1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Identification of peripheral blood mononuclear cell gene signatures for detection of hepatocellular carcinoma
Paper ID : 1226-ICB10
Authors:
ُSara Fayazzadeh1, Anna Meyfour *2, Javad Zahiri3
1Bioinformatics and Computational Omics Lab(BioCOOL), Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
2Basic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Center for Gastroenterology and Liver Diseases, Shahid Beheshti University, Tehran, Iran
3Department of Neurosciences, University of California, San Diego, CA, USA
Abstract:
Liver cancer is ranked sixth among the most frequently occurring cancers for both sexes worldwide in 2020 and the second leading cause of cancer deaths following lung cancer [1]. Hepatocellular carcinoma (HCC) is liver cancer's most common primary malignancy and accounts for ~90% of cases [2]. Currently available diagnostic methods for HCC exhibit a relatively moderate sensitivity of 60% [3], therefore introducing gene signatures for the disease diagnosis seems necessary. The gene expression profile of peripheral blood mononuclear cells (PBMCs) has shown an alteration in the case of malignancies such as different types of cancer [3]. In this study, we aim to detect the gene signatures of PBMCs that could distinguish HCC cases from healthy controls by analyzing multiple datasets retrieved from GEO database. Differentially expressed genes (DEGs) were determined using Limma package in R-4.1.0. A total of 11 genes, including 9 upregulated and 2 downregulated, were determined as DEGs based on the defined criteria. DAVID online tool was then utilized for enrichment analysis of DEGs. Several signaling pathways such as Toll-like receptor, NOD-like receptor, TNF signaling pathways, and pathways in cancer were enriched. These genes were also able to classify HCC from healthy controls with an accuracy of 93%. The results demonstrate PBMCs contain promising gene signatures that could shed light on the mechanism of the disease, leading to the introduction of a non-invasive diagnostic panel and/or therapeutic targets.
Keywords:
Hepatocellular carcinoma; Cancer; Microarray, Differential expression, DEG, Gene signature
Status : Paper Accepted (Oral Presentation)