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Predicting the spectrum of TCR repertoire sharing with a data-driven model of recombination


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      Despite the extreme diversity of T cell repertoires, many identical T-cell receptor (TCR) sequences are found in a large number of individual mice and humans. These widely-shared sequences, often referred to as `public', have been suggested to be over-represented due to their potential immune functionality or their ease of generation by V(D)J recombination. Here we show that even for large cohorts the observed degree of sharing of TCR sequences between individuals is well predicted by a model accounting for by the known quantitative statistical biases in the generation process, together with a simple model of thymic selection. Whether a sequence is shared by many individuals is predicted to depend on the number of queried individuals and the sampling depth, as well as on the sequence itself, in agreement with the data. We introduce the degree of publicness conditional on the queried cohort size and the size of the sampled repertoires. Based on these observations we propose a public/private sequence classifier, `PUBLIC' (Public Universal Binary Likelihood Inference Classifier), based on the generation probability, which performs very well even for small cohort sizes.

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      Landscape of tumor-infiltrating T cell repertoire of human cancers

      We developed a computational method to infer the complementarity determining region 3 (CDR3) sequences of tumor infiltrating T-cells in 9,142 RNA-seq samples across 29 cancer types. We identified over 600 thousand CDR3 sequences, including 15% with full-length. 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 observed a strong association between T-cell diversity and tumor mutation load, and predicted SPAG5 and TSSK6 as putative immunogenic cancer/testis antigens in multiple cancers. Finally, we identified 3 potential immunogenic somatic mutations based on their co-occurrence with CDR3 sequences. One of them, PRAMEF4 F300V, was predicted to bind strongly to both MHC-I and MHC-II, with matched HLA types in its carriers. Our analyses have the potential to simultaneously identify immunogenic neoantigens and the tumor-reactive T-cell clonotypes.

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        02 March 2018

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