Literature DB >> 23679280

Analysis of key genes and pathways associated with colorectal cancer with microarray technology.

Yan-Jun Liu1, Shu Zhang, Kang Hou, Yun-Tao Li, Zhan Liu, Hai-Liang Ren, Dan Luo, Shi-Hong Li.   

Abstract

OBJECTIVE: Microarray data were analyzed to explore key genes and their functions in progression of colorectal cancer (CRC).
METHODS: Two microarray data sets were downloaded from Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified using corresponding packages of R. Functional enrichment analysis was performed with DAVID tools to uncover their biological functions.
RESULTS: 631 and 590 DEGs were obtained from the two data sets, respectively. A total of 32 common DEGs were then screened out with the rank product method. The significantly enriched GO terms included inflammatory response, response to wounding and response to drugs. Two interleukin-related domains were revealed in the domain analysis. KEGG pathway enrichment analysis showed that the PPAR signaling pathway and the renin-angiotensin system were enriched in the DEGs.
CONCLUSIONS: Our study to systemically characterize gene expression changes in CRC with microarray technology revealed changes in a range of key genes, pathways and function modules. Their utility in diagnosis and treatment now require exploration.

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Year:  2013        PMID: 23679280     DOI: 10.7314/apjcp.2013.14.3.1819

Source DB:  PubMed          Journal:  Asian Pac J Cancer Prev        ISSN: 1513-7368


  4 in total

1.  Integrated bioinformatics analysis for the identification of key genes and signaling pathways in thyroid carcinoma.

Authors:  Bo Zhang; Zuoyu Chen; Yuyun Wang; Guidong Fan; Xianghui He
Journal:  Exp Ther Med       Date:  2021-01-28       Impact factor: 2.447

2.  Identification of Key Pathways and Genes in Anaplastic Thyroid Carcinoma via Integrated Bioinformatics Analysis.

Authors:  Shengqing Hu; Yunfei Liao; Lulu Chen
Journal:  Med Sci Monit       Date:  2018-09-14

3.  Analysis of potential genes and pathways associated with the colorectal normal mucosa-adenoma-carcinoma sequence.

Authors:  Zhuoxuan Wu; Zhen Liu; Weiting Ge; Jiawei Shou; Liangkun You; Hongming Pan; Weidong Han
Journal:  Cancer Med       Date:  2018-04-16       Impact factor: 4.452

4.  Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics.

Authors:  Yubin Kou; Suya Zhang; Xiaoping Chen; Sanyuan Hu
Journal:  Onco Targets Ther       Date:  2015-04-08       Impact factor: 4.147

  4 in total

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