Identification of prognostic biomarkers and drug target prediction for colon cancer according to a competitive endogenous RNA network

Abstract

colorectal cancer is one of the commoner digestive tract malignant tumor types, and its incidence and mortality rate are high. accumulating evidence indicates that long-chain non-coding rnas (lncrnas) and protein-coding rnas interact with each other by competing with the same micro(mi) rna response element (Mres) and serve an important role in the regulation of gene expression in a variety of tumor types. However, the regulatory mechanism and prognostic role of lncrna-mediated competing endogenous (ce)rna networks in colon cancer have yet to be elucidated. The expression profiles of mrnas, lncrnas and mirnas from 471 colon cancer and 41 paracancerous tissue samples were downloaded from The cancer Genome atlas database. a lncrna-mirna-mrna cerna network in colon cancer was constructed and comprised 17 hub lncrnas, 87 hub mirna and 144 hub mrnas. The topological properties of the network were analyzed, and the random walk algorithm was used to identify the nodes significantly associated with colon cancer. Survival analysis using the ualcan database indicated that 2/17 lncrnas identified [metastasis-associated lung adenocarcinoma transcript (MalaT1) and maternally expressed gene 3 (MeG3)] and 5/144 mrnas [FeS upstream region (FURIN), nuclear factor of activated T-cells 5 (NFAT5), rna Binding Motif Protein 12B (RBM12B), ras related GTP binding a (RRAGA) and Wd repeat domain phosphoinositide-interacting protein 2 (WIPI2)] were significantly associated with the overall survival of patients with colon cancer, and may therefore be used as potential prognostic biomarkers of colon cancer. according to extracted lncrna-mirna-mrna interaction pairs, the GSe26334 dataset was used to confirm that the lncrna MALAT1/miR-129-5p/NFAT5 axis may represent a novel regulatory mechanism concerning the progression of colon cancer. The clusterProfiler package was used to analyze Gene Ontology (Go) and Kyoto encyclopedia of Genes and Genomes (KeGG) pathways in colon cancer. Finally, drugs that significantly interact with the core genes identified in colon cancer were predicted using a hypergeometric test. of these, fostamatinib was identified to be a targeted drug for colon cancer therapy. The present findings provide a novel perspective for improved understanding of the lncrna-associated cerna network and may facilitate the development of novel targeted therapeutics in colon cancer.

Construction and Characterization of a Synergistic lncRNA–miRNA Network Reveals a Crucial and Prognostic Role of lncRNAs in Colon Cancer

“…Summarizing these results, we believe that MEG3 played a role in cancer development while ZEB1-AS1 could act in both carcinogenesis and cancer development. These results were consistent with previous studies ( Fu and Cui, 2017 ; Gong et al, 2017 ; Liu et al, 2019 ; Hu et al, 2020 ; Ni et al, 2020 ).…”

Identification of prognostic biomarkers and potential regulatory axes for acute myeloid leukemia based on a competitive endogenous RNA network

“…Similarly, NFAT5, which is a target gene of hsa-mir-206 in the ceRNA network, has been shown to regulate multiple tumor processes. For example, NFAT5 can act as a ceRNA regulated by circFOXO3, plays a role in glioblastoma through sponging miR-138-5p and miR-432-5p [31], and may also regulate the progression of colon cancer through the MALAT1/miR1295p/NFAT5 axis [32]. Here, results from our investigation and the GEPIA website both showed that NFAT5 has a strong relationship with CTB-193M12.1 (Fig.…”

MALAT1 shuttled by extracellular vesicles promotes M1 polarization of macrophages to induce acute pancreatitis via miR‐181a‐5p/HMGB1 axis

“… 9 Long non‐coding RNA (lncRNA) metastasis‐associated lung adenocarcinoma transcript‐1 (MALAT1) can act as competitive endogenous RNA (ceRNA) to regulate its downstream target genes via interaction of microRNA response elements (MREs) and microRNAs (miRNAs). 10 Accumulating evidence proves that knockdown of MALAT1 promotes differentiation of macrophages into M1 subtypes in hepatocellular carcinoma. 11 Additionally, MALAT1 shuttled by exosomes from oxidized low‐density lipoprotein‐treated endothelial cells can promote the M2 polarization of macrophages in cardiovascular disease.…”