrosine kinase inhibitors (TKIs)[5]. Combination therapies that target VEGF and mTOR are considered more effective since they work in concert to target tumor growth and vascularization, whereas sequential treatments are typically associated with a greater likelihood of tumors developing resistance[6]. Unfortunately, these combination therapies are associated with undesirable toxicities and have not been linked with durable responses[7].
Advances in immunotherapy have led to transformative treatment options for RCC. Immune checkpoint blockade (ICB) has been one promising treatment strategy, and the FDA approved the use of anti-PD-1/PD-L1 (nivolumab) for the treatment of advanced ccRCC in 2015[8]. A follow up study showed that anti-PD-1 was associated with the best clinical benefit in ccRCC carrying loss-of-function mutations in PBRM1, which appears to affect tumor expression profiles in such a way to maintain responsiveness to checkpoint blockade[9]. Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) is another checkpoint molecule that has been targeted for checkpoint blockade with the monoclonal antibody ipilimumab. Similar to PD-L1 blockade, CTLA-4 blockade was associated with a partial response against metastatic RCC. Combination therapies have shown much more durable responses in patients with advanced RCC, and the FDA approved the use of nivolumab plus ipilimumab for the treatment of intermediate or high risk metastatic RCC in 2018[10]. ICB blockade in combination with TKI are also under investigation as alternative first or second line treatments. Unfortunately, PD-1/PD-L1 blockade has been less successful for PRCC[11] and ChRCC[12], and further studies are needed to identify therapeutic targets in these forms of RCC. Clinical studies with other checkpoint blockade targets are currently underway and are likely to provide new treatment options to RCC patients[13].
The future of RCC therapies relies on the identification of new molecules or pathways in tumor cells that can be targeted therapeutically without causing toxicity or promoting resistance. Advances in single-cell omics are leading the way in terms of target identification and understanding how different forms of RCC progress.
[1] Hsieh JJ, Purdue MP, Signoretti S, Swanton C, Albiges L, Schmidinger M, Heng DY, Larkin J, Ficarra V. Renal cell carcinoma. Nat Rev Dis Primers. 2017;3:17009.
[2] Ricketts CJ, De Cubas AA, Fan H, et al. The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma [published correction appears in Cell Rep. 2018 Jun 19;23(12):3698]. Cell Rep. 2018;23(1):313-326.e5.
[3] Turajlic S, Swanton C, Boshoff C. Kidney cancer: The next decade. J Exp Med. 2018;215(10):2477-2479. doi:10.1084/jem.20181617
[4]Rini BI, Halabi S, Rosenberg JE, et al. Phase III trial of bevacizumab plus interferon alfa versus interferon alfa monotherapy in patients with metastatic renal cell carcinoma: final results of CALGB 90206. J Clin Oncol. 2010;28(13):2137-2143.
[5] Leonetti A, Leonardi F, Bersanelli M, Buti S. Clinical use of lenvatinib in combination with everolimus for the treatment of advanced renal cell carcinoma. Ther Clin Risk Manag. 2017 Jun 30;13:799-806.
[6] Gore ME, Larkin JM. Challenges and opportunities for converting renal cell carcinoma into a chronic disease with targeted therapies. Br J Cancer. 2011 Feb 1;104(3):399-406.
[7] Escudier B: Emerging immunotherapies for renal cell carcinoma. Ann Oncol 23:viii35-viii40, 2012 (suppl 8).
[8] Motzer RJ, Escudier B, McDermott DF, et al. Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma. N Engl J Med. 2015;373(19):1803-1813.
[9] Miao D, Margolis CA, Gao W, Voss MH, Li W, Martini DJ, Norton C, Bossé D, Wankowicz SM, Cullen D, Horak C, Wind-Rotolo M, Tracy A, Giannakis M, Hodi FS, Drake CG, Ball MW, Allaf ME, Snyder A, Hellmann MD, Ho T, Motzer RJ, Signoretti S, Kaelin WG Jr, Choueiri TK, Van Allen EM. Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma. Science. 2018 Feb 16;359(6377):801-806.
[10] Hammers HJ, Plimack ER, Infante JR, Rini BI, McDermott DF, Lewis LD, Voss MH, Sharma P, Pal SK, Razak ARA, Kollmannsberger C, Heng DYC, Spratlin J, McHenry MB, Amin A. Safety and Efficacy of Nivolumab in Combination With Ipilimumab in Metastatic Renal Cell Carcinoma: The CheckMate 016 Study. J Clin Oncol. 2017 Dec 1;35(34):3851-3858.
[11] de Vries-Brilland, Manon, et al. Are immune checkpoint inhibitors a valid option for papillary renal cell carcinoma? A multicentre retrospective study. European Journal of Cancer 2020; 136:76-83.
[12] Schwartzman, William, et al. "Safety and efficacy of immune checkpoint inhibitors (ICI) in metastatic non-clear cell renal cell carcinoma (nccRCC): An institutional experience." J. Clin Oncol. 2020: 640.
[13] Mollica V, Di Nunno V, Gatto L, Santoni M, Cimadamore A, Cheng L, Lopez-Beltran A, Montironi R, Pisconti S, Battelli N, Massari F. Novel Therapeutic Approaches and Targets Currently Under Evaluation for Renal Cell Carcinoma: Waiting for the Revolution. Clin Drug Investig. 2019 Jun;39(6):503-519.
