Identified hub genes associated with colorectal cancer by Weighted Gene Co-Expression Network Analysis
Identified hub genes associated with colorectal cancer by Weighted Gene Co-Expression Network Analysis
Zahra Taslimi,1,*
1. Faculty of Advanced Technologies, Shahrekord University of Medical Sciences
Introduction: Colorectal cancer (CRC) is one of the most common cancers worldwide, with the second highest cancer-related mortality rate. Today, colonoscopy is known to be the gold standard screening method for CRC, but it is an expensive and semi-invasive method. Therefore, patient non-compliance with endoscopy remains a major challenge in this field. On the other hand, the suboptimal accuracy of fecal occult blood testing has led to late diagnosis of CRC. Tumor lymph node metastasis (TNM) stage is currently the basis for CRC prognosis. The significant burden of colorectal cancer and its increasing trend in young adults highlight the need to understand its underlying mechanisms, provide new diagnostic and prognostic markers as well as Improved treatment methods. Weighted gene expression network analysis (WGCNA) is an in silico systems biology tool for analyzing gene expression in a complex network of regulatory genes. This R programming-based tool can identify highly correlated groups of genes (modules) to discover useful hub genes as diagnostic and prognostic biomarkers and therapeutic targets. Thus, this review provide a general overview of hub genes in colorectal cancer that were found by the WGCNA method and as therapeutic and diagnostic targets.
Methods: This is a review study collected from original articles related to the identification of hub genes in colorectal cancer with the keywords “WGCNA” AND “colorectal cancer” AND “hub genes” from 2018 onwards, from Google Scholar and Pubmed, it has been compiled and written. 40 articles were collected and 9 of them were excluded by lack of subject relevance so 31 studies were used. The inclusion criteria were all articles that found hub genes in colorectal cancer using the WGCNA method.
Results: Different studies illustrate that numerous hub genes can be as prognostic biomarkers and therapeutic targets.
HCLS1, EVI2B, CD48, GUCA2B, HJURP, CA2, CHP2, SULT1B1, MOGAT2, C1orf115, TDRD5 GPC1, COL6A3, MAL2 , PBXIP1, MPMZ, SCARA3, INA, ILK, MPP2, L1CAM, FLNA, FSTL3, LEMD1 and NKD1 are several hub genes in CRC were identified that have been evaluated with laboratory tests in addition to in silico analysis.
The hub genes have been validated only by bioinformatics analysis include: PAICS, ATR, AASDHPPT, DDX18, NUP107, TOMM6, MT1X, MT1G, MT2A, CXCL8, IL1B, CXCL5, CXCL11, IL10RA, GZMB, KIT, CCNF, DIAPH3, OSBPL3, RERGL, BAI3, CKAP2L, IVL, KRT16, KRT6C, KRT6A, KRT78, SBSN, LMOD3, CDKN2AIPNL, EXO5, ZNF69, BMS1P5, METTL21A, IL17RD, MIGA1, CEP19, FKBP14, CLCA1, GUCA2A, UGT2B17, DSC2, CA1, AQP8, ITLN1, BEST4, KLF4, IQCF6, PAFAH1B1, LMNB1, CACYBP, GLO1, PUM3, POC1A, ASF1B, SDCCAG3, ASNS, PDCD2L, CLCA1, CLCA4, SPARC, DCN, FBN1, WWTR1, TAGLN, DDX28, CSDC2, ABCC13, AMPD1, SCNN1B, TMIGD1, FYN, SEMA3A, AP2M1, L1CAM, NRP1, TLN1, VWF, ITGB3, ILK, ACTN1, COL1A2, THBS2, BGN, COL1A1, TAGLN, DACT3, DKC1, PA2G4, LYAR NOLC1, CCDC69, CLMP, FAM110B, FAM129A, GUCY1B3, PALLD, PLEKHO1, STY11, SOD2, CXCL8, MYL9, CNN1, L12 (RPL12), RPS3A, RPS9, RPL27A, RPL7, RPL28, RPL14, RPS17, mitochondrial ribosomal protein L16, G elongation factor, mitochondrial 2, (ZNF) 813, ZNF426, ZNF611, ZNF320, ZNF573, TIMP1, SPARCL1, MYL9, TPM2, CNN1, AAR2, PSMA7, NELFCD, PIGU, CHEK1, DEPDC1B, FANCI, MCM10, NCAPG, PARPBP, PLK4, RAD51AP1, RFC4.
Conclusion: Advances in high-throughput techniques and analytical methods such as WGCNA have provided new opportunities to study CRC at different molecular levels and advance our knowledge of CRC, ultimately leading to generate significant amounts of data. CRC is a very complex disease and thousands of molecules are changed during the process. Among these molecules, some may be valuable markers for cancer diagnosis and prognosis. These dysregulated molecules could serve as potential targets to help scientists develop new targeted drugs to treat CRC.