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Tissue-specific thresholds of mutation burden associated with anti-PD-1/L1 therapy benefit and prognosis in microsatellite-stable cancers

Nature Cancer (2024)Cite this article

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Abstract

Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 or its ligand (PD-1/L1) have expanded the treatment landscape against cancers but are effective in only a subset of patients. Tumor mutation burden (TMB) is postulated to be a generic determinant of ICI-dependent tumor rejection. Here we describe the association between TMB and survival outcomes among microsatellite-stable cancers in a real-world clinicogenomic cohort consisting of 70,698 patients distributed across 27 histologies. TMB was associated with survival benefit or detriment depending on tissue and treatment context, with eight cancer types demonstrating a specific association between TMB and improved outcomes upon treatment with anti-PD-1/L1 therapies. Survival benefits were noted over a broad range of TMB cutoffs across cancer types, and a dose-dependent relationship between TMB and outcomes was observed in a subset of cancers. These results have implications for the use of cancer-agnostic and universal TMB cutoffs to guide the use of anti-PD-1/L1 therapies, and they underline the importance of tissue context in the development of ICI biomarkers.

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Fig. 1: Associations between TMB cutoffs and OS among ICI-treated and non-ICI-treated cohorts for different cancer types.
Fig. 2: Time on treatment and OS HRs of ICI-treated patients.
Fig. 3: Lowest absolute and percentile TMB thresholds with detectable survival benefit after treatment with ICIs.
Fig. 4: TME characteristics among TMB-H cancers across cancer types.

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Data availability

Data will be made available upon reasonable request with the permission of Caris Life Sciences. Raw sequencing data are owned by Caris Life Sciences and cannot be shared due to patient privacy and protected proprietary information. Access to aggregated data can be requested by contacting the corresponding author, including a brief description of the requirements and intended use. Requests will be discussed with the Caris data access team and a response given within 4 weeks. External datasets used in this study are available from the following public resources: gnomAD, gnomad.broadinstitute.org; International Genome Sample Resource (1000 Genomes Project), www.internationalgenome.org; dbSNP, www.ncbi.nlm.nih.gov/snp. Source data are provided with this paper.

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Acknowledgements

D.H. is supported by a Cancer Prevention and Research Institute of Texas Early Clinical Investigator Award (RP200549) and the Josephine Hughes Sterling Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper. D.S.B.H. is supported by the Dr. Miriam and Sheldon Adelson Medical Research Foundation. The remaining authors received no specific funding for this work.

Author information

Authors and Affiliations

  1. Division of Hematology and Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Maishara Muquith, Hao Zhu & David Hsiehchen

  2. Division of Digestive and Liver Diseases, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Magdalena Espinoza

  3. Caris Life Sciences, Phoenix, AZ, USA

    Andrew Elliott, Joanne Xiu, George W. Sledge & David Spetzler

  4. Department of Hematology and Oncology, Comprehensive Cancer Center Innsbruck, Medical University of Innsbruck, Innsbruck, Austria

    Andreas Seeber

  5. Laboratory of Translational Oncology and Experimental Cancer Therapeutics, Warren Alpert Medical School, Brown University, Providence, RI, USA

    Wafik El-Deiry

  6. Division of Hematology, Oncology and Transplantation, Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA

    Emmanuel S. Antonarakis

  7. Lifespan Cancer Institute, Legorreta Cancer Center, Brown University, Providence, RI, USA

    Stephanie L. Graff

  8. Department of Clinical Genetics, Fox Chase Cancer Center, Temple University Health System, Philadelphia, PA, USA

    Michael J. Hall

  9. Department of Hematology–Oncology, Fox Chase Cancer Center, Temple University Health System, Philadelphia, PA, USA

    Hossein Borghaei

  10. Department of Translational Molecular Medicine, Saint John’s Cancer Institute, Providence Saint John’s Health Center, Santa Monica, CA, USA

    Dave S. B. Hoon

  11. Division of Hematology and Oncology, Georgetown University, Washington, DC, USA

    Stephen V. Liu

  12. Penn State Cancer Institute, Hershey, PA, USA

    Patrick C. Ma

  13. Moores Cancer Center, University of California San Diego Health, La Jolla, CA, USA

    Rana R. McKay

  14. Division of Hematology and Oncology, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, USA

    Trisha Wise-Draper

  15. Ruesch Center for The Cure of Gastrointestinal Cancers, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA

    John Marshall

  16. Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Hao Zhu & David Hsiehchen

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  1. Maishara Muquith
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Contributions

D.H. and H.Z. conceptualized the study. M.M., M.E., A.E., J.X. and D.H. performed data analyses. A.S., W.E.-D., E.S.A., S.L.G., M.J.H., H.B., D.S.B.H., S.V.L., P.C.M., R.R.M., T.W.-D., J.M., G.W.S., D.S., H.Z. and D.H. contributed to the assembly of the CARIS cohort. M.M. and D.H. drafted the paper, and all authors participated in the review and editing of the paper.

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Correspondence to David Hsiehchen.

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Competing interests

A.E., J.X., G.W.S. and D.S. are employees of Caris Life Sciences. S.L.G. serves a paid consultant and advisor to Pfizer, Daiichi Sankyo, Eli Lilly, AstraZeneca, Genentech, SeaGen, Novartis and Menarini and has stock ownership in HCA Healthcare. E.S.A. serves as a paid consultant and advisor to Janssen, Astellas, Sanofi, Dendreon, Bayer, BMS, Amgen, Constellation, Blue Earth, Exact Sciences, Invitae, Curium, Pfizer, Merck, AstraZeneca, Clovis and Eli Lilly; has received research support (to his institution) from Janssen, J&J, Sanofi, BMS, Pfizer, AstraZeneca, Novartis, Curium, Constellation, Celgene, Merck, Bayer and Clovis; and is the co-inventor of a patented AR-V7 biomarker technology that has been licensed to Qiagen. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 TMB cutoffs associated with ICI benefit retain predictive value across demographics.

Subset analyses of patients stratified by age groups and self-reported sex show that the association between TMB cutoffs and outcomes are similar across demographics. Forest plots depict hazard ratios (squares) and error bars indicate 95% confidence intervals.

Source data

Extended Data Fig. 2 Associations between overall survival and TMB at the 75th percentile for individual cancer types are independent of the sequencing platform used.

Hazard ratios of overall survival in the ICI cohort using a TMB threshold at the 75th percentile for individual cancer types were separately calculated for cases analyzed by the 592-gene panel or exome sequencing. Forest plots depict hazard ratios (squares) and error bars indicate 95% confidence intervals.

Source data

Extended Data Fig. 3 Immune correlates between TMB-high and TMB-low cancers using the earliest cutoff at which ICIs are predictive.

PD-L1 positive cell frequency, T-cell inflammatory score, and CD8 + T cell frequency are compared between TMB-high cancers and TMB-low cancers using the earliest cutoff at which ICIs are associated with OS benefit. Biomarkers enriched in TMB-high and TMB-low cancers using a false discovery rate of 0.05 are highlighted.

Source data

Supplementary information

Supplementary Information

Supplementary Tables 1 and 2.

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Muquith, M., Espinoza, M., Elliott, A. et al. Tissue-specific thresholds of mutation burden associated with anti-PD-1/L1 therapy benefit and prognosis in microsatellite-stable cancers. Nat Cancer (2024). https://doi.org/10.1038/s43018-024-00752-x

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