Published in:
01-01-2019 | Epidemiology
Immune receptor recombinations from breast cancer exome files, independently and in combination with specific HLA alleles, correlate with better survival rates
Authors:
Wei Lue Tong, Blake M. Callahan, Yaping N. Tu, Saif Zaman, Boris I. Chobrutskiy, George Blanck
Published in:
Breast Cancer Research and Treatment
|
Issue 1/2019
Login to get access
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.