Abstract
BackgroundWhile 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.MethodsWe 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.ResultsPTML (derived from 170 genes) was highly correlated with ATML in cutaneous melanoma and lung adenocarcinoma validation cohorts (R2 = 0.73 and R2 = 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).ConclusionsThe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-016-0705-4) contains supplementary material, which is available to authorized users.
Highlights
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
Derivation of predicted total mutation load (PTML) in melanoma and lung cancer samples We sought to determine if mutations identified within a small, defined set of genes could be utilized to accurately predict the total mutation burden determined by WES
Analysis of two independent cohorts of lung cancer samples (n = 217) [15, 16] that had undergone WES demonstrated a strong correlation between the lung cancer PTML and the actual total mutation load (ATML) of these validation cohorts (R2 = 0.81, Fig. 1b)
Summary
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. There is a strong impetus to personalize the care of cancer patients to deliver selective therapies. One way this is being done clinically is by performing nextgeneration sequencing (NGS) on panels of cancerrelated genes to identify targeted therapy approaches to which patients are most likely to respond. The development of a method to accurately estimate total mutation load from widely available NGS gene panels could further personalize the care of cancer patients by improving patient selection for immune-based therapies. Several cohorts of patients were used to determine the accuracy of PTML, and to assess its association with clinical outcomes in melanoma and lung cancer patients treated with immunotherapies
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