Silencing lung cancer genes using miRNAs identified by 7mer-seed matching. (June 2021)

• Record Type: Journal Article
• Authors: Chakraborty, Supriyo; Nath, Durbba; Barbhuiya, Parvin A; Choudhury, Yashmin; Uddin, Arif
• Is Part Of: Computational biology and chemistry. Volume 92(2021)
• Publication Date: 2021-06
• Subjects: Small cell lung cancer -- Non small cell lung cancer -- microRNA -- Overexpressed genes; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2021.107483
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Screening analysis revealed a few lung cancer genes had numerous miRNA binding sites. Free energy of mRNAs revealed their compact structure caused complexity in miRNA binding. GC content in target sites was relatively higher than that in flanks. Cosm and compAI suggested lung cancer genes withnon optimal codons were translationally less efficient. Gene ontology unveiled the diverse functionalities of 12 genes. Abstract: Lung cancer (LC) is the main cause of cancer-associated deaths in both men and women globally with a very high mortality rate. The microRNAs (miRNAs) are a class of noncoding RNAs consisting of 18–25 nucleotides. They inhibit translation of protein through binding to complementary target mRNAs. The non-coding miRNAs are recognized as potent biomarkers for detection, development and treatment of malignancy. In this study, we screened a set of 12 genes over expressed in small cell lung cancer, non small cell lung cancer and the genes involved in both categories and their binding sites for human miRNAs as no work was reported yet. Screening of human miRNAs revealed that a few genes showed numerous miRNA binding sites. Free energy values of mRNA sequences revealed that they might acquire compact folded structure causing complexity for miRNAs to interact. GC content in the target site was relatively higher than that of their flanks. It was observed through analysis of cosine similarity metric and compAI parameters that the genes related to lung cancer were encoded with non optimal codons and thus might be translationally less efficient for producing polypeptides. Gene ontology analysis was carried out to understand the diverse functions of these 12 genes.