Abstract

BackgroundUnderstanding the interactions between tumor and the host immune system is critical to finding prognostic biomarkers, reducing drug resistance, and developing new therapies. Novel computational methods are needed to estimate tumor-infiltrating immune cells and understand tumor–immune interactions in cancers.ResultsWe analyze tumor-infiltrating immune cells in over 10,000 RNA-seq samples across 23 cancer types from The Cancer Genome Atlas (TCGA). Our computationally inferred immune infiltrates associate much more strongly with patient clinical features, viral infection status, and cancer genetic alterations than other computational approaches. Analysis of cancer/testis antigen expression and CD8 T-cell abundance suggests that MAGEA3 is a potential immune target in melanoma, but not in non-small cell lung cancer, and implicates SPAG5 as an alternative cancer vaccine target in multiple cancers. We find that melanomas expressing high levels of CTLA4 separate into two distinct groups with respect to CD8 T-cell infiltration, which might influence clinical responses to anti-CTLA4 agents. We observe similar dichotomy of TIM3 expression with respect to CD8 T cells in kidney cancer and validate it experimentally. The abundance of immune infiltration, together with our downstream analyses and findings, are accessible through TIMER, a public resource at http://cistrome.org/TIMER.ConclusionsWe develop a computational approach to study tumor-infiltrating immune cells and their interactions with cancer cells. Our resource of immune-infiltrate levels, clinical associations, as well as predicted therapeutic markers may inform effective cancer vaccine and checkpoint blockade therapies.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1028-7) contains supplementary material, which is available to authorized users.

Highlights

  • Understanding the interactions between tumor and the host immune system is critical to finding prognostic biomarkers, reducing drug resistance, and developing new therapies

  • Clinical relevance of tumor immune infiltration To study the distribution of infiltrating immune cells in the tumor and adjacent/normal tissues, we focused on 18 cancer types for which the mRNA expression profiles of adjacent or normal tissues were available

  • Among the remaining three The Cancer Genome Atlas (TCGA) cancers with available microsatellite instability (MSI) information, we found higher levels of MSI to be associated with increased CD8 T cells in stomach cancer

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Summary

Introduction

Understanding the interactions between tumor and the host immune system is critical to finding prognostic biomarkers, reducing drug resistance, and developing new therapies. Novel computational methods are needed to estimate tumor-infiltrating immune cells and understand tumor–immune interactions in cancers. Rooney et al [6] studied cytolytic activity (CYT) using the expression levels of two effector molecules and identified possible mechanisms of immune evasion. Our estimates of tumor-infiltrating immune cells were validated using multiple approaches, including in silico simulation, comparison with orthogonal inferences, and a pathological approach. Our in silico inferences and associated findings have been packaged into a web-accessible resource, TIMER (Tumor IMmune Estimation Resource), to enable further explorations of the disease-specific clinical impact of different immune infiltrates in the tumor microenvironment

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