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 leukemogenesis^3,4. 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.
       

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1. Pratcorona M, Abbas S, Sanders MA, et al. Acquired mutations in ASXL1 in acute myeloid leukemia: prevalence and prognostic value. Haematologica. 2012;97(3):388-392.
2. Abdel-Wahab O, Adli M, LaFave LM, et al. ASXL1 mutations promote myeloid transformation through loss of PRC2-mediated gene repression. Cancer Cell. 2012;22(2):180-193.
3. Balasubramani A, Larjo A, Bassein JA, et al. Cancer-associated ASXL1 mutations may act as gain-of-function mutations of the ASXL1-BAP1 complex. Nat Commun. 2015;6:7307.
4. Asada S, Goyama S, Inoue D, et al. Mutant ASXL1 cooperates with BAP1 to promote myeloid leukaemogenesis. Nat Commun. 2018;9(1):2733
5. Guo Y, Yang H, Chen S, et al. Reduced BAP1 activity prevents ASXL1 truncation-driven myeloid malignancy in vivo. Leukemia. 2018;32(8):1834-1837.
6.  Jadhav SP, Kumari N, Ng L, et al. circASXL1-1 regulates BAP1 deubiquitinase activity in leukemia. Haematologica, 2020; 105 (7): e343 DOI: 10.3324/haematol.2019.225961.

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.

 

 

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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.

 

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:

1. Wanted Alive, Not Dead: The development of plate-based TIL assays offers users flexibility and scalability, but it is critical to assess the viability of cultured TILs at the outset of any of these assays. Some TIL cultures are prone to high levels of cell death over time, and culture conditions may need to be optimized to include different cytokines and growth factors to promote viability as well as growth and expansion of tumor-specific T cells.
   
   
2.  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.
   
   
3. TIL Test Drive: Ex vivo expansion of TILs must include functional assays in order to ascertain if these cells have anti-tumor properties. Analysis typically includes flow cytometry-based immunophenotyping and characterization of cytokine production and tumor-specific cytotoxicity. An ideal TIL product will show tumor-specific activity with limited off-target effects, and TILs will retain a phenotype that is predicted to be well-tolerated in a patient upon re-infusion.

 

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.

 

 

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[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.

Current CCA classification and clinical care

 

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].

 

CCA molecular classification

 

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].

 

 New CCA precision therapies

 

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.

 

 

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1. Razumilava N, Gores Cholangiocarcinoma. Lancet. 2014;383(9935):2168- 79.

2. 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.

3. Hirschfield GM, Karlsen TH, et Primary sclerosing cholangitis. Lancet. 2013;382(9904):1587-99.

4. Yazici C, Niemeyer DJ, et al. Hepatocellular carcinoma and cholangiocarcinoma: an Expert Rev Gastroenterol Hepatol. 2014;8(1):63-82.

5. Jusakul A, Cutcutache I, et al. Whole‐genome and epigenomic landscapes of etiologically distinct subtypes of cholangiocarcinoma. Cancer Discov 2017;7:1116‐1135

6. 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.

7. Churi CR, Shroff R, et Mutation profiling in cholangiocarcinoma: prognostic and therapeutic implications. PLoS One. 2014;9:e115383.

8. Graham RP, Barr Fritcher EG, et al. Fibroblast growth factor receptor 2 translocations in intrahepatic Hum Pathol. 2014;45(8):1630- 1638.

9. 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.

10. 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

11. 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.

12. 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.

13. Sumbly V, Landry I, Rizzo V. Ivosidenib for IDH1 Mutant Cholangiocarcinoma: A Narrative Review. Cureus. 2022 Jan 7;14(1):e21018

14. 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.

15. https://www.fda.gov/drugs/resources-information-approved-drugs/fda-grants-accelerated-approval-infigratinib-metastatic-cholangiocarcinoma

16. 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.

17. https://www.fda.gov/drugs/resources-information-approved-drugs/fda-grants-accelerated-approval-futibatinib-cholangiocarcinoma

18. 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.

19. Touat M, Ileana E, et Targeting FGFR signaling in cancer. Clin Cancer Res. 2015;21(12):2684-2694.

20. 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 Analysis and Scoring Methods

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.

 

 

Testing for PD-L1 in metastatic NSCLC

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.

 

 

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[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

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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, including the DNA damage repair mechanism, but errors and mutations can occur, which sets off a chain of events that leads 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 damage repair pathways.

Improvements in animal models for cancer have revolutionized how anti-cancer drugs are evaluated and developed, including drugs targeting DNA damage. 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 to study DNA damage repair mechanisms. These immunocompromised mice can also be humanized by inoculating human immune cells or made to express components of the human immune system, like immune checkpoint molecules, 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.

Different assays can also be used to study DNA damage and repair mechanisms:

• comet assay is used to detect DNA single/double-strand breaks in single cells,
• γH2AX detection by IHC staining or western blot can be used to detect, measure, and localize DNA breaks.

This approach is powerful for screening preclinical drug candidates targeting DNA damage and repair for efficacy against a range of tumors and it also provides insights into potential off-target effects or toxicities. From the patient's perspective, pre-screening potential treatment options in mice can lead to the selection of the most appropriate drug or therapeutic targeting DNA damage and repair and help 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.

Champions Oncology is the ideal partner to accelerate your DNA damage-targeted drug pipeline. We offer a large bank of PDX models, particularly PDX models with high microsatellite instability (MSI-H), that have dysregulated DNA damage repair mechanisms, for ex vivo and in vivo studies. We also provide DNA sequencing, comet assay, and γH2AX detection by IHC staining or western blot, to support your DNA damage targeting drug programs. To add DNA damage evaluation to your upcoming study, contact us today.

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, the application of western blotting to all fields of biological and biomedical research has been broad because it is a straightforward and robust method for detecting specific proteins. Here we provide an overview of the western blot method and highlight the current application of western blotting 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.

 

Application of Western Blotting to 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. The application of western blotting in preclinical oncology research allows 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 the application of western blotting continues to be broad in preclinical and clinical oncology studies related to understanding oncogenesis and defining potential tumor biomarkers.

 

 

 

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.

 

1. What are the immune system features of your disease state? 

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.

2. What is the desired treatment outcome?

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.

3. Can this be translated into a clinical flow cytometry protocol?

In some disease models, particularly models using humanized mice, flow cytometry endpoints can be used in both preclinical screens and to evaluate clinical trial specimens. This consideration is valuable as protocols are developed and cell phenotypes are identified as predictors of good or poor prognoses.

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.

 

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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.