期刊
BMC MEDICINE
卷 14, 期 -, 页码 -出版社
BMC
DOI: 10.1186/s12916-016-0705-4
关键词
Melanoma; Lung cancer; Total mutation load; CTLA-4; PD-1; Immunotherapy
资金
- Rising Stars Award, University of Texas System
- UT MD Anderson Cancer Center NCI SPORE in Melanoma [P50 CA093459]
- NIH National Cancer Institute (NCI) grant [T32 CA163185]
- NCI Grant [U01 CA180964]
- Khalifa Bin Zayed Al Nahyan Foundation
- NCATS grant [UL1 TR000371]
- University of Texas MD Anderson Cancer Center Support grant [NIH/NCI P30 CA016672]
- CPRIT [RP150405]
- Lung Cancer Moon Shot
- Dr. Miriam and Sheldon G. Adelson Medical Research Foundation
- Aim at Melanoma Foundation
- Miriam Research Fund
- Jim Mulva Research Fund
Background: While clinical outcomes following immunotherapy have shown an association with tumor mutation load using whole exome sequencing (WES), its clinical applicability is currently limited by cost and bioinformatics requirements. Methods: We developed a method to accurately derive the predicted total mutation load (PTML) within individual tumors from a small set of genes that can be used in clinical next generation sequencing (NGS) panels. PTML was derived from the actual total mutation load (ATML) of 575 distinct melanoma and lung cancer samples and validated using independent melanoma (n = 312) and lung cancer (n = 217) cohorts. The correlation of PTML status with clinical outcome, following distinct immunotherapies, was assessed using the Kaplan-Meier method. Results: PTML (derived from 170 genes) was highly correlated with ATML in cutaneous melanoma and lung adenocarcinoma validation cohorts (R-2 = 0.73 and R-2 = 0.82, respectively). PTML was strongly associated with clinical outcome to ipilimumab (anti-CTLA-4, three cohorts) and adoptive T-cell therapy (1 cohort) clinical outcome in melanoma. Clinical benefit from pembrolizumab (anti-PD-1) in lung cancer was also shown to significantly correlate with PTML status (log rank P value < 0.05 in all cohorts). Conclusions: The approach of using small NGS gene panels, already applied to guide employment of targeted therapies, may have utility in the personalized use of immunotherapy in cancer.
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