Tissue Microarray from Cell Block Material (cbTMA)—An Additional Shot for Cytology in the Predictive Pathology Era: The PD-L1 Experience

Generally, predictive biomarker tests are clinically validated on histological formalin-fixed, paraffin-embedded (FFPE) samples. In addition to FFPE samples, cytological samples have also emerged as a useful approach to detect predictive biomarkers. However, as of today, despite the promising results reported in the recent literature, their full implementation in routine clinical practice is still lagging owing to a lack of standardized preparatory protocols, challenging assessments of cyto-histological correlation, and variable inter-observer agreement. The aim of this report was to explore the possibility of implementing a large-scale validation of predictive biomarker testing on cytological material. To this aim, we evaluated the technical feasibility of PD-L1 assessment on a cell block (CB)-derived tissue microarray (cbTMA). Consecutive and unselected CBs prepared from metastatic lymph node fine-needle cytology (FNC) samples were retrospectively collected and used for TMA construction. PD-L1 immunohistochemistry (IHC) was carried out on cbTMA sections with the companion diagnostic kit SP263 assay. TMA contained 33 CB-derived cores. A total of 20 sections were hematoxylin and eosin (H&E) stained. Overall, 29 (88%) samples were visible at least in one H&E-stained slide. Four cases out of five sections stained with the SP263 assay (4/29, 13.8%) showed PD-L1 positivity in neoplastic and/or immune cells; remarkably, no unspecific background was observed. Although our study was based on a limited and non-selected series, our findings do provide proof of concept for the use of cbTMA in predictive biomarker testing on cytological material in large-scale post-clinical trial validation studies, multicenter studies, and quality control programs.

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Precision Medicine for Lung Cancer: Role of the Surgical Pathologist

Archives of Pathology & Laboratory Medicine ◽

10.5858/arpa.2012-0390-ra ◽

2012 ◽

Vol 136 (10) ◽

pp. 1186-1189 ◽

Cited By ~ 6

Author(s):

Philip T. Cagle ◽

Jeffrey Myers

Keyword(s):

Lung Cancer ◽

Precision Medicine ◽

Predictive Biomarkers ◽

Predictive Biomarker ◽

Molecular Techniques ◽

Specific Cell ◽

Traditional Role ◽

Lung Cancers ◽

Biomarker Testing

Precision medicine is altering the traditional role of the surgical pathologist in caring for patients with lung cancer. Diagnosing specific cell type is now a foundation for selecting lung cancers for predictive-biomarker testing by molecular techniques. Using conventional techniques and familiar equipment, the surgical pathologist's role goes beyond this important step and will include screening for, and possibly diagnosis of, predictive biomarkers as we illustrate for one predictive biomarker. Pathologists should embrace the innovations described at the Houston Lung Symposium but must recognize that their traditional expertise will be an important component of precision medicine for the foreseeable future.

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Predictive biomarkers in nonsmall cell carcinoma and their clinico-pathological association

South Asian Journal of Cancer ◽

10.4103/sajc.sajc_373_18 ◽

2019 ◽

Vol 08 (04) ◽

pp. 250-254 ◽

Cited By ~ 1

Author(s):

Anurag Mehta ◽

Nayana N. Sriramanakoppa ◽

Poojan Agarwal ◽

Gayatri Viswakarma ◽

Smreti Vasudevan ◽

...

Keyword(s):

Cell Carcinoma ◽

Kinase Inhibitors ◽

Growth Factor Receptor ◽

Stage Iv ◽

Predictive Biomarkers ◽

Progression Free Survival ◽

Predictive Biomarker ◽

First Line ◽

Anaplastic Lymphoma ◽

Biomarker Testing

Abstract Background: Lung cancer is the leading cause of cancer-related mortality worldwide. Genome-directed therapy is less toxic, prolongs survival and provides a better quality of life. Predictive biomarker testing, therefore, has become a standard of care in advanced lung cancers. The objective of this study was to relate clinical and pathological features, including response to targeted therapy (TT) and progression-free survival (PFS) with positive driver mutation. Materials and Methods: Archival data of nonsmall cell carcinoma patients with Stage IV disease were retrieved. Those who tested positive for one of the four biomarkers (epidermal growth factor receptor [EGFR], anaplastic lymphoma kinase [ALK], MET, and ROS) were included. Patient demographics and clinical features were reviewed. Tumor histomorphology was correlated with oncological drivers. Treatment response, PFS, and overall survival were studied in three subcohorts of patients who received computed tomography (CT), CT followed by TT and those who received TT in the first line. Results: A total of 900 patients underwent biomarker evaluation of which 288 tested positive. Frequency of the four biomarkers observed was 26.6% (229/860), 6.6% (51/775), 6.6% (5/75), and 5.1% (3/59) for EGFR, ALK, MET, and ROS-1, respectively. The median PFS for EGFR-mutated cohort was 12 months, whereas it was 21 months for ALK protein overexpressing cases. Patients treated with first-line tyrosine kinase inhibitors performed better compared to those who were switched from chemotherapy to TT or those who received chemotherapy alone (P < 0.05). Conclusion: Biomarker testing has improved patient outcome. Genome-directed therapy accords best PFS with an advantage of nearly 10 months over cytotoxic therapy.

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Biomarker testing in oncology – Requirements for organizing external quality assessment programs to improve the performance of laboratory testing: revision of an expert opinion paper on behalf of IQNPath ABSL

Virchows Archiv ◽

10.1007/s00428-020-02928-z ◽

2020 ◽

Cited By ~ 2

Author(s):

K. Dufraing ◽

◽

F. Fenizia ◽

E. Torlakovic ◽

N. Wolstenholme ◽

...

Keyword(s):

Current Knowledge ◽

Predictive Biomarkers ◽

Predictive Biomarker ◽

Test Methods ◽

External Quality ◽

Patients With Cancer ◽

Umbrella Organization ◽

Biomarker Testing ◽

Cancer Types

Abstract In personalized medicine, predictive biomarker testing is the basis for an appropriate choice of therapy for patients with cancer. An important tool for laboratories to ensure accurate results is participation in external quality assurance (EQA) programs. Several providers offer predictive EQA programs for different cancer types, test methods, and sample types. In 2013, a guideline was published on the requirements for organizing high-quality EQA programs in molecular pathology. Now, after six years, steps were taken to further harmonize these EQA programs as an initiative by IQNPath ABSL, an umbrella organization founded by various EQA providers. This revision is based on current knowledge, adds recommendations for programs developed for predictive biomarkers by in situ methodologies (immunohistochemistry and in situ hybridization), and emphasized transparency and an evidence-based approach. In addition, this updated version also has the aim to give an overview of current practices from various EQA providers.

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Genomic characterization of ATM alterations in advanced pancreatic ductal adenocarcinoma (PDAC).

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.3_suppl.396 ◽

2021 ◽

Vol 39 (3_suppl) ◽

pp. 396-396

Author(s):

Sheron Perera ◽

Robert Edward Denroche ◽

Spring Holter ◽

Deirdre Kelly ◽

Amy Zhang ◽

...

Keyword(s):

Homologous Recombination ◽

Large Scale ◽

Predictive Biomarkers ◽

Predictive Biomarker ◽

Parp Inhibitors ◽

Ductal Adenocarcinoma ◽

Parp Inhibition ◽

Germline Variants ◽

Pathogenic Variants

396 Background: BRCA1/2 and PALB2 are genes critical to the faithful repair of double strand breaks through the homologous recombination repair (HRR) pathway. Alterations in these genes serve as predictive biomarkers to both platinum and PARP inhibitors. Ataxia-telangiectasia mutated ( ATM) is also indirectly involved in HRR; however, its role as a predictive biomarker to DNA damage response agents is debated. Herein we evaluated the genomic characteristics and clinical outcomes of patients with ATM alterations on the Comprehensive Molecular Characterization of Advanced Ductal Pancreas Adenocarcinoma for Better Treatment Selection (COMPASS) trial. Methods: Patients on this study undergo a biopsy for whole genome sequencing (WGS) and RNA sequencing prior to chemotherapy; those with germline variants in ATM were reviewed by a genetics counsellor and defined as pathogenic, likely pathogenic, variant of unknown significance (VUS) or benign/likely benign. Genomic characteristics were reviewed and published classifiers of homologous recombination deficiency (HRD) were applied to all cases and included the percentage of substitution base signature (SBS) 3, the HRDetect score, the computed algorithm of large scale transitions, telomeric allelic imbalances and loss of heterozygosity (LOH), otherwise known as the genomic instability score (GIS). Results: As of January 2020, 304 patients were enrolled and 245 patients had both WGS and clinical data available. 86 germline variants in ATM were present in 70 patients. The majority of these (80%) were classified as benign or likely benign. 10 VUS were detected and 4 patients (2%) had pathogenic/likely pathogenic variants (PV). Of these 4 patients, LOH or a second somatic hit was evident in 1 case. Upon review of the PVs and VUS, SBS were consistent with typical PDAC and tumour mutational burden was low. HRDetect scores were low ( < 0.1) for 13/14 cases with either a VUS or PV; one VUS without biallelic loss, had a high HRDetect score, with presence of SBS 3 and a high GIS. This particular case was also found to have a tandem duplicator phenotype. None of the 4 cases with PV had evidence of HRD. Furthermore all four were treated with platinum based regimens without evidence of response. Conclusions: In a large series of sequenced pancreatic cancers, the presence of pathogenic germline variants in ATM was rare, with none of the cases demonstrating evidence of HRD. This suggests that this population is unlikely to benefit from PARP inhibition.

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The combined detection of Amphiregulin, Cyclin A1 and DDX20/Gemin3 expression predicts aggressive forms of oral squamous cell carcinoma

British Journal of Cancer ◽

10.1038/s41416-021-01491-x ◽

2021 ◽

Author(s):

Ekaterina Bourova-Flin ◽

Samira Derakhshan ◽

Afsaneh Goudarzi ◽

Tao Wang ◽

Anne-Laure Vitte ◽

...

Keyword(s):

Gene Expression ◽

Squamous Cell ◽

Large Scale ◽

Biomarker Discovery ◽

Gene Expression Signature ◽

Predictive Biomarkers ◽

Specific Gene ◽

Specific Expression ◽

Intrinsic Nature ◽

Independent Cohort

Abstract Background Large-scale genetic and epigenetic deregulations enable cancer cells to ectopically activate tissue-specific expression programmes. A specifically designed strategy was applied to oral squamous cell carcinomas (OSCC) in order to detect ectopic gene activations and develop a prognostic stratification test. Methods A dedicated original prognosis biomarker discovery approach was implemented using genome-wide transcriptomic data of OSCC, including training and validation cohorts. Abnormal expressions of silent genes were systematically detected, correlated with survival probabilities and evaluated as predictive biomarkers. The resulting stratification test was confirmed in an independent cohort using immunohistochemistry. Results A specific gene expression signature, including a combination of three genes, AREG, CCNA1 and DDX20, was found associated with high-risk OSCC in univariate and multivariate analyses. It was translated into an immunohistochemistry-based test, which successfully stratified patients of our own independent cohort. Discussion The exploration of the whole gene expression profile characterising aggressive OSCC tumours highlights their enhanced proliferative and poorly differentiated intrinsic nature. Experimental targeting of CCNA1 in OSCC cells is associated with a shift of transcriptomic signature towards the less aggressive form of OSCC, suggesting that CCNA1 could be a good target for therapeutic approaches.

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Immune Checkpoint Inhibitors in Urothelial Carcinoma: Recommendations for Practical Approaches to PD-L1 and Other Potential Predictive Biomarker Testing

Cancers ◽

10.3390/cancers13061424 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1424

Author(s):

Antonio Lopez-Beltran ◽

Fernando López-Rios ◽

Rodolfo Montironi ◽

Sophie Wildsmith ◽

Markus Eckstein

Keyword(s):

Cell Death ◽

Programmed Cell Death ◽

Best Practice ◽

Checkpoint Inhibitors ◽

Predictive Biomarker ◽

High Quality ◽

The Status ◽

Biomarker Testing ◽

Novel Biomarkers ◽

Scoring Algorithms

Immuno-oncology (IO) agents (anti–programmed cell death 1 (PD-1) and anti–programmed cell death-ligand 1 (PD-L1)) are approved as first- and second-line treatments for metastatic UC. PD-L1 expression levels in UC tumors help clinicians determine which patients are more likely to respond to IO therapies. Assays for approved IO agents use different antibodies, immunohistochemical protocols, cutoffs (defining “high” vs. “low” PD-L1 expression), and scoring algorithms. The robust control of pre-analytical and analytical standards is needed to obtain high-quality PD-L1 results. To better understand the status and perspectives of biomarker-guided patient selection for anti–PD-1 and anti–PD-L1 agents in UC, three workshops were held from December 2018 to December 2019 in Italy, Malaysia, and Spain. The primary goal was to develop recommendations for best practice approaches to PD-L1 testing in UC. Recommendations pertaining to the interpretation and reporting of the results of PD-L1 assays from experienced pathologists and oncologists from around the globe are included. A test request form for pathology laboratories was developed as a critical first step for oncologists/urologists to encourage communication between clinicians and pathologists, ensuring fast and high-quality test results. In this era of personalized medicine, we briefly discuss novel biomarkers being evaluated for IO agents in UC.

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BIOM-32. ENDOPLASMIC RETICULUM PROTEIN SSR3 DETERMINES AND PREDICTS RESPONSE TO PACLITAXEL IN BREAST CANCER AND GLIOBLASTOMA

Neuro-Oncology ◽

10.1093/neuonc/noab196.063 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi17-vi18

Author(s):

Crismita Dmello ◽

Aarón Sonabend ◽

Víctor Arrieta ◽

Daniel Zhang ◽

Deepak Kanojia ◽

...

Keyword(s):

Breast Cancer ◽

Endoplasmic Reticulum ◽

Glioma Cells ◽

Predictive Biomarkers ◽

Predictive Biomarker ◽

Precision Oncology ◽

Patient Response ◽

Knock Out ◽

Genome Wide ◽

A Genome

Abstract Paclitaxel (PTX) is one the most potent and commonly used chemotherapies for breast and pancreatic cancer. Given the potency of this drug for glioblastomas (GBM) several ongoing clinical trials are investigating means of enhancing delivery of PTX across the blood-brain barrier for this disease. In spite of the efficacy of PTX, individual tumors exhibit variable susceptibility to this drug, with response rate in the range of 30%-60%. To identify predictive biomarkers for response to PTX, we performed a genome-wide CRISPR knock-out screen using human glioma cells. The most enriched genes in the CRISPR screen underwent further selection based on their correlation with survival in the breast cancer patient cohorts treated with PTX and not in patients treated with other chemotherapies, a finding that was validated on a second independent patient cohort. This led to the discovery of endoplasmic reticulum (ER) protein SSR3 as a putative predictive biomarker for PTX. SSR3 protein levels showed positive correlation with response to PTX in breast cancer cells, glioma cells, in multiple intracranial glioma xenografts and in GBM patient derived explant cultures. Knockout of SSR3 turned the cells resistant to PTX while its overexpression sensitized the cells to PTX. In gliomas, SSR3-mediated susceptibility to PTX relates to modulation of phosphorylation of ER stress sensor IRE1α. Thus, by using genome-wide screen combined with patient response data, we discovered a biomarker that demonstrates causal and correlative relationship with response to PTX in breast cancer and GBM. Prospective validation of this biomarker is warranted for its broad implementation for precision oncology.

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An automated procedure to properly handle digital images in large scale Tissue Microarray experiments

Computer Methods and Programs in Biomedicine ◽

10.1016/j.cmpb.2005.04.004 ◽

2005 ◽

Vol 79 (3) ◽

pp. 197-208 ◽

Cited By ~ 10

Author(s):

Rossana Dell’Anna ◽

Francesca Demichelis ◽

Mattia Barbareschi ◽

Andrea Sboner

Keyword(s):

Tissue Microarray ◽

Large Scale ◽

Digital Images ◽

Microarray Experiments

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Use of Circulating Tumour DNA (ctDNA) for Measurement of Therapy Predictive Biomarkers in Patients with Cancer

Journal of Personalized Medicine ◽

10.3390/jpm12010099 ◽

2022 ◽

Vol 12 (1) ◽

pp. 99

Author(s):

Michael J. Duffy ◽

John Crown

Keyword(s):

Gold Standard ◽

Kinase Inhibitors ◽

Predictive Biomarkers ◽

Lower Sensitivity ◽

Cancer Therapies ◽

Gold Standard Method ◽

Biomarker Analysis ◽

Egfr Tyrosine Kinase Inhibitors ◽

Biomarker Testing ◽

Circulating Tumour Dna

Biomarkers that predict likely response or resistance to specific therapies are critical in personalising treatment for cancer patients. Such biomarkers are now available for an increasing number of anti-cancer therapies, especially targeted therapy and immunotherapy. The gold-standard method for determining predictive biomarkers requires tumour tissue. Obtaining tissue, however, is not always possible and even if possible, the amount or quality of tissue obtained may be inadequate for biomarker analysis. Tumour DNA, however, can be released into the bloodstream, giving rise to what is referred to as circulating tumour DNA (ctDNA). In contrast to tissue, blood can be obtained from effectively all patients in a minimally invasive and safe manner. Other advantages of blood over tissue for biomarker testing include a shorter turn-around time and an ability to perform serial measurements. Furthermore, blood should provide a more complete profile of mutations present in heterogeneous tumours than a single-needle tissue biopsy. A limitation of blood vis-à-vis tissue, however, is lower sensitivity and, thus, the possibility of missing an actionable mutation. Despite this limitation, blood-based predictive biomarkers, such as mutant EGFR for predicting response to EGFR tyrosine kinase inhibitors in advanced non-small-cell lung cancer and mutant PIK3CA for predicting response to alpelisib in combination with fulvestrant in advanced breast cancer, may be used when tissue is unavailable. Although tissue remains the gold standard for detecting predictive biomarkers, it is likely that several further blood-based assays will soon be validated and used when tissue is unavailable or unsuitable for analysis.

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Identification of predictive biomarker for immunotherapy by associating with CD8+T cell Infiltration in lung adenocarcinoma.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e21177 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e21177-e21177

Author(s):

Puyuan Xing ◽

Teng Li ◽

Han Wang ◽

Lin Yang ◽

Guoqiang Wang ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Predictive Biomarkers ◽

Tumor Infiltrating Lymphocytes ◽

Predictive Performance ◽

Predictive Biomarker ◽

Pooled Analysis ◽

The Cancer Genome Atlas ◽

T Cell Infiltration ◽

Or Groups ◽

Cancer Genome Atlas

e21177 Background: Tumor immune microenvironment (TIME) has been proved associated with response to immunotherapy(I/O). We hypothesized that screening potential mutation pattern which could significantly impact the tumor infiltrating lymphocytes(TILs) can help us to identify predictive biomarkers for I/O in Lung adenocarcinoma(LUAD). Methods: Multiple-dimensional data from The Cancer Genome Atlas LUAD cohort (n = 514) was used for building a mathematical model beween mutation signature and CD8+TIL score (based on MCP-counter). An independent public validation cohort (cohort 1: LUAD, n = 598) were used to assess the immunotherapeutic predictive performance of the potential mutation patterns. Results: Top 100 gene associated with CD8+TIL score were selected based on MC+ model which can provides the minimum non-convexity of the penalized loss given the level of bias. Seven TIME genes (SPTA1 coef 0.09; MET coef 0.02; HSD3B1 coef -0.00; STAT4 coef -0.01; EGFR coef -0.08; PIK3CB coef -0.08; KEAP1 coef -0.24) were generated by taking the intersection of the top 100 mutant genes and FoundationOne (F1) CDx NGS 315 genes panel and verified in cohort 1. Survival analysis showed that SPTA1mt was the only one that associated with both significantly longer PFS (median PFS 3.15 vs 2.89 months; HR 0.65; 95% CI 0.45 to 0.93; p = 0.02) and OS (median PFS 15.08 vs 7.36 months; HR 0.59; 95% CI 0.40 to 0.88; p = 0.01) for patients who received I/O compared with chemotherapy(CT) among seven TIME genes. In order to test our hypothesis fully, a pooled analysis of SPTA1mt (a core positive predictors of CD8+TILs) and KEAP1mt (a core negative predictors for CD8+TILs ) were conducted and yielded that co occurrence of SPTA1mt and KEAP1mt had a compound effects for TIME. The validation showed that co mutation with SPTA1mt was accompanied by an decrease HR for I/O vs. CT in both PFS (HR S+K vs. K only 0.59 vs 1.56) and OS (HR S+K vs. K only 0.39 vs 0.80) for KEAP1mt patients. Conclusions: Our data show that it is feasible to identify individuals or groups of individual with specific mutations to immunotherapy responses from TIME view. SPTA1mt was a core predictors for higher CD8+ TILs and can be identified as a predictive biomarker for benefit from I/O compared with CT. Prospective studies are warranted for further investigation.

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