Literature DB >> 33411100

Integration of gene expression data identifies key genes and pathways in colorectal cancer.

Hossein Hozhabri1, Ali Lashkari2, Seyed-Morteza Razavi3,4,5, Ali Mohammadian6.   

Abstract

Colorectal cancer (CRC) is one of the most common malignant tumor and prevalent cause of cancer-related death worldwide. In this study, we analyzed the gene expression profiles of patients with CRC with the aim of better understanding the molecular mechanism and key genes in CRC. Four gene expression profiles including, GSE9348, GSE41328, GSE41657, and GSE113513 were downloaded from GEO database. The data were processed using R programming language, in which 319 common differentially expressed genes including 94 up-regulated and 225 down-regulated were identified. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were conducted to find the most significant enriched pathways in CRC. Based on the GO and KEGG pathway analysis, the most important dysregulated pathways were regulation of cell proliferation, biocarbonate transport, Wnt, and IL-17 signaling pathways, and nitrogen metabolism. The protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape software and hub genes including MYC, CXCL1, CD44, MMP1, and CXCL12 were identified as the most critical hub genes. The present study enhances our understanding of the molecular mechanisms of the CRC, which might potentially be applied in the treatment strategies of CRC as molecular targets and diagnostic biomarkers.

Entities:  

Keywords:  Bioinformatics analysis; Colorectal cancer; Differentially expressed gene; Microarray

Year:  2021        PMID: 33411100     DOI: 10.1007/s12032-020-01448-9

Source DB:  PubMed          Journal:  Med Oncol        ISSN: 1357-0560            Impact factor:   3.064


  42 in total

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Journal:  CA Cancer J Clin       Date:  2020-03-05       Impact factor: 508.702

5.  Identification of key pathways and genes in colorectal cancer using bioinformatics analysis.

Authors:  Bin Liang; Chunning Li; Jianying Zhao
Journal:  Med Oncol       Date:  2016-08-31       Impact factor: 3.064

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Journal:  Nucleic Acids Res       Date:  2016-05-03       Impact factor: 16.971

7.  STRING v10: protein-protein interaction networks, integrated over the tree of life.

Authors:  Damian Szklarczyk; Andrea Franceschini; Stefan Wyder; Kristoffer Forslund; Davide Heller; Jaime Huerta-Cepas; Milan Simonovic; Alexander Roth; Alberto Santos; Kalliopi P Tsafou; Michael Kuhn; Peer Bork; Lars J Jensen; Christian von Mering
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Authors:  Darshan S Chandrashekar; Bhuwan Bashel; Sai Akshaya Hodigere Balasubramanya; Chad J Creighton; Israel Ponce-Rodriguez; Balabhadrapatruni V S K Chakravarthi; Sooryanarayana Varambally
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10.  Hub Genes and Key Pathway Identification in Colorectal Cancer Based on Bioinformatic Analysis.

Authors:  Jian Lv; Lili Li
Journal:  Biomed Res Int       Date:  2019-11-06       Impact factor: 3.411

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  3 in total

1.  MiR-19a suppresses ferroptosis of colorectal cancer cells by targeting IREB2.

Authors:  Hongwei Fan; Rong Ai; Suen Mu; Xuemin Niu; Zhengrong Guo; Lin Liu
Journal:  Bioengineered       Date:  2022-05       Impact factor: 6.832

2.  Contribution of Matrix Metalloproteinase-1 Genotypes to Colorectal Cancer in Taiwan.

Authors:  Ming-Hsien Wu; Te-Cheng Yueh; Wen-Shin Chang; Chia-Wen Tsai; Chun-Kai Fu; Mei-Due Yang; Chien-Chih Yu; DA-Tian Bau
Journal:  Cancer Genomics Proteomics       Date:  2021-04-23       Impact factor: 4.069

3.  Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis.

Authors:  Xi Wang; Guangyu Gao; Zhengrong Chen; Zhihao Chen; Mingxiao Han; Xiaolu Xie; Qiyuan Jin; Hong Du; Zhifei Cao; Haifang Zhang
Journal:  Cancer Cell Int       Date:  2021-07-07       Impact factor: 5.722

  3 in total

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