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NGS in Oncology
Cancer Genomics Research Clinical Cancer Research Cancer Companion Diagnostics NGS in Oncology

Tumor Mutational Burden

What is tumor mutational burden (TMB)?

Tumor mutational burden (TMB) is the number of somatic mutations within the coding region of a tumor genome. It correlates with response to immunotherapeutic agents such as checkpoint inhibitors.1-5 Studies have indicated that a high tumor mutational burden, or load, increases the likelihood that immunogenic neoantigens expressed by tumor cells may induce a response to immunotherapy.1-4

What types of cancer are associated with TMB?

Numerous clinical studies have demonstrated that higher mutational burden correlates to improved survival benefits in patients receiving checkpoint inhibitor therapies for cancers such as melanoma, colon, and non-small cell lung cancer (NSCLC). Data from past clinical trials like CheckMate 227 have demonstrated that, in NSCLC, higher TMB is associated with improved clinical outcomes.6

TMB prevalence

13-26% of advanced cancer patients exhibit TMB-High results across tumor types.5,7-10

Testing for TMB using NGS

Large assays with ~1.1 Mb of coding genome are needed to accurately assess TMB.11, 12 Comprehensive Genomic Profiling (CGP) analyzes hundreds of biomarkers simultaneously, including TMB.

Improving precision medicine for high TMB using CGP

TMB measured from blood (bTMB) using CGP has been associated with improved clinical outcomes when ≥ 20 mutations per megabase were detected in mNSCLC.13-15

Immunotherapy treatments for TMB

Clinical trials and regulatory approvals have established several cancer immunotherapy treatments for multiple tumor types.16 The ability to identify molecular signatures that help predict response to these treatments is important for better predicting who will benefit from these treatments.

Tumor mutational burden (TMB) and microsatellite instability (MSI) status are two FDA-approved biomarkers indicative of patient response to immunotherapy and recommended for testing by guidelines.17-18

Approved therapies for cancers with high TMB

Stay up to date on FDA-approved therapies for TMB high cancers in the US.

View FDA approvals

Using comprehensive genomic profiling approach for TMB NGS testing

Comprehensive genomic profiling (CGP) can detect biomarkers at nucleotide-level resolution and typically comprises all large genomic signatures (TMB, MSI), maximizing the ability to find clinically actionable alterations.

Single-gene and small hotspot panel testing methods are not large enough to detect known and emerging biomarkers and molecular signatures, potentially missing important actionable variants.19-22 CGP provides broad molecular coverage of the genome, capturing a comprehensive set of clinically relevant genes in one test.

Assess tumor types with single NGS assay

CGP can offer both actionable and potentially actionable results to help identify more effective therapeutic paths and innovative clinical trial options for cancer patients.

Learn more about CGP

TMB Workflow

 
Library Preparation

 

TruSight Oncology Comprehensive IVD

TruSight Oncology Comprehensive (EU) is the first CE-marked IVD test kit for comprehensive genomic profiling based on DNA and RNA that consolidates multiple iterative tests into one.

 
Sequencing

 

NextSeq 550Dx System

The NextSeq 550Dx instrument is a CE-marked IVD that enables clinical laboratories to develop and perform a wide range of applications..

 
Data Analysis

 

Local Run Manager TruSight Oncology Comprehensive (EU) Analysis Module (On-Instrument Software)

Analyze results using the TruSight Oncology Comprehensive Local Run Manager analysis module.

Learn more about testing for TMB

Measuring tumor mutational burden

A study by Dr. Albrecht Stenzinger and his colleagues investigated the influence of gene panel size on the precision of tumor mutational burden measurement.

CGP at a glance

Get a quick overview of CGP testing and how it improves patient outcomes.

A new era for better patient outcomes

Get a better understanding of TruSight Oncology Comprehensive (EU).

References
  1. Rizvi NA, Hellmann MD, Snyder A, et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348 (6230):124-128.
  2. Snyder A, Makarov V, Merghoub T, et al. Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma. N Engl J Med. 2014;371(23):2189-2199.
  3. Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 2015;350(6257):207-211.
  4. Garofalo A, Sholl L, Reardon B, et al. The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine. Genome Med. 2016;8(1):79. doi:10.1186/s13073-016-0333-9.
  5. Marabelle A, Fakih M, Lopez J, et al. Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet Oncol. 2020;21(10):1353-1365. doi.org/10.1016/S1470-2045(20)30445-9.
  6. Hellmann MD, Ciuleanu TE, Pluzanski A, et al. Nivolumab plus Ipilimumab in Lung Cancer with a High Tumor Mutational Burden. N Engl J Med. 2018;378(22): 2093–2104.
  7. European Society for Medical Oncology. Guidelines | ESMO. ESMO website. https://www.esmo.org/guidelines. Accessed February 10, 2021. 16.
  8. Cristescu, R, Aurora-Garg, D, Albright, D, et al. Association Between Tumor Mutational Burden Assessed by Whole-Exome Sequencing and Outcomes of Pembrolizumab Monotherapy. Poster presented at: 2020 American Association of Cancer Research Virtual Annual Meeting II; June 22-24, 2020. LB-261.
  9. Samstein RM, Lee CH, Shoushtari AN, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51(2):202-206. doi:10.1038/s41588-018-0312-8.
  10. Goodman AM, Kato S, Bazhenova L, et al. Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers. Mol Cancer Ther. 2017;16(11):2598-2608. doi:10.1158/1535-7163.MCT-17-0386.
  11. Chalmers ZR, Connelly CF, Fabrizio D, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9(1):34. Published 2017 Apr 19. doi:10.1186/s13073-017-0424-2.
  12. Buchhalter I, Rempel E, Endris V, et al. Size matters: Dissecting key parameters for panel-based tumor mutational burden analysis. Int J Cancer. 2019;144(4):848-858. doi:10.1002/ijc.31878.
  13. Rizvi NA, Cho BC, Reinmuth N, et al. Durvalumab With or Without Tremelimumab vs Standard Chemotherapy in Firstline Treatment of Metastatic Non-Small Cell Lung Cancer: The MYSTIC Phase 3 Randomized Clinical Trial. JAMA Oncol. 2020;6(5):661-674. doi:10.1001/jamaoncol.2020.0237.
  14. Garassino MC, Gadgeel SM, Rodriguez-Abreu D, et al. Evaluation of blood TMB (bTMB) in KEYNOTE-189: Pembrolizumab (pembro) plus chemotherapy (chemo) with pemetrexed and platinum versus placebo plus chemo as first-line therapy for metastatic nonsquamous NSCLC. J Clin Oncol. 2020;38:15_suppl, 9521-9521. doi: 10.1158/1078-0432.CCR-20-3771.
  15. Gandara DR, Paul SM, Kowanetz M, et al. Blood-based tumor mutational burden as a predictor of clinical benefit in non-small-cell lung cancer patients treated with atezolizumab. Nat Med. 2018;24(9):1441-1448. doi:10.1038/s41591-018-0134-3.
  16. Emens LA, Ascierto PA, Darcy PK, et al. Cancer immunotherapy: Opportunities and challenges in the rapidly evolving clinical landscape. Eur J Cancer. 2017;81:116-129. doi:10.1016/j.ejca.2017.01.035
  17. Luchini C, Bibeau F, Ligtenberg MJ, et al. ESMO recommendations on microsatellite instability testing for immunotherapy in cancer, and its relationship with PD-1/PD-L1 expression and tumour mutational burden: a systematic review-based approach. Ann. Oncol. 2019;30(8):1232-1243. doi:https://doi.org/10.1093/annonc/mdz116.
  18. Chakravarty D, Johnson A, Sklar J, et al. Somatic genomic testing in patients with metastatic or advanced cancer: ASCO provisional clinical opinion. J. Clin. 2022; 40(11):1231-1258. doi: 10.1200/JCO.21.02767.
  19. Suh JH, Johnson A, Albacker L, et al. Comprehensive Genomic Profiling Facilitates Implementation of the National Comprehensive Cancer Network Guidelines for Lung Cancer Biomarker Testing and Identifies Patients Who May Benefit From Enrollment in Mechanism-Driven Clinical Trials. Oncologist. 2016;21(6):684-691. doi:10.1634/theoncologist.2016-0030.
  20. Drilon A, Wang L, Arcila ME, et al. Broad, Hybrid Capture-Based Next-Generation Sequencing Identifies Actionable Genomic Alterations in Lung Adenocarcinomas Otherwise Negative for Such Alterations by Other Genomic Testing Approaches. Clin Cancer Res. 2015;21(16):3631-3639. doi:10.1158/1078-0432.CCR-14-2683.
  21. Ali SM, Hensing T, Schrock AB, et al. Comprehensive Genomic Profiling Identifies a Subset of Crizotinib-Responsive ALKRearranged Non-Small Cell Lung Cancer Not Detected by Fluorescence In Situ Hybridization. Oncologist. 2016;21(6):762-770. doi:10.1634/theoncologist.2015-0497.
  22. Schrock AB, Frampton GM, Herndon D, et al. Comprehensive Genomic Profiling Identifies Frequent Drug-Sensitive EGFR Exon 19 Deletions in NSCLC not Identified by Prior Molecular Testing. Clin Cancer Res. 2016;22(13):3281-3285. doi:10.1158/1078-0432. CCR-15-1668.
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