Skip NavigationSkip to Content
Return Return to Search Results

Aligning Tumor Mutational Burden (TMB) quantification across diagnostic platforms: Phase 2 of the Friends of Cancer Research TMB Harmonization Project

  1. Author:
    Vega, Diana Merino
    Yee, Laura M
    McShane, Lisa M
    Williams,Mickey
    Chen,Li
    Vilimas, Tomas
    Fabrizio, David
    Funari, Vincent
    Newberg, Justin
    Bruce, Lauryn Keeler
    Chen, Shu-Jen
    Baden, Jonathan
    Barrett, J Carl
    Beer, Philip
    Butler, Matthew
    Cheng, Jen-Hao
    Conroy, Jeffrey
    Cyanam, Dinesh
    Eyring, Kenneth
    Garcia, Elizabeth
    Green, George
    Gregersen, Vivi Raundahl
    Hellmann, Matthew D
    Keefer, Laurel A
    Lasiter, Laura
    Lazar, Alexander J
    Li, Ming-Chung
    Macconaill, Laura E
    Meier, Kristen
    Mellert, Hestia
    Pabla, Sarabjot
    Pallavajjalla, Aparna
    Pestano, Gary
    Salgado, Roberto
    Samara, Raed
    Sokol, Ethan S
    Stafford, Phillip
    Budczies, Jan
    Stenzinger, Albrecht
    Tom, Warren
    Valkenburg, Kenneth C
    Wang, XiaoZhe
    Weigman, Victor
    Xie, Mingchao
    Xie, Qian
    Zehir, Ahmet
    Zhao, Chen
    Zhao, Yingdong
    Stewart, Mark D
    Allen, Jeff

  2. Author Address

    Friends of Cancer Research, Washington, DC, USA., National Cancer Institute, Bethesda, MD, USA., Molecular Characterization Laboratory, Frederick National Lab for Cancer Research, Leidos Biomedical Research Inc., Frederick, MD, USA., Foundation Medicine Inc., Cambridge, MA, USA., NeoGenomics Laboratories, Aliso Viejo, CA, USA., ACT Genomics, Taipei, Taiwan., Bristol Myers Squibb Co., Princeton, NJ, USA., AstraZeneca Pharmaceuticals LP, Waltham, MA, USA., European Organisation for Research and Treatment of Cancer, Geneva, Switzerland., LGC Clinical Diagnostics, Gaithersburg, MD, USA., OmniSeq Inc., Buffalo, NY, USA., Clinical Sequencing Division, Thermo Fisher Scientific, Ann Arbor, MI, USA., Intermountain Precision Genomics, St. George, UT, USA., Brigham and Women 39;s Hospital, Boston, MA, USA., QIAGEN Inc, Aarhus, Denmark., Memorial Sloan Kettering Cancer Center, New York, NY, USA., Personal Genome Diagnostics, Baltimore, MD, USA., The University of Texas MD Anderson Cancer Center, Houston, TX, USA., Illumina Inc, Clinical Genomics, San Diego, CA, USA., Biodesix, Inc., Boulder, CO, USA., Johns Hopkins University, Baltimore, MD, USA., Caris Life Sciences Inc, Phoenix, Arizona, USA., Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany., EMD Serono Research and Development Institute, Inc., Billerica, MA, USA., Q Squared Solutions, Durham, NC, USA., General Dynamics Information Technology, Inc., Columbia, MD, USA., Friends of Cancer Research, Washington, DC, USA. Electronic address: mstewart@focr.org.,
    1. Year: 2021
    2. Date: Dec
    3. Epub Date: 2021 10 01
  2. Journal: Annals of oncology : official journal of the European Society for Medical Oncology
    1. 32
    2. 12
    3. Pages: 1626-1636
  4. Type of Article: Article
  5. ISSN: 0923-7534
  1. Abstract:

    Tumor Mutational Burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability and the development and use of a calibration tool that can help facilitate comparability across different panel assays may aid in broader adoption of panels assays and development of clinical applications. Twenty-nine tumor samples and ten human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values. Panel sizes greater than 667Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cutoffs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency (pMAF) resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from TCGA data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples, although RMSE across samples at the laboratory level was less often reduced. Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available. Copyright © 2021. Published by Elsevier Ltd.

    See More

  1. Keywords:

External Sources

  1. View Full Text
  2. DOI: 10.1016/j.annonc.2021.09.016
  3. PMID: 34606929
  4. View record in Web of Science®
  5. WOS: 000721610600020
  6. PII : S0923-7534(21)04495-1

Library Notes

  1. Fiscal Year: FY2021-2022
NCI at Frederick

You are leaving a government website.

This external link provides additional information that is consistent with the intended purpose of this site. The government cannot attest to the accuracy of a non-federal site.

Linking to a non-federal site does not constitute an endorsement by this institution or any of its employees of the sponsors or the information and products presented on the site. You will be subject to the destination site's privacy policy when you follow the link.

ContinueCancel