Nagar Hosseini - Genetic Division, Department of Biology, Faculty of Basic Science, Shahrekord Univeristy, Shahrekord, I.R.Iran
Marzieh Abolghasemi - Genetic Division, Department of Biology, Faculty of Basic Science, Shahrekord Univeristy, Shahrekord, I.R.Iran
Fatemeh Kheiri - Genetic Division, Department of Biology, Faculty of Basic Science, Shahrekord Univeristy, Shahrekord, I.R.Iran

Introduction & Objective: cancer is abnormal proliferation of cells in the body that can lead to death. The crutial role of growth factors in cancer progression has been demonstrated. Using microRNA-related mechanisms is one of the main regulalting genetic processes. These molecules are responsibe for regulating the expression of many genes. The aim of this study is to investigate the microRNAs that target on cancer-promoting growth factor genes and select the most effective microRNAs as a molecular biomarker to cancer diagnosis and treatment.Meterials & Methods: firstly, according to studies taken from articles and NCBI database, the major genes of growth factors were considered and ten genes (EGF, VGFFA, HGF, TGFB, EGFR, ERBB2, ERBB3, ERBB4, IGF1, IGF2) selected as well. Additionally, KEGG database used to consider the cancer pathway and selected genes. Afterwards, miRWalk, miRTarBase and miRDB databases were used to find microRNA that affect candidate genes and select microRNAs targeting more genes. It is worth to mention that each of these databases has different predictive algorithms. The data obtained from all these databases ,for all genes, was recorded in the excel file and ordered by the name of microRNA. Finally, after selecting appropriate microRNAs, in the phenomiR database, the rate of expression and efficacy of microRNAs role in cancer were evaluated.Results: the microRNAs binding to 3’UTR of genes were predicted by using algorithms of above-mentioned databases. Then, from the gained microRNAs, some cases that identified more genes or had more binding sites on a single gene were selected.Conclusion: Considering the bioinformatics studies, has-miR-133a-3p, has-miR-125a-5p and has-miR-205-5p have the highest score therefore they are the most suitable options for further investigation in practical analyses leading to inhibit cell proliferation.

microRNA, Growth Factors, Biomarker