Risha Patel – STAR Scholars Abstract – 2020 Identification of Viral Signatures in Hepatocellular Carcinoma
Transcriptomes Hepatocellular Carcinoma (HCC) is the most common type of liver cancer and makes up approximately 80% of known cases. HCC is often caused by viral infection, primarily Hepatitis B (HBV) and Hepatitis C (HCV); however, there is little known about their mechanisms and viral signatures. To address this gap in knowledge, we used bioinformatics tools to create and test a data analysis pipeline that identifies RNA transcripts and quantifies their expression relative to the human genome. In our study, we applied this pipeline to both a non-tumor liver tissue sample and an HCC liver tissue sample to produce a list of genes, including AKT1 and CHORDC1, that are differentially expressed within the two tissues. Previous studies have shown that AKT1 is upregulated in tumor liver tissue samples relative to non-tumor liver tissue samples and CHORDC1 is down-regulated, parallel to the results of our pipeline. This pipeline can be used to identify correlations between the genes expressed in HCC, while also being able to identify the expression of viral signatures. This can be accomplished by comparing the RNA to viral genomes, creating the potential to detect viral signatures of HBV and HCV in other cancers, and even other diseases.
Transcriptomes Hepatocellular Carcinoma (HCC) is the most common type of liver cancer and makes up approximately 80% of known cases. HCC is often caused by viral infection, primarily Hepatitis B (HBV) and Hepatitis C (HCV); however, there is little known about their mechanisms and viral signatures. To address this gap in knowledge, we used bioinformatics tools to create and test a data analysis pipeline that identifies RNA transcripts and quantifies their expression relative to the human genome. In our study, we applied this pipeline to both a non-tumor liver tissue sample and an HCC liver tissue sample to produce a list of genes, including AKT1 and CHORDC1, that are differentially expressed within the two tissues. Previous studies have shown that AKT1 is upregulated in tumor liver tissue samples relative to non-tumor liver tissue samples and CHORDC1 is down-regulated, parallel to the results of our pipeline. This pipeline can be used to identify correlations between the genes expressed in HCC, while also being able to identify the expression of viral signatures. This can be accomplished by comparing the RNA to viral genomes, creating the potential to detect viral signatures of HBV and HCV in other cancers, and even other diseases.