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Inference of Tumor Immunity and T-cell Receptor Repertoire from TCGA RNA-seq Data
We developed a computational approach to study tumor-infiltrating immune cells and their interactions with cancer cells. Analysis of over ten thousand RNA-seq samples from the Cancer Genome Atlas (TCGA) identified strong association between immune infiltrates and patient clinical features, viral infection status, and cancer genetic alterations. We found that melanomas with high levels of CTLA4 as well as kidney tumors with high TIM3 separate into two distinct groups with respect to CD8 T-cell infiltration. We also developed a computational method to infer the complementarity determining region 3 (CDR3) sequences of tumor infiltrating T-cells in TCGA RNA-seq samples. CDR3 sequence length distribution and amino acid conservation, as well as variable gene usage of infiltrating T-cells in many tumors, except brain and kidney cancers, resembled those in the peripheral blood of healthy donors. We identified 3 potential immunogenic somatic mutations based on their co-occurrence with CDR3 sequences. The analysis of immune infiltrates and T-cell receptor repertoire might lead to useful insights on the clinical responses to immune checkpoint blockade.