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Trends in Oncology

Ex Vivo Hematologic Oncology Models improve therapeutic agent screening.

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 hematologic oncology 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 drug screening 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, ex vivo hematologic oncology models closely recapitulate the tumor of origin and can provide valuable information about the variability of drug response in a cohort of patients.

Top 3 Considerations for Using Ex Vivo Hematologic Models

5/25/23 10:22 AM / by Champions Oncology posted in Ex Vivo Platforms

Ex vivo Systems

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 hematologic oncology 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 drug screening 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, ex vivo hematologic oncology models 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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  1. Viability, Survival, and Proliferation: Patient-derived ex vivo hematologic oncology models may adapt to culture conditions very differently; some cells may die off significantly whereas others proliferate at high rates. It is critical to measure and understand the proliferation and viability parameters of your ex vivo hematologic oncology models to assure you are working with a reliable specimen.

  2. Consider Specific Cell Characteristics: Prolonged culturing of ex vivo hematologic oncology models may introduce unwanted changes to cells that can alter their responses to drugs or antibodies. Be sure to thoroughly characterize the phenotype of specific ex vivo hematologic oncology models before and during ex vivo culture to assure that prolonged culture does not significantly alter the cell phenotype or cause unintended mutations. Short term cultures reduce the risk of such changes happening.

  3. The Power of the Panel: A major advantage of using ex vivo hematologic oncology models is the ability to scale up cultures and screen large panels of experimental antibodies or drugs. This can also be done with multiple patient-derived ex vivo hematologic oncology models being screened in parallel.

Ex vivo hematologic oncology models have advanced significantly as ex vivo drug screening platforms have emerged. With our expertise and our large bank of ex vivo hematologic oncology models, at Champions Oncology, we are well poised to help you advance your preclinical therapeutic screening. Leveraging the multi-omics and multimodal characterization of our ex vivo hematologic oncology models will help you narrow down your drug candidates and speed up the trajectory to clinical investigation.

Learn more about Champions' Hematological VitroScreen

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The Dos & Don’ts of Flow Cytometry in the Clinic

5/18/23 3:15 PM / by Champions Oncology posted in Clinical Flow Cytometry

Scientist at computer

Clinical flow cytometry is now a standard tool used by clinical researchers in numerous fields, especially immuno-oncology. Consider these “Dos & 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.

Antibodies destroy an infected cell by a virus

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.

 

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Insights in Invasive Bladder Cancer

5/12/23 10:30 AM / by Champions Oncology posted in Solid Tumor Oncology

T Lymphocytes and Cancer Cell photo

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.

Mutation Landscape  

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].

 

Immunotherapy Insights

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].

T-cell, Tumor cell diagram

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.

 

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[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.

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Head & Neck Cancers - New Mutation Insights Lead to New Therapies

4/27/23 11:35 AM / by Champions Oncology posted in Solid Tumor Oncology

H&NBlog_Header

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].

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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.

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[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.

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Novel RNAs Insights Toward AML Development

4/13/23 2:15 PM / by Champions Oncology posted in Hematological Malignancies

3D rendering of cancer cell surrounded by red blood cells


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.

 

3D illustration of DNA strand

 

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.
       Hematologic Malignancies: Immunogenomic Landscape and Prognostic Tools


  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.
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Overcoming Drug Resistance in AML: Targeting Tricky Signaling Pathways

3/30/23 6:44 PM / by Champions Oncology posted in Hematological Malignancies

Overcoming Drug Resistance in 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]. Overcoming Drug Resistance in AMLDXR 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.

 

Hematologic Malignancies: Immunogenomic Landscape and Prognostic Tools

 


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.

 

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UnTIL We Meet Again: Testing TIL Therapies in an Ex Vivo Platform

3/7/23 1:15 PM / by Champions Oncology posted in Immuno-Oncology, Ex Vivo Platforms

3D Rendering of a Natural Killer Cell (NK Cell) destroying a cancer cell

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. Scientist injecting liquid into a microtiter plate 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.

 

Get your copy of the Autologous TIL Platform - download now

 

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Clinical Flow Cytometry – Understanding GCLP Standards and Compliance

3/2/23 10:30 AM / by Champions Oncology posted in Clinical Flow Cytometry

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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.

030322_BlogInsideA 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.

 

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Targeted Therapy for Biliary Cancers

2/23/23 12:46 PM / by Champions Oncology posted in Solid Tumor Oncology

3d rendered image, enhanced scanning electron micrograph (SEM) of cancer cell

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].

 

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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

     

 

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Leveraging IHC as a powerful clinical tool for IO therapies

2/16/23 11:28 AM / by Champions Oncology posted in IHC

Mara_2Scientist examining tissue sample slides

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.

 

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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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