» Articles » PMID: 33736924

High Tumor Mutation Burden Fails to Predict Immune Checkpoint Blockade Response Across All Cancer Types

Overview
Journal Ann Oncol
Publisher Elsevier
Specialty Oncology
Date 2021 Mar 19
PMID 33736924
Citations 484
Authors
Affiliations
Soon will be listed here.
Abstract

Background: High tumor mutation burden (TMB-H) has been proposed as a predictive biomarker for response to immune checkpoint blockade (ICB), largely due to the potential for tumor mutations to generate immunogenic neoantigens. Despite recent pan-cancer approval of ICB treatment for any TMB-H tumor, as assessed by the targeted FoundationOne CDx assay in nine tumor types, the utility of this biomarker has not been fully demonstrated across all cancers.

Patients And Methods: Data from over 10 000 patient tumors included in The Cancer Genome Atlas were used to compare approaches to determine TMB and identify the correlation between predicted neoantigen load and CD8 T cells. Association of TMB with ICB treatment outcomes was analyzed by both objective response rates (ORRs, N = 1551) and overall survival (OS, N = 1936).

Results: In cancer types where CD8 T-cell levels positively correlated with neoantigen load, such as melanoma, lung, and bladder cancers, TMB-H tumors exhibited a 39.8% ORR to ICB [95% confidence interval (CI) 34.9-44.8], which was significantly higher than that observed in low TMB (TMB-L) tumors [odds ratio (OR) = 4.1, 95% CI 2.9-5.8, P < 2 × 10]. In cancer types that showed no relationship between CD8 T-cell levels and neoantigen load, such as breast cancer, prostate cancer, and glioma, TMB-H tumors failed to achieve a 20% ORR (ORR = 15.3%, 95% CI 9.2-23.4, P = 0.95), and exhibited a significantly lower ORR relative to TMB-L tumors (OR = 0.46, 95% CI 0.24-0.88, P = 0.02). Bulk ORRs were not significantly different between the two categories of tumors (P = 0.10) for patient cohorts assessed. Equivalent results were obtained by analyzing OS and by treating TMB as a continuous variable.

Conclusions: Our analysis failed to support application of TMB-H as a biomarker for treatment with ICB in all solid cancer types. Further tumor type-specific studies are warranted.

Citing Articles

Proteogenomic Profiling of Treatment-Naïve Metastatic Malignant Melanoma.

Kuras M, Betancourt L, Hong R, Szadai L, Rodriguez J, Horvatovich P Cancers (Basel). 2025; 17(5).

PMID: 40075679 PMC: 11899103. DOI: 10.3390/cancers17050832.


Comprehensive genetic variant analysis reveals combination of KRAS and LRP1B as a predictive biomarker of response to immunotherapy in patients with non-small cell lung cancer.

Eklund E, Svensson J, Naslund L, Yhr M, Sayin S, Wiel C J Exp Clin Cancer Res. 2025; 44(1):75.

PMID: 40011914 PMC: 11866712. DOI: 10.1186/s13046-025-03342-6.


Integration of multiple machine learning approaches develops a gene mutation-based classifier for accurate immunotherapy outcomes.

Shi R, Sun J, Zhou Z, Shi M, Wang X, Gao Z NPJ Precis Oncol. 2025; 9(1):54.

PMID: 40011681 PMC: 11865301. DOI: 10.1038/s41698-025-00842-8.


Exploration of the clonal evolution and construction of the tumor clonal evolution rate as a prognostic indicator in metastatic breast cancer.

Lv D, Lan B, Guo Q, Yi Z, Qian H, Guan Y BMC Med. 2025; 23(1):122.

PMID: 40001125 PMC: 11863457. DOI: 10.1186/s12916-025-03959-6.


Clinical metric of tumor mutational burden depicts colorectal cancer patients at the extremes.

Zheng M Clin Transl Oncol. 2025; .

PMID: 39984774 DOI: 10.1007/s12094-025-03873-6.


References
1.
Mariathasan S, Turley S, Nickles D, Castiglioni A, Yuen K, Wang Y . TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature. 2018; 554(7693):544-548. PMC: 6028240. DOI: 10.1038/nature25501. View

2.
Ellrott K, Bailey M, Saksena G, Covington K, Kandoth C, Stewart C . Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines. Cell Syst. 2018; 6(3):271-281.e7. PMC: 6075717. DOI: 10.1016/j.cels.2018.03.002. View

3.
Gubin M, Artyomov M, Mardis E, Schreiber R . Tumor neoantigens: building a framework for personalized cancer immunotherapy. J Clin Invest. 2015; 125(9):3413-21. PMC: 4588307. DOI: 10.1172/JCI80008. View

4.
Rooney M, Shukla S, Wu C, Getz G, Hacohen N . Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015; 160(1-2):48-61. PMC: 4856474. DOI: 10.1016/j.cell.2014.12.033. View

5.
Siegel R, Miller K, Jemal A . Cancer statistics, 2020. CA Cancer J Clin. 2020; 70(1):7-30. DOI: 10.3322/caac.21590. View