• A bioinformatics analysis of potential differentially regulated biomarkers in hepatocellular carcinoma (HCC) related gene COL4A1
  • Maryam Abbasi,1 Fatemeh Baghban,2 Shadi Omidghaemi,3 Mansoureh Azadeh,4,*
    1. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran
    2. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran
    3. Isfahan province, Isfahan, Hezar Jerib Avenue, Kargar Avenue, Esfahan Technical and Vocational Training Organization, Department of Biotechnology
    4. Isfahan province, Isfahan, Hezar Jerib Avenue, Kargar Avenue, Esfahan Technical and Vocational Training Organization, Department of Biotechnology


  • Introduction: Hepatocellular carcinoma (HCC), one of the top ranked occurring cancers worldwide, could emerge because of hereditary background related metabolic diseases, cirrhosis, chronic hepatitis B and C (HBV and HCV) and viral infection. They lead to heterogeneous tumors diverging from different molecular factors and pathways, requiring vast inquiry for early diagnosis, biomarker detection and disease progress route and treatment; therefore, with bioinformatics and and in silico studies, precise mechanism and development of HCC, which still is unclear, could be identified. In this study, biological biomarker including micoRNAs (miRs) and long non-coding RNAs (lncRNAs) related to one of the top HCC associated pathways and significantly differential expressed genes from the collagen family, collagen type IV alpha 1(COL4A1), were perused.
  • Methods: The process began with selection and then analysis of GSE102079’s extracted data form the Gene Expression Omnibus (GEO) with GEO2R for differentially expressed genes’ (DEGs) purpose. Afterwards, functional-related gene groups with the same regulations and their related pathways, were enriched and analyzed by Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) in DAVID database. protein-protein interaction (PPI) network, for further evaluation, was erected using STRING. For miR seed matching, potential SNPs with zero distance of COL4A1 was applied in mirdSNP. LncBase v.2 was used in purpose of appropriate lncRNAs selection. At last, NONCODE was used for lncRNAs expression evaluation in both liver and HEPG2 cell lines.
  • Results: One has-mir-205 was elected and ten lncRNAs were identified as a competitor for both 3p and 5p has-mir-205. For has-mir-205-5p NONHSAT077300.2, NONHSAT017523.2, NONHSAT142243.2, NONHSAT021488.2, NONHSAT041650.2 and NONHSAT058723.2 were identified. As for has-mir-205-3p NONHSAT192799.1, NONHSAT017523.2, NONHSAT192676.1 and NONHSAT041374.2 were recognized. Both has-mir-205-3p and has-mir-5p were downregulated in HCC in contrast with all the lncRNAs, except for NONHSAT041374.2, which were upregulated. NONHSAT017523.2 was common in two miRs and the other notable things are presence of NONHSAT021488.2 only in liver and significant and specific upregulation in HepG2 cell lines. To note that all lncRNAs, showed differentiation in both liver expression and HEPG2 cell lines’ expression.
  • Conclusion: Other studies show that COL4A1 is oncogene with the most upregulation out of 44 members of collagen family, which facilitates metastasis, causes more cell growth and leads to an advanced liver cancer. A competing endogenous RNAs network with mRNA, a lncRNA-miR-mRNA network, could affect drug resistance and cancer progress. miRs and possibly lncRNAs, will make fine biomarkers for a better diagnosis. With these interpretations, we suggest that has-mir-205 is a tumor suppressor and nine out of ten lncRNAs are probably onco-lncs (NONHSAT041374.2 is probably tumor suppressor. The common NONHSAT017523.2, would be a good biomarker for detecting more than one type of miRs (has-mir-205-3p and has-mir-205-5p). We also note that NONHSAT021488.2 is potentially a remarkable biomarker, because of its only and specific expression in liver.
  • Keywords: Hepatocellular carcinoma, microRNA, lncRNA, bioinformatics, COL4A1