Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.
Department of Immunology, H. Lee Moffitt Cancer Center and Research Institute, 12901 Bruce B. Downs Blvd., Tampa, FL, 33612, USA.
Breast Cancer Res Treat. 2019 Jan;173(1):167-177. doi: 10.1007/s10549-018-4961-1. Epub 2018 Sep 18.
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.
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.
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.
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.
对癌症(包括乳腺癌)的免疫特征进行分析,为预后提供了有用的信息,并且被认为在未来对免疫疗法(包括免疫检查点抑制剂疗法)的应用具有重要意义。在这项研究中,我们试图通过基因组学方法进一步对这些特征进行分析,特别是通过经济有效地利用外显子组文件。
通过从癌症基因组图谱(TCGA)乳腺癌数据集恢复免疫受体重组读取,我们观察到这些重组与 T 细胞和 B 细胞生物标志物以及不同的生存率之间存在关联。
TRD 或 IGH 重组读取的恢复与无病生存率的改善相关(p=0.047 和 0.045)。使用外显子组文件确定 HLA 类型,使 T 细胞受体 V 和 J 基因片段的使用与特定 HLA 等位基因相匹配,从而可以进一步确定免疫受体重组读取的恢复与生存率的关联。例如,TRBV7 和 HLA-C*07:01 组合与所有其他乳腺癌样本相比,无病结果显著更差(p=0.014)。通过直接比较不同的 TRB 基因片段的使用,HLA 等位基因组合揭示了 TCGA 乳腺癌数据集内的乳腺癌亚组,具有更显著的生存差异。
总之,使用外显子组文件恢复适应性免疫受体重组读取,并同时确定 HLA 类型,有可能推进免疫基因组学在乳腺癌肿瘤样本免疫特征分析中的应用。