Trends in Oncology

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.

Sarcoma TME and Immune Checkpoint Blockade

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 survival^3,4. 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 survival^5,6.

Targeted Therapies

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 endpoints^7,8. 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.

Cellular Immunotherapy

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.

[9] https://twin-cities.umn.edu/news-events/university-minnesota-opens-first-its-kind-clinical-trial-treat-metastatic-gi-cancers

[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.

1. 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.
2. Free receptor assay: In this assay, cells are first stained with an unlabeled therapeutic antibody and then stained with a labeled version of the same antibody, which will only bind to the remaining free receptors. Measurement of free receptor levels at different doses is required for generating PK/PD datasets.
3. Drug-occupied receptor assay: This assay labels cells with your antibody of interest (“drug”), and then a labeled secondary antibody binds to a different site on your antibody of interest. This measurement can be used in place of free receptor assays when they are not technically feasible.

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.

1. Shah NN, et al. Mechanisms of resistance to CAR T cell therapy. Nat Rev Clin Oncol. 2019 Jun;16(6):372-385. doi: 10.1038/s41571-019-0184-6. PMID: 30837712; PMCID: PMC8214555.
2. Sterner RC, et al. CAR-T cell therapy: current limitations and potential strategies. Blood Cancer J. 2021 Apr 6;11(4):69. doi: 10.1038/s41408-021-00459-7. PMID: 33824268; PMCID: PMC8024391.
3. Plaks V, et al. CD19 target evasion as a mechanism of relapse in large B-cell lymphoma treated with axicabtagene ciloleucel. Blood. 2021 Sep 23;138(12):1081-1085. doi: 10.1182/blood.2021010930. PMID: 34041526; PMCID: PMC8462361.
4. Sworder BJ, et al. Determinants of resistance to engineered T cell therapies targeting CD19 in large B cell lymphomas. Cancer Cell. 2023 Jan 9;41(1):210-225.e5. doi: 10.1016/j.ccell.2022.12.005. Epub 2022 Dec 29. PMID: 36584673; PMCID: PMC10010070.
5. Frey NV, et al. Optimizing Chimeric Antigen Receptor T-Cell Therapy for Adults With Acute Lymphoblastic Leukemia. J Clin Oncol. 2020 Feb 10;38(5):415-422. doi: 10.1200/JCO.19.01892. Epub 2019 Dec 9. PMID: 31815579; PMCID: PMC8312030.
6. Chen GM, et al. Characterization of Leukemic Resistance to CD19-Targeted CAR T-cell Therapy through Deep Genomic Sequencing. Cancer Immunol Res. 2023 Jan 3;11(1):13-19. doi: 10.1158/2326-6066.CIR-22-0095. PMID: 36255409; PMCID: PMC9808313.
7. Atilla PA, et al. Resistance against anti-CD19 and anti-BCMA CAR T cells: Recent advances and coping strategies. Transl Oncol. 2022 Aug;22:101459. doi: 10.1016/j.tranon.2022.101459. Epub 2022 May 23. PMID: 35617812; PMCID: PMC9136177.

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.

Teasing Apart the Tumor Microenvironment

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].

Elevating Liquid Biopsies

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.

Better Biomarkers

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.

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.