Weighted correlation network analysis revealed novel long non-coding RNAs for colorectal cancer

Abstract

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide, which after breast, lung and, prostate cancers, is the fourth prevalent cancer in the United States. Long non-coding RNAs (lncRNAs) have an essential role in the pathogenesis of CRC. Therefore, bioinformatics studies on lncRNAs and their target genes have potential importance as novel biomarkers. In the current study, publicly available microarray gene expression data of colorectal cancer (GSE106582) was analyzed with the Limma, Geoquery, Biobase package. Afterward, identified differentially expressed lncRNAs and their target genes were inserted into Weighted correlation network analysis (WGCNA) to obtain modules and hub genes. A total of nine differentially expressed lncRNAs (LINC01018, ITCH-IT, ITPK1-AS1, FOXP1-IT1, FAM238B, PAXIP1-AS1, ATP2B1-AS1, MIR29B2CHG, and SNHG32) were identified using microarray data analysis. The WGCNA has identified several hub genes for black (LMOD3, CDKN2AIPNL, EXO5, ZNF69, BMS1P5, METTL21A, IL17RD, MIGA1, CEP19, FKBP14), blue (CLCA1, GUCA2A, UGT2B17, DSC2, CA1, AQP8, ITLN1, BEST4, KLF4, IQCF6) and turquoise (PAFAH1B1, LMNB1, CACYBP, GLO1, PUM3, POC1A, ASF1B, SDCCAG3, ASNS, PDCD2L) modules. The findings of the current study will help to improve our understanding of CRC. Moreover, the hub genes that we have identified could be considered as possible prognostic/diagnostic biomarkers. This study led to the determination of nine lncRNAs with no previous association with CRC development.

Identification and validation of voltage‐dependent anion channel 1‐related genes and immune cell infiltration in diabetic nephropathy

“…Data source and preprocessing GSE30122 17 and GSE30529 17 datasets from patients with DN were acquired from the Gene Expression Omnibus 18 database by using the "GEOquery (Version 2.68.0, http://seandavi.github. io/GEOquery)" 19 package. The GSE30122 dataset included data from 50 healthy controls and 19 patients with DN, whereas the GSE30529 dataset included data from 12 healthy controls and 10 patients with DN.…”

ATP2B1-AS1 exacerbates sepsis-induced cell apoptosis and inflammation by regulating miR-23a-3p/TLR4 axis

“…12 LncRNA ATPase plasma membrane Ca2+ transporting 1 antisense RNA 1 (ATP2B1-AS1), also known as long intergenic non-protein-coding RNA 936 (LINC00936), is harbored in chr12:89,708,954-89,713,726 with a length of 3626-bp. 13 ATP2B1-AS1 has been identified as one of the differentially expressed lncRNAs using microarray data analysis in colorectal cancer 14 and acute myocardial infarction. 15 Additionally, ATP2B1-AS1 modulates miR-330-5p/ TLR4 axis to facilitate cerebral ischemia/reperfusion injury through MyD88/NF-κB signaling pathway.…”

Identifying potential anti‐metastasis drugs for prostate cancer through integrative bioinformatics analysis and compound library screening

“…The development of high‐throughput methods (such as large‐scale microarrays and whole‐genome sequencing) and bioinformatics methods has provided a wealth of information to guide drug screening. One such method is the weighted gene co‐expression network analysis (WGCNA), which is able to analyze both differentially expressed genes, as well as their interconnectivity, enabling the discovery of synergistically expressed modules 7 . The discovery of hub genes and subsequent screening for candidate biomarkers or therapeutic targets has been applied in various cancers.…”

“…One such method is the weighted gene co-expression network analysis (WGCNA), which is able to analyze both differentially expressed genes, as well as their interconnectivity, enabling the discovery of synergistically expressed modules. 7 The discovery of hub genes and subsequent screening for candidate biomarkers or therapeutic targets has been applied in various cancers.…”