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Tumor Infiltrating Lymphocytes Signature as a New Pan-Cancer Predictive Biomarker of Anti PD-1/PD-L1 Efficacy.


ABSTRACT: Tumor immune infiltrates are associated with tumor prognosis in many cancer types. However, their capacity to predict the efficacy of checkpoint inhibitors is poorly documented. We generate three signatures that evaluate in different ways these infiltrates: lymphoid- and myeloid-alone signatures, and a combined signature of both named the TIL (tumor-infiltrating lymphocyte) transcriptomic signature. We evaluate these signatures in The Cancer Genome Atlas Program (TCGA) Pan-Cancer cohort and four cohorts comprising patients with melanoma, lung, and head and neck cancer treated with anti-PD-1 or anti-CTLA-4 therapies. We observe using TCGA Pan-Cancer cohort that this TIL or lymphoid-alone signature accurately estimates prognosis in most cancer types and outperforms histological TIL evaluation or myeloid signature alone. Both TIL and lymphoid signatures are correlated with response rate to immunotherapy. Combining lymphoid signature or TIL with tumor mutational burden generates a score that is highly efficient in predicting response to immunotherapy. In different series of patients treated with checkpoint inhibitors for non-small cell lung cancer, head and neck cancer, and melanoma, we observed that TIL or lymphoid signature were associated with outcome. These data demonstrate that a simple TIL or lymphoid signature could be used as a Pan-Cancer prognostic and predictive biomarker to estimate patient survival under checkpoint inhibitors.

SUBMITTER: Ballot E 

PROVIDER: S-EPMC7564481 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Tumor Infiltrating Lymphocytes Signature as a New Pan-Cancer Predictive Biomarker of Anti PD-1/PD-L1 Efficacy.

Ballot Elise E   Ladoire Sylvain S   Routy Bertrand B   Truntzer Caroline C   Ghiringhelli François F  

Cancers 20200826 9


Tumor immune infiltrates are associated with tumor prognosis in many cancer types. However, their capacity to predict the efficacy of checkpoint inhibitors is poorly documented. We generate three signatures that evaluate in different ways these infiltrates: lymphoid- and myeloid-alone signatures, and a combined signature of both named the TIL (tumor-infiltrating lymphocyte) transcriptomic signature. We evaluate these signatures in The Cancer Genome Atlas Program (TCGA) Pan-Cancer cohort and four  ...[more]

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