Wei Lue Tong1, Blake M Callahan1, Yaping N Tu1, Saif Zaman1, Boris I Chobrutskiy1, George Blanck2,3. 1. Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA. 2. Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA. gblanck@health.usf.edu. 3. Department of Immunology, H. Lee Moffitt Cancer Center and Research Institute, 12901 Bruce B. Downs Blvd., Tampa, FL, 33612, USA. gblanck@health.usf.edu.
Abstract
PURPOSE: Immune characterizations of cancers, including breast cancer, have led to information useful for prognoses and are considered to be important in the future of refining the use of immunotherapies, including immune checkpoint inhibitor therapies. In this study, we sought to extend these characterizations with genomics approaches, particularly with cost-effective employment of exome files. METHODS: By recovery of immune receptor recombination reads from the cancer genome atlas (TCGA) breast cancer dataset, we observed associations of these recombinations with T-cell and B-cell biomarkers and with distinct survival rates. RESULTS: Recovery of TRD or IGH recombination reads was associated with an improved disease-free survival (p = 0.047 and 0.045, respectively). Determination of the HLA types using the exome files allowed matching of T-cell receptor V- and J-gene segment usage with specific HLA alleles, in turn allowing a refinement of the association of immune receptor recombination read recoveries with survival. For example, the TRBV7, HLA-C*07:01 combination represented a significantly worse, disease-free outcome (p = 0.014) compared to all other breast cancer samples. By direct comparisons of distinct TRB gene segment usage, HLA allele combinations revealed breast cancer subgroups, within the entire TCGA breast cancer dataset with even more dramatic survival distinctions. CONCLUSIONS: In sum, the use of exome files for recovery of adaptive immune receptor recombination reads, and the simultaneous determination of HLA types, has the potential of advancing the use of immunogenomics for immune characterization of breast tumor samples.
PURPOSE: Immune characterizations of cancers, including breast cancer, have led to information useful for prognoses and are considered to be important in the future of refining the use of immunotherapies, including immune checkpoint inhibitor therapies. In this study, we sought to extend these characterizations with genomics approaches, particularly with cost-effective employment of exome files. METHODS: By recovery of immune receptor recombination reads from the cancer genome atlas (TCGA) breast cancer dataset, we observed associations of these recombinations with T-cell and B-cell biomarkers and with distinct survival rates. RESULTS: Recovery of TRD or IGH recombination reads was associated with an improved disease-free survival (p = 0.047 and 0.045, respectively). Determination of the HLA types using the exome files allowed matching of T-cell receptor V- and J-gene segment usage with specific HLA alleles, in turn allowing a refinement of the association of immune receptor recombination read recoveries with survival. For example, the TRBV7, HLA-C*07:01 combination represented a significantly worse, disease-free outcome (p = 0.014) compared to all other breast cancer samples. By direct comparisons of distinct TRB gene segment usage, HLA allele combinations revealed breast cancer subgroups, within the entire TCGA breast cancer dataset with even more dramatic survival distinctions. CONCLUSIONS: In sum, the use of exome files for recovery of adaptive immune receptor recombination reads, and the simultaneous determination of HLA types, has the potential of advancing the use of immunogenomics for immune characterization of breast tumor samples.
Entities:
Keywords:
Breast cancer; HLA alleles; Immune receptor recombinations; V- and J-gene segment usage
Authors: Andrea Chobrutskiy; Boris I Chobrutskiy; Saif Zaman; Monica Hsiang; George Blanck Journal: Breast Cancer Res Treat Date: 2020-11-12 Impact factor: 4.872
Authors: Brooke E Mcbreairty; Boris I Chobrutskiy; Andrea Chobrutskiy; Etienne C Gozlan; Michael J Diaz; George Blanck Journal: Biomed Rep Date: 2022-06-09
Authors: Boris I Chobrutskiy; Michelle Yeagley; Andrea Diviney; Saif Zaman; Etienne C Gozlan; Price Tipping; Darush M Koohestani; Andrea M Roca; George Blanck Journal: Immunology Date: 2020-01-21 Impact factor: 7.397