A bioinformatics analysis of potential sifted biomarkers related to COL1A1 in Hepatocellular carcinoma (HCC)

A bioinformatics analysis of potential sifted biomarkers related to COL1A1 in Hepatocellular carcinoma (HCC)
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, the most commonly occurred liver cancer and froth fatal cancer globally has different risk factors including hepatitis B and C viral infection, cirrhosis, hereditary metabolic diseases and alcoholism. The precise molecular progress and tumor development is still not clear; therefore, bioinformatics analysis and related studies with HCC related gene, gene coded protein interactions, gene coding mRNAs, microRNAs(miRs) and long noncoding RNAs (lncRNAs) could suggest probable novel biomarkers leading to an early stage diagnosis and treatment.
Methods: By the help of bioinformatics database and in silico studies, after the extraction of genomic expression in both tumor and normal liver tissue and then analyzing it, one genes were selected by pathway recognition and at last, two microRNAs (miRs) along with their four competitor long non-codding RNAs (lncRNA), were sifted and studied for oncogene and tumor suppressor function identification. The route began with selection and analysis of GSE102079 form the Gene Expression Omnibus (GEO) with GEO2R for differentially expressed genes’ (DEGs) selection and identification. Enriched functional-related gene groups and related pathways, were analyzed by Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) in DAVID database. protein-protein interaction network (PPIN), was constructed using STRING. As for miR seed matching, potential SNPs of COL1A1, were applied in mirdSNP. LncBase v.2 was used in order to select appropriate lncRNAs, and NONCODE for expression evaluation in liver and HEPG2 cell lines.
Results: From the suggested biological pathways, contributed genetic related factors in HCC and elected COL1A1, were obtained. Two miRs including has-mir-29a and has-mir-129 were selected with a zero distanced SNP. A total of 3 different miR related lncRNAs, were identified which showed different expression rate in both liver and HEPG2 cell lines. has-mir-129-5p includes two related lncRNAs, NONHSAT075477.2 and NONHSAT017523.2. has-mir-29a-5p’s competitor is NONHSAT017523.2 and has-mir-29a-3p’s is NONHSAT017474.2. In HCC, has-mir-129-5p and has-mir-29a-5p downregulate in contrast with their lncRNAs, but has-mir-29a-3p upregulates although its’ lncRNA downregulates.
Conclusion: In other researches, COL1A1 is counted oncogene which its upregulation causes metastasis and withstand to anticancer therapy in HCC. We suggest that all miRs except has-mir-29a-3p are tumor suppressors versus their lncRNAs that are likely oncolnc. To pinpoint that NONHSAT017523.2 was common between two miRs, causing it to be a potential biomarker for both miR detection and HCC.
Keywords: Hepatocellular carcinoma, microRNA, lncRNA, bioinformatics, COL1A1