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Chemical complementarity between immune receptors and cancer mutants, independent of antigen presentation protein binding, is associated with increased survival rates

Uterine cancer has been associated with a T-cell immune response that leads to increased survival. Therefore, we used several bioinformatics approaches to explore specific interactions between T-cell receptor (TCR) and tumor mutant peptide sequences. Using endometrioid uterine cancer exome files fro...

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Detalles Bibliográficos
Autores principales: Hsiang, Monica, Chobrutskiy, Boris I., Diaz, Michael, Huda, Taha I., Creadore, Stefan, Zaman, Saif, Cios, Konrad J., Gozlan, Etienne C., Blanck, George
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Neoplasia Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8039726/
https://www.ncbi.nlm.nih.gov/pubmed/33780706
http://dx.doi.org/10.1016/j.tranon.2021.101069
Descripción
Sumario:Uterine cancer has been associated with a T-cell immune response that leads to increased survival. Therefore, we used several bioinformatics approaches to explore specific interactions between T-cell receptor (TCR) and tumor mutant peptide sequences. Using endometrioid uterine cancer exome files from the The Cancer Genome Atlas database, we obtained tumor resident V-J recombinations for the T-Cell Receptor alpha gene (TRA). The charged-based, chemical complementarity for each patient's LRP2 or TTN mutant amino acids (AAs) and the recovered, TRA complementarity determining region-3 (CDR3) sequences was calculated, allowing a division of patients into complementary and noncomplementary groups. Complementary groups with TTN mutants had increased disease-free survival and increased expression of complement genes. Furthermore, the survival distinction based on CDR3-mutant peptide complementarity was independent of programmatically assessed HLA class II binding and was not observable based on the CDR3 AA chemical features alone. The above approach provides a potential, highly efficient method for identifying TCR targets in uterine cancer and may aid in the development of novel prognostic tools.