journal contribution
posted on 2023-03-31, 02:04 authored by Frederick S. Varn, Evelien Schaafsma, Yue Wang, Chao Cheng Supplementary Figure S1: Differences in immune signature enrichment scores between virus-infected and non-infected samples. Supplementary Figure S2: Differences in the expression of HLA genes between HBV-positive and HBV-negative LIHC patients. Supplementary Figure S3: Differences in non-silent mutation burden between virus-infected and non-infected samples. Supplementary Figure S4: Differences in TCR read abundance between virus-infected and non-infected cancer patients. Supplementary Figure S5: Performance of the virus infection gene expression signature in four HNSC datasets. Supplementary Figure S6: Survival meta-analysis of the virus infection gene expression signature in six cancer types. Supplementary Figure S7: Differences in MKI67 gene expression and ESTIMATE immune scores between HPV-positive and HPV-negative HNSC patients.
Funding
National Institutes of Health
National Center for Advancing Translational Sciences
Geisel School of Medicine at Dartmouth
History
ARTICLE ABSTRACT
Viruses affect approximately 20% of all human cancers and induce expression of immunogenic viral oncoproteins that make these tumors potent targets for immune checkpoint inhibitors. In this study, we apply computational tools to The Cancer Genome Atlas (TCGA) and other genomic datasets to define how virus infection shapes the tumor immune microenvironment and genetic architecture of 6 virus-associated tumor types. Across cancers, the cellular composition of the microenvironment varied by viral status, with virus-positive tumors often exhibiting increased infiltration of cytolytic cell types compared with their virus-negative counterparts. Analyses of the infiltrating T-cell receptor repertoire in these patients revealed that Epstein–Barr virus infection was associated with decreased receptor diversity in multiple cancers, suggesting an antigen-driven clonal T-cell response. Tissue-specific gene-expression signatures capturing virus-associated transcriptomic changes successfully predicted virus status in independent datasets and were associated with both immune- and proliferation-related features that were predictive of patient prognosis. Together, the analyses presented suggest viruses have distinct effects in different tumors, with implications for immunotherapy.Significance: This study utilizes TCGA and other genomic datasets to further our understanding of how viruses affect the tumor immune response in different cancer types.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/22/6413/F1.large.jpg. Cancer Res; 78(22); 6413–23. ©2018 AACR.
