Document Type
Article
Publication Date
2016
Keywords
the cancer genome atlas, TCGA, T-cell receptor rearrangement, exome, breast cancer, bladder cancer
Digital Object Identifier (DOI)
https://doi.org/10.4137/CIN.S35784
Abstract
Tumor immunoscoring is rapidly becoming a universal parameter of prognosis, and T-cells isolated from tumor masses are used for ex vivo amplification and readministration to patients to facilitate an antitumor immune response. We recently exploited the cancer genome atlas (TCGA) RNASeq data to assess T-cell receptor (TcR) expression and, in particular, discovered strong correlations between major histocompatibility class II (MHCII) and TcR-α constant region expression levels. In this article, we describe the results of searching TCGA exome files for TcR-α V-regions, followed by searching the V-region datasets for TcR-α-J regions. Both primary and metastatic breast cancer sample files contained recombined TcR-α V-J regions, ranging in read counts from 16–39, at the higher level. Among four such V-J rearrangements, three were productive rearrangements. Rearranged TcR-α V–J regions were also detected in TCGA–bladder cancer, -lung cancer, and -ovarian cancer datasets, as well as exome files representing bladder cancer, in Moffitt Cancer Center patients. These results suggest that a direct search of commonly available, conventional exome files for rearranged TcR segments could play a role in more sophisticated immunoscoring or in identifying particular T-cell clones and TcRs directed against tumor antigens.
Rights Information
This work is licensed under a Creative Commons Attribution 3.0 License.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Cancer Informatics, v. 15, p. 23-28
Scholar Commons Citation
Gill, Thomas R.; Samy, Mohammad D.; Butler, Shanitra N.; Mauro, James A.; Sexton, Wade J.; and Blanck, George, "Detection of Productively Rearranged TcR-α V–J Sequences in TCGA Exome Files: Implications for Tumor Immunoscoring and Recovery of Antitumor T-cells" (2016). Molecular Medicine Faculty Publications. 30.
https://digitalcommons.usf.edu/mme_facpub/30
