Whole Exome Sequencing of Ulcerative Colitis–associated Colorectal Cancer Based on Novel Somatic Mutations Identified in Chinese Patients

Yan, Pengguang; Wang, Yanan; Meng, Xiangchen; Yang, Hong; Liu, Zhanju; Qian, Jiaming; Zhou, Weixun; Li, Jingnan

doi:10.1093/ibd/izz020

Cited by 20 publications

(16 citation statements)

References 37 publications

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“…A previous study reported that somatic mutations and altered pathways are one of the reasons why UC turns into cancer [ 30 ]. Besides, Yan et al [ 9 ] found that COL6A3 referred to apoptosis, and the phosphatidylinositol 3-kinase/Akt pathway is associated with nonsilent recurrent somatic mutations in UC. COL3A1 is a profibrogenic extracellular matrix gene.…”

Section: Discussionmentioning

confidence: 99%

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Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

et al. 2021

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Background This study aimed to screen the feature modules and characteristic genes related to ulcerative colitis (UC) and construct a support vector machine (SVM) classifier to distinguish UC patients. Methods Four datasets that contained UC and control samples were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) with consistency were screened via the MetaDE method. The weighted gene coexpression network (WGCNA) was used to distinguish significant modules based on the four datasets. The protein–protein interaction network was established based on intersection genes. Enrichment analysis of Gene Ontology (GO) biological processes (BPs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were established based on DAVID. An SVM combined with recursive feature elimination was also applied to construct a disease classifier for the disease diagnosis of UC patients. The efficacy of the SVM classifier was evaluated through receiver operating characteristic curves. Results Twelve highly preserved modules were obtained using the WGCNA, and 2009 DEGs with significant consistency were selected using the MetaDE method. Sixteen significantly related GO BPs and 12 KEGG pathways were obtained, such as cytokine-cytokine receptor interaction, cell adhesion molecules, and leukocyte transendothelial migration. Subsequently, 41 genes were used to construct an SVM classifier, such as CXCL1, CCR2, IL1B, and IL1A. The area under the curve (AUC) was 0.999 in the training dataset, whereas the AUC was 0.886, 0.790, and 0.819 in the validation set (GSE65114, GSE37283, and GSE36807, respectively). Conclusions An SVM classifier based on feature genes might correctly identify healthy people or UC patients.

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Section: Discussionmentioning

confidence: 99%

“…Zhu et al [ 8 ] found several genes associated with the development of UC, such as MMP1 , REG1A , and AQP8 . Yan et al [ 9 ] found 11 mutated genes differentially expressed in UC samples, such as APC , APOB , MECP2 , NCOR2 , and USP48 . All these reports suggested that feature genes might play an important role in the diagnosis of UC.…”

Section: Introductionmentioning

confidence: 99%

Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

et al. 2021

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“…CRC is a major long-term serious complication in patients with UC (22)(23)(24). Previous studies have shown that the main area of colon cancer incidence (25,26).…”

Section: Discussionmentioning

confidence: 99%

Correlation of ulcerative colitis and colorectal cancer: a systematic review and meta-analysis

Wang¹,

Wang²,

Shao³

2021

J Gastrointest Oncol

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“…Yang VW and Liu Y found that the deletion of KLF4 causes genetic instability, which in turn leads to the progress of CAC (36). The mutation of APOB gene in CRC associated with ulcerative colitis was found by whole exon sequencing, and there was signi cant difference between ulcerative colitis associated CRC and scattered CRC (37). CD44 is an adhesion and anti-apoptotic molecule that is highly expressed in colon cancer (38).…”

Section: Discussionmentioning

confidence: 99%

Identification of Hub Genes and Pathways in Colitis-Associated Colon Cancer by Integrated Bioinformatic Analysis

Yao

Liu

Wang

et al. 2021

Preprint

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Background Colon cancer is the third leading cause of death in the world. According to the etiology, colon cancer can be divided into three categories: sporadic, hereditary, and colitis-associated colon cancer(CAC). In terms of clinical features, CAC patients have younger age of onset, more multiple lesions, more difficult to find under endoscope, stronger tumor invasiveness than sporadic colorectal cancer patients. Early detection of CAC by endoscopic monitoring is a challenge, and the incidence of septal colorectal cancer is still high. So it is indispensable to find the biomarkers to predict tumorigenesis of CAC. Methods The gene expression profiles of GSE43338 and GSE4904 were downloaded from Gene Expression Omnibus (GEO) database. The Limma package was used to standardize the data and obtain differentially expressed genes (DEGs). Protein-protein interaction (PPI) network was evaluated by STRING database. The Cytoscape software was used to establish PPI network and to perform modular analysis. Functional annotation analysis were performed by the DAVID. The transcription factor (TF) and miRNAs that regulate genes expression were analyzed by using the Network Analyst algorithm. Expression correlation analysis were conducted in GEPIA. The prognostic analysis of hub genes were conducted based on TCGA samples. Results A total of 275 DEGs including 103 up-regulated genes and 172 down-regulated genes were identified by bioinformatics analysis in CAC. IGF1, BMP4, SPP1, APOB, CCND1, CD44, PTGS2, CFTR, BMP2, KLF4, TLR2 were identified as hub DEGs, which were significantly enriched in PI3K-Akt signaling pathway, stem cell pluripotency regulation pathway, Focal adhesion-Hippo signal pathway and AMPK signal pathway respectively. The FOXC1 were crucial regulators for these hub gene according to the TF analysis. The Sankey diagram showed that both PI3K-AKT signal pathway and Focal adhesion were composed of up-regulated genes, such as SPP1, CD44, TLR2, CCND1, IGF1, which were related to core miRNAs, hsa-mir-16-5p, hsa-mir-129-2-3p and hsa-mir-37a-3p by research and prediction. Survival analysis showed that the differential expression of SPP1, CFRT and KLF4 was significantly related to the poor prognosis of CAC. Conclusion This study provided a novel way to illuminate the mechanism of colitis-associated colon cancer. The most of all, the hub genes and signaling pathways may contribute to the prevention, diagnosis and treatment of CAC.

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Whole Exome Sequencing of Ulcerative Colitis–associated Colorectal Cancer Based on Novel Somatic Mutations Identified in Chinese Patients

Cited by 20 publications

References 37 publications

Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

Screening of characteristic genes in ulcerative colitis by integrating gene expression profiles

Correlation of ulcerative colitis and colorectal cancer: a systematic review and meta-analysis

Identification of Hub Genes and Pathways in Colitis-Associated Colon Cancer by Integrated Bioinformatic Analysis

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