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Omicsoft is the leading provider of Next Generation Sequencing, Cancer Genomics, Immunology, and Bioinformatics solutions for Next Generation Sequencing Data and Gene Expression Analysis.

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Keeping you up-to-date with the latest in NGS, Bioinformatics Analysis, and cancer genomics with blogs on Array Suite, OncoLand (TCGA and more), ImmunoLand, and more.

[Oncology Research] Oncovirus: Tumor-Virus Association

Vivian Zhang

The tumor-virus associations are known in many types of cancer, including Human papillomavirus (HPV) head-and-neck squamous cell carcinoma, Hepatitis B virus in hepatocellular carcinoma and Epstein-Barr virus (EBV) in gastric carcinoma tumors (1,2). Infection with the hepatitis B virus has been linked to the development of hepatocellular carcinoma. HBV-induced chronic active hepatitis (CAH) and cirrhosis are important risk factors in liver carcinogenesis (3). The detection capacity and sensitivity of RNA-Seq allow researchers to study this association across human genome.

The Cancer Genome Atlas (TCGA) provides viral sequences generated by RNA-Seq. OncoLand, with its integration analysis capacity among mutation, gene expression and structural variation data, provides easy and fast approaches to examine the virus-gene expression association in tumor samples.

OncoLand provides virus sequence count data from more than 4000 GeneBank IDs that were generated by TCGA. In OncoLand, it’s easy to show viral count (expression) per sample. It is clear that Hepatitis B virus is highly expressed in Liver Hepatocellular Carcinoma (LIHC): 

To investigate the single gene-Hepatitis B virus association, OncoLand enables user to create cohorts with user-defined high and low virus counts through creation of SampleSet=>Group SampleSet from Selection: 

With cohorts annotated by high and low virus count, Integration Analysis provides a Kruskal–Wallis test to compare the gene expression between high and low viral cohorts across the rest of the genome. Users could examine one individual gene, a list of molecular signatures of interest or all genes by specifying a Gene Set: 

The result provides statistical results, including gene expression levels in different cohorts:

The user can export the results to Array Studio for further analysis, focus in on a gene or genes of interest for further validation of the association, or export the results to excel for reporting. Tumor-related genes could be good candidates for explaining the molecular viral oncology mechanism and for cancer drug discovery. 

 

 

REFERENCE

1.     Khoury, Joseph D., et al. The landscape of DNA virus associations across human malignant cancers using RNA-Seq: an analysis of 3775 cases. Journal of virology (2013): JVI-00340.

2.     Di Bisceglie, Adrian M. Hepatitis B and hepatocellular carcinoma. Hepatology49.S5 (2009): S56-S60.

3.       Kremsdorf, D., et al. Hepatitis B virus-related hepatocellular carcinoma: paradigms for viral-related human carcinogenesis. Oncogene 25.27 (2006): 3823-3833.