The pattern of gene copy number variations (CNVs) in hepatocellular carcinoma; in silico analysis

Author:

Shahrisa Arman1,Tahmaseby Maryam2,Ansari Hossein3,Mohammadi Zahra2,Carloni Vinicio4,Asl Javad Mohammadi2

Affiliation:

1. Tarbiat Modares University Faculty of Biological Sciences

2. Ahvaz Jondishapour University of Medical Sciences

3. Islamic Azad University

4. Florence University

Abstract

Abstract Recent studies showed that genetic lost or gain in the genome can predispose cells toward malignancy. Hepatocellular carcinoma (HCC) is the most common type of liver cancer which occurs predominantly in patients with underlying chronic liver disease and cirrhosis. Prognosis of HCC is strongly connected with diagnostic delay. To date, no ideal screening modality has been developed for HCC. Recent findings demonstrated that Copy number variation (CNVs) can lead to activation of oncogenes and inactivation of tumor suppressor genes in cancers. In this study, CNV profile of 361 HCC samples was evaluated to reveal the potent - chromosomal regions involved in the disease. The obtained data showed that the chr1q and chr8p were two hotspot regions for gene amplifications and deletions in studied samples respectively. In this research, YY1AP1 (Yin Yang-1 Associated Protein 1) on chr1q22 was the most amplified gene in HCC samples and showed the positive correlation with tumor grade. Deletion of CHMP7 (Charged Multivesicular Body Protein 7) on chr8p21.3 was another frequently observed CNV among HCC patients. Both genes were interacted with variety of well-known oncogenes and tumor suppressor genes including YY1 (Yin Yang 1), CCND1 (Cyclin D1), HDAC1 (Histone deacetylase 1), VHL (von Hippel-Lindau tumor suppressor), MAD2L2 (Mitotic Arrest Deficient 2 Like 2), CEBPA (CCAAT/enhancer-binding protein alpha), CHMP4A, CHMP5, CHMP2A, CHMP3 and ENSG00000249884 (RNF103-CHMP3 gene), all of them are well-known in carcinogenesis. Although this study was based on in silico evaluations, our findings can open a new window for researchers of HCC to focus on such candidate genes during experimental assays.

Publisher

Research Square Platform LLC

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The CNV Predict Model in Esophagus Cancer;Intelligent Computing Theories and Application;2022

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