Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

Characterization of tumors utilizing next‐generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence‐based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.

[1]  Olaf Neumann,et al.  Measurement of tumor mutational burden (TMB) in routine molecular diagnostics: in silico and real‐life analysis of three larger gene panels , 2019, International journal of cancer.

[2]  Olaf Neumann,et al.  Size matters: Dissecting key parameters for panel‐based tumor mutational burden analysis , 2018, International journal of cancer.

[3]  Olaf Neumann,et al.  Implementing tumor mutational burden (TMB) analysis in routine diagnostics-a primer for molecular pathologists and clinicians. , 2018, Translational lung cancer research.

[4]  Arunika Mukhopadhaya Nobel Prize in Physiology or Medicine – 2018 , 2018, Resonance.

[5]  T A Chan,et al.  Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic , 2018, Annals of oncology : official journal of the European Society for Medical Oncology.

[6]  J. Lunceford,et al.  Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy , 2018, Science.

[7]  Paul Baas,et al.  Liquid Biopsy for Advanced Non‐Small Cell Lung Cancer (NSCLC): A Statement Paper from the IASLC , 2018, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[8]  Jacob Silterra,et al.  Blood-based tumor mutational burden as a predictor of clinical benefit in non-small-cell lung cancer patients treated with atezolizumab , 2018, Nature Medicine.

[9]  Steven J. M. Jones,et al.  Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients , 2018, Cancer cell.

[10]  D. Lipson,et al.  Abstract 5706: A blood-based next-generation sequencing assay to determine tumor mutational burden (bTMB) is associated with benefit to an anti-PD-L1 inhibitor, atezolizumab , 2018, Immunology.

[11]  Matthew D. Hellmann,et al.  Abstract CT078: Tumor mutational burden (TMB) as a biomarker for clinical benefit from dual immune checkpoint blockade with nivolumab (nivo) + ipilimumab (ipi) in first-line (1L) non-small cell lung cancer (NSCLC): identification of TMB cutoff from CheckMate 568 , 2018, Clinical Trials.

[12]  Edward S. Kim,et al.  Prospective clinical evaluation of blood-based tumor mutational burden (bTMB) as a predictive biomarker for atezolizumab (atezo) in 1L non-small cell lung cancer (NSCLC): Interim B-F1RST results. , 2018 .

[13]  Paolo A Ascierto,et al.  Tumor Mutational Burden and Efficacy of Nivolumab Monotherapy and in Combination with Ipilimumab in Small-Cell Lung Cancer. , 2018, Cancer cell.

[14]  Arun Ahuja,et al.  Genomic Features of Response to Combination Immunotherapy in Patients with Advanced Non-Small-Cell Lung Cancer , 2018, Cancer cell.

[15]  J. Szustakowski,et al.  Nivolumab plus Ipilimumab in Lung Cancer with a High Tumor Mutational Burden , 2018, The New England journal of medicine.

[16]  Zhidong Liu,et al.  The characteristics of ctDNA reveal the high complexity in matching the corresponding tumor tissues , 2018, BMC Cancer.

[17]  Brooke L. Billman,et al.  Circulating Tumor DNA Analysis in Patients With Cancer: American Society of Clinical Oncology and College of American Pathologists Joint Review. , 2018, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[18]  Y. Boumber Tumor mutational burden (TMB) as a biomarker of response to immunotherapy in small cell lung cancer. , 2018, Journal of thoracic disease.

[19]  R. Salgia,et al.  Value-based genomics , 2018, Oncotarget.

[20]  E. Jaffee,et al.  Tumor Mutational Burden and Response Rate to PD-1 Inhibition. , 2017, The New England journal of medicine.

[21]  M. Ringnér,et al.  Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma , 2017, Nature Communications.

[22]  Etienne Rouleau,et al.  Whole exome sequencing for determination of tumor mutation load in liquid biopsy from advanced cancer patients , 2017, PloS one.

[23]  K. Cole,et al.  Comprehensive Analysis of Hypermutation in Human Cancer , 2017, Cell.

[24]  T. Chan,et al.  Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab , 2017, Cell.

[25]  Razelle Kurzrock,et al.  Hypermutated Circulating Tumor DNA: Correlation with Response to Checkpoint Inhibitor–Based Immunotherapy , 2017, Clinical Cancer Research.

[26]  Matthew D. Galsky,et al.  848PDImpact of zumor mutation burden on nivolumab efficacy in second-line urothelial carcinoma patients: Exploratory analysis of the phase ii checkmate 275 study , 2017 .

[27]  Seung-Ho Shin,et al.  A Method to Evaluate the Quality of Clinical Gene-Panel Sequencing Data for Single-Nucleotide Variant Detection. , 2017, The Journal of molecular diagnostics : JMD.

[28]  Ying Sun,et al.  Genomic Analysis of Tumor Microenvironment Immune Types across 14 Solid Cancer Types: Immunotherapeutic Implications , 2017, Theranostics.

[29]  T. Stricker,et al.  Abstract LB-105: Characterization of total mutational burden in the GENIE cohort: Small and large panels can provide TMB information but to varying degrees , 2017 .

[30]  M. Socinski,et al.  First‐Line Nivolumab in Stage IV or Recurrent Non–Small‐Cell Lung Cancer , 2017, The New England journal of medicine.

[31]  T. Taxter,et al.  Comparison of tumor mutational burden (TMB) across tumor tissue and circulating tumor DNA (ctDNA). , 2017 .

[32]  Y. Sasaki,et al.  Assessment of the quality of DNA from various formalin-fixed paraffin-embedded (FFPE) tissues and the use of this DNA for next-generation sequencing (NGS) with no artifactual mutation , 2017, PloS one.

[33]  Marina N Nikiforova,et al.  Guidelines for Validation of Next-Generation Sequencing-Based Oncology Panels: A Joint Consensus Recommendation of the Association for Molecular Pathology and College of American Pathologists. , 2017, The Journal of molecular diagnostics : JMD.

[34]  Levi Garraway,et al.  Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden , 2017, Genome Medicine.

[35]  C. Deng,et al.  Characterization of potential driver mutations involved in human breast cancer by computational approaches , 2017, Oncotarget.

[36]  Donavan T. Cheng,et al.  Mutational Landscape of Metastatic Cancer Revealed from Prospective Clinical Sequencing of 10,000 Patients , 2017, Nature Medicine.

[37]  J. Lunceford,et al.  Mutational load (ML) and T-cell-inflamed microenvironment as predictors of response to pembrolizumab. , 2017 .

[38]  R. Bourgon,et al.  Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: a single-arm, multicentre, phase 2 trial , 2017, The Lancet.

[39]  Bernat Gel,et al.  Benchmarking of Whole Exome Sequencing and Ad Hoc Designed Panels for Genetic Testing of Hereditary Cancer , 2017, Scientific Reports.

[40]  Jacqueline A. Hall,et al.  Quality to rely on: meeting report of the 5th Meeting of External Quality Assessment, Naples 2016 , 2016, ESMO Open.

[41]  Etienne Rouleau,et al.  Integration of next-generation sequencing in clinical diagnostic molecular pathology laboratories for analysis of solid tumours; an expert opinion on behalf of IQN Path ASBL , 2016, Virchows Archiv.

[42]  M. Dimopoulos,et al.  DNA damage, tumor mutational load and their impact on immune responses against cancer. , 2016, Annals of translational medicine.

[43]  Nikhil Wagle,et al.  The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine , 2016, Genome Medicine.

[44]  C. Lefebvre,et al.  Mutational Landscape and Sensitivity to Immune Checkpoint Blockers , 2016, Clinical Cancer Research.

[45]  S. Roy-Chowdhuri,et al.  Preanalytic Variables in Cytology: Lessons Learned From Next-Generation Sequencing-The MD Anderson Experience. , 2016, Archives of pathology & laboratory medicine.

[46]  Daniel S. Chen,et al.  Immune escape to PD-L1/PD-1 blockade: seven steps to success (or failure). , 2016, Annals of oncology : official journal of the European Society for Medical Oncology.

[47]  R. Bourgon,et al.  Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial , 2016, The Lancet.

[48]  M. Marton,et al.  Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories , 2016, International journal of molecular sciences.

[49]  Eric S. Lander,et al.  Genomic Correlates of Immune-Cell Infiltrates in Colorectal Carcinoma , 2016, Cell reports.

[50]  Nicolai J. Birkbak,et al.  Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade , 2016, Science.

[51]  Mads Thomassen,et al.  Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data , 2016, PloS one.

[52]  Xianshu Gao,et al.  "Liquid biopsy"-ctDNA detection with great potential and challenges. , 2015, Annals of translational medicine.

[53]  R. Goswami,et al.  Analysis of Pre-Analytic Factors Affecting the Success of Clinical Next-Generation Sequencing of Solid Organ Malignancies , 2015, Cancers.

[54]  J. Snowden,et al.  The role of JAK/STAT signalling in the pathogenesis, prognosis and treatment of solid tumours , 2015, British Journal of Cancer.

[55]  P. Sharma,et al.  The future of immune checkpoint therapy , 2015, Science.

[56]  Martin L. Miller,et al.  Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer , 2015, Science.

[57]  T. Schumacher,et al.  Neoantigens in cancer immunotherapy , 2015, Science.

[58]  William J. Howat,et al.  Tissue fixation and the effect of molecular fixatives on downstream staining procedures , 2014, Methods.

[59]  Trevor J Pugh,et al.  A systematic approach to assessing the clinical significance of genetic variants , 2013, Clinical genetics.

[60]  Alex M. Fichtenholtz,et al.  Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing , 2013, Nature Biotechnology.

[61]  Rashmi Kanagal-Shamanna,et al.  Clinical validation of a next-generation sequencing screen for mutational hotspots in 46 cancer-related genes. , 2013, The Journal of molecular diagnostics : JMD.

[62]  David T. W. Jones,et al.  Signatures of mutational processes in human cancer , 2013, Nature.

[63]  Drew M. Pardoll,et al.  The blockade of immune checkpoints in cancer immunotherapy , 2012, Nature Reviews Cancer.

[64]  P. A. Futreal,et al.  Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. , 2012, The New England journal of medicine.

[65]  M. Gerstung,et al.  Reliable detection of subclonal single-nucleotide variants in tumour cell populations , 2012, Nature Communications.

[66]  Emily H Turner,et al.  Targeted Capture and Massively Parallel Sequencing of Twelve Human Exomes , 2009, Nature.

[67]  M. Stratton,et al.  The cancer genome , 2009, Nature.

[68]  Yoshimasa Tanaka,et al.  Involvement of PD-L1 on tumor cells in the escape from host immune system and tumor immunotherapy by PD-L1 blockade , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[69]  V. Natarajan,et al.  [The Nobel Prize in physiology or medicine]. , 1998, Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke.

[70]  G. Hampton,et al.  OA20.01 Tumor Mutation Burden (TMB) is Associated with Improved Efficacy of Atezolizumab in 1L and 2L+ NSCLC Patients , 2017 .

[71]  Trevor J Pugh,et al.  Mutational heterogeneity in cancer and the search for new cancer genes , 2014 .

[72]  Sofamor Danek,et al.  SUMMARY OF SAFETY AND EFFECTIVENESS DATA (SSED) , 2004 .

[73]  S. Jewell,et al.  Copyright © American Society for Investigative Pathology Review Effect of Fixatives and Tissue Processing on the Content and Integrity of Nucleic Acids , 2022 .