Analysis of the immune landscape in virus-induced cancers using a novel integrative mechanism discovery approach

Lindsay M Wong; Wei Tse Li; Neil Shende; Joseph C Tsai; Jiayan Ma; Jaideep Chakladar; Aditi Gnanasekar; Yuanhao Qu; Kypros Dereschuk; Jessica Wang-Rodriguez; Weg M Ongkeko

doi:10.1016/j.csbj.2021.11.013

Analysis of the immune landscape in virus-induced cancers using a novel integrative mechanism discovery approach

Comput Struct Biotechnol J. 2021 Nov 18:19:6240-6254. doi: 10.1016/j.csbj.2021.11.013. eCollection 2021.

Authors

Lindsay M Wong^{1

2}, Wei Tse Li^{1

2}, Neil Shende^{1

2}, Joseph C Tsai^{1

2}, Jiayan Ma^{1

2}, Jaideep Chakladar^{1

2}, Aditi Gnanasekar^{1

2}, Yuanhao Qu^{1

2}, Kypros Dereschuk^{1

2}, Jessica Wang-Rodriguez^{3

4}, Weg M Ongkeko^{1

2}

Affiliations

¹ Department of Surgery, Division of Otolaryngology-Head and Neck Surgery, University of California, San Diego, La Jolla, CA, 92093, USA.
² Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA.
³ Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA.
⁴ Pathology Service, VA San Diego Healthcare System, San Diego, CA 92161, USA.

Abstract

Background: The mechanisms of carcinogenesis from viral infections are extraordinarily complex and not well understood. Traditional methods of analyzing RNA-sequencing data may not be sufficient for unraveling complicated interactions between viruses and host cells. Using RNA and DNA-sequencing data from The Cancer Genome Atlas (TCGA), we aim to explore whether virus-induced tumors exhibit similar immune-associated (IA) dysregulations using a new algorithm we developed that focuses on the most important biological mechanisms involved in virus-induced cancers. Differential expression, survival correlation, and clinical variable correlations were used to identify the most clinically relevant IA genes dysregulated in 5 virus-induced cancers (HPV-induced head and neck squamous cell carcinoma, HPV-induced cervical cancer, EBV-induced stomach cancer, HBV-induced liver cancer, and HCV-induced liver cancer) after which a mechanistic approach was adopted to identify pathways implicated in IA gene dysregulation.

Results: Our results revealed that IA dysregulations vary with the cancer type and the virus type, but cytokine signaling pathways are dysregulated in all virus-induced cancers. Furthermore, we also found that important similarities exist between all 5 virus-induced cancers in dysregulated clinically relevant oncogenic signatures and IA pathways. Finally, we also discovered potential mechanisms for genomic alterations to induce IA gene dysregulations using our algorithm.

Conclusions: Our study offers a new approach to mechanism identification through integrating functional annotations and large-scale sequencing data, which may be invaluable to the discovery of new immunotherapy targets for virus-induced cancers.

Keywords: Algorithm; C2, Canonical pathway; C6, Oncogenic signature; C7, Immunological signature; CA, Cancer-associated; CESC, Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma; CNA, Copy number alteration; Cervical squamous cell carcinoma and endocervical adenocarcinoma; EBV, Epstein-Barr virus; Epstein-Barr virus; FDR, False discovery rate; GSEA, Gene set enrichment analysis; HBV, Hepatitis B virus; HCV, Hepatitis C virus; HNSCC, Head and Neck Squamous Cell Carcinoma; HPV, Human papillomavirus; Head and neck squamous cell carcinoma; Hepatitis B; Hepatitis C; Human papillomavirus; IA, Immune-associated; LIHC, Liver Hepatocellular Carcinoma; Liver hepatocellular carcinoma; MSigDB, Molecular Signature Database; STAD, Stomach Adenocarcinoma; Stomach adenocarcinoma; TCGA; TCGA, The Cancer Genome Atlas.