ML‐Based Screening of miRNA Inhibitors and Intervention of lncRNA/miRNA/mRNA Axis in Oncogenic KRAS‐Associated Colorectal Cancer

Mutant KRAS promotes proliferation and tumorigenesis in several cancers such as colorectal cancer (CRC), pancreatic ductal adenocarcinoma (PDAC), and non-small cell lung cancer (NSCLC). The long noncoding RNAs (lncRNAs) regulate the microRNAs (miRNAs) that further result in the dysregulation of messenger RNAs (mRNAs) in various mutant KRAS-associated cancers. Although the role and function of the lncRNA axis are not clearly understood, various studies have recently focussed on the evaluation of the lncRNA axis role in various cancers. The lncRNAs CRNDE and SNHG7 are highly expressed in KRAS-associated colon adenocarcinoma (COAD), a major subtype of CRC, and further regulate the miRNA expression and thus indirectly regulate mRNA expression levels. In the present study, we have utilized various bioinformatics approaches such as differential gene expression (DEG) analysis, survival analysis, immunohistochemistry (IHC) analysis, prediction of RNA-RNA interaction, miRNA and mRNA stability prediction, and binding energy evaluation. Alongside, machine learning (ML)-based screening was also performed to identify potential miRNA inhibitors from natural source using RDKit. From our study, we have observed that CRNDE sponges hsa-miR-181a-5p and downregulates their expression, and the hsa-miR-181a-5p further regulates the expression of CTNNB1 and TCF4 in COAD. Also, in the lncRNA SNHG7 axis, it regulates the hsa-miR-216b-5p expression, and further, the GALNT1 was downregulated by the binding of hsa-miR-216b-5p. Additionally, ML-based screening revealed some potential inhibitors particularly based on anthraquinone, quinazoline, and sulfonamide scaffolds against hsa-miR-216b-5p and hsa-miR-216b-5p. Thus, we conclude that the lncRNA/miRNA/mRNA axis of CRNDE/hsa-miR-181a-5p/(CTNNB1/TCF4) and SNHG7/hsa-miR-216b-5p/GALNT1 axes as the significant therapeutic target in the mutant KRAS-associated CRC, and natural compounds have to be studied more in detail and to be developed as miRNA inhibitors. However, our predictions were supported by the evidence of the interaction and regulation of the lncRNA/miRNA/mRNA axis through bioinformatics approaches and ML-based miRNA inhibitor screening; it has to be studied further in in vitro and in vivo settings in the near future. Keywords: colorectal cancer, KRAS, lncRNA, machine learning, miRNA, RNA-RNA hybrid