Literature DB >> 31638423

Screening and Identification of Key Biomarkers in Pancreatic Cancer: Evidence from Bioinformatic Analysis.

Meng Zhang1, Chen-Yi Di2, Peng Guo3, Ling-Bing Meng4, Meng-Jie Shan5, Yong Qiu6, Pei-Yuan Guo7, Ke-Qin Dong7, Qi Xie8, Qiang Wang9.   

Abstract

Pancreatic cancer (PC) whose mortality is comparable to morbidity is a highly fatal disease. Early approaches of diagnosis and treatment for PC are quite limited, so it is of great urgency to figure out the exact tumorigenesis and development mechanism of PC. To identify the related molecular markers of pancreatic oncogenesis, we downloaded three microarray datasets (GSE63111, GSE101448, and GSE107610) from Gene Expression Omnibus (GEO) database. The common differentially expressed genes (DEGs) among them were identified, and the corresponding function enrichment analyses were accomplished. The protein-protein interaction network was conducted by Search Tool for the Retrieval of Interacting Genes (STRING), and the corresponding module analysis was accomplished by Cytoscape. There were 55 DEGs found in total. The molecular function and biological processes (BP) of these DEGs mainly include cytokinesis, mitotic nuclear division, cell division, cell proliferation, microtubule-based movement, and mineral absorption. Among the 55 DEGs, 14 hub genes were further confirmed and it was concluded that they mainly function in mitotic cytokinesis, microtubule-based movement, mitotic chromosome condensation, and mitotic spindle assembly from the BP analysis. The survival analysis showed that all the 14 hub genes, especially nucleolar and spindle associated protein 1 and abnormal spindle microtubule assembly, may involve in the tumorigenesis and development of PC. And they might be used as new biomarkers for auxiliary diagnosis and potential targets for immunotherapy of PC.

Entities:  

Keywords:  bioinformatic analysis; biomarker; pancreatic cancer

Year:  2019        PMID: 31638423     DOI: 10.1089/cmb.2019.0189

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  1 in total

1.  RPN2 Predicts Poor Prognosis and Promotes Bladder Cancer Growth and Metastasis via the PI3K-Akt Pathway.

Authors:  Chenglin Han; Shuxiao Chen; Haiyang Ma; Xiangchuan Wen; Zilong Wang; Yingkun Xu; Xunbo Jin; Xiao Yu; Muwen Wang
Journal:  Onco Targets Ther       Date:  2021-03-03       Impact factor: 4.147

  1 in total

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