Identification of genomic expression differences between right-sided and left-sided colon cancer based on bioinformatics analysis
Authors Peng Q, Lin K, Chang T, Zou L, Xing P, Shen Y, Zhu Y
Received 16 October 2017
Accepted for publication 4 January 2018
Published 31 January 2018 Volume 2018:11 Pages 609—618
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Amy Norman
Peer reviewer comments 3
Editor who approved publication: Dr Yao Dai
Qiliang Peng,1–3,* Kaisu Lin,4,* Tao Chang,5 Li Zou,1–3 Pengfei Xing,1–3 Yuntian Shen,1–3 Yaqun Zhu1–3
1Department of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, 2Institute of Radiotherapy & Oncology, Soochow University, Suzhou, 3Suzhou Key Laboratory for Radiation Oncology, Suzhou, 4Department of Oncology, Nantong Rich Hospital, Nantong, 5Department of General Surgery, The Sixth People’s Hospital of Kunshan, Kunshan, People’s Republic of China
*These authors contributed equally to this work
Introduction: More and more findings have demonstrated that right-sided colon cancers (RCC) and left-sided colon cancers (LCC) are distinct clinical and biological entities and suggest that they should be treated as different diseases. However, the reasons why RCC and LCC harbor different clinical and biological features remain unclear.
Materials and methods: To identify the genomic expression differences between RCC and LCC and uncover the mechanisms underlying these differences, we chose the gene expression profiles of GSE14333 from the Gene Expression Omnibus (GEO) database as an object of study. Then, a systematic and integrative bioinformatics analysis was performed to research the possible mechanism of the differentially expressed (DE) genes from the Gene Expression Omnibus dataset including gene ontology (GO) analysis, pathway enrichment analysis, protein–protein interaction (PPI) network construction, and module analysis. Totally, we extracted 3,793 DE genes from samples of colon cancer including 1,961 genes upregulated in RCC and 1,832 genes upregulated in LCC from the selected dataset.
Results: The results of GO and pathway enrichment analysis indicated that RCC and LCC could predispose to different pathways regulated by different genes. Based on the PPI network, PCNA, TP53, HSP90AA1, CSNK2A1, UBB, LRRK2, ABL1, PRKACA, CAV1, and JUN were identified as the key hub genes. Also, significant modules were screened from the PPI network.
Conclusion: In conclusion, the present study indicated that the identified genes and pathways may promote new insights into the underlying molecular mechanisms contributing to the difference between RCC and LCC and might be used as specific therapeutic targets and prognostic markers for the personalized treatment of RCC and LCC.
Keywords: colon cancer, location, differentially expressed genes, bioinformatics analysis
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