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It has recently become apparent that it is possible to characterize productively recombined, T-cell receptor (TcR) gene segments in tumor exome files, which presumably include representations of the DNA of other cells in the microenvironment. Similar characterizations have been done for TcR recombinations in tumor specimen RNASeq files. While exome files have been used to characterize immunoglobulin gene segment recombinations for tumors closely related to B-cells, immunoglobulin recombinations have yet to be characterized for putative microenvironment cells for solid tumors. Here we report a novel scripted algorithm that detects productive and unproductive immunoglobulin recombinations in both B-cell related tumor exome files and in solid tumor exome files, with the most important result being the relatively high level B-cell infiltrate in breast cancer. This analysis has the potential of streamlining and dramatically augmenting the knowledge base regarding B-cell infiltrates into solid tumors; and leading to antibody reagents directed against tumor antigens and tissue resident, infectious pathogens.

Understanding tumor-resident T cells is important for cancer prognosis and treatment options. Conventional, solid tumor specimen exome files can be searched directly for recombined T cell receptor (TcR)-α segments; RNASeq files can include TcR-β VDJ recombinations. To learn whether there are medically relevant uses of exome-based detection of TcR V(D)J recombinations in the tumor microenvironment, we searched cancer genome atlas and Moffitt Cancer Center, tumor specimen exome files for TcR-β, TcR-γ, and TcR-δ recombinations, for bladder and stomach cancer. We found that bladder cancer exomes with productive TcR-β recombinations had a significant association with No Subsequent Tumors and a positive response to drug treatments, with p < 0.004, p < 0.05, and p < 0.004, depending on the sample sets examined. We also discovered the opportunity to detect productive TcR-γ and TcR-δ recombinations in the tumor microenvironment, via the tumor specimen exome files.