Zang HL, Huang GM, Ju HY, Tian XF. Integrative analysis of the inverse expression patterns in pancreas development and cancer progression. World J Gastroenterol 2019; 25(32): 4727-4738 [PMID: 31528097 DOI: 10.3748/wjg.v25.i32.4727]
Corresponding Author of This Article
Xiao-Feng Tian, MSc, Attending Doctor, Department of Hepatobiliary and Pancreatic Surgery, China-Japan Union Hospital of Jilin University, No.126 Sendai Street, Changchun 130033, Jilin Province, China. chuie03755@163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Basic Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Hong-Liang Zang, Guo-Min Huang, Xiao-Feng Tian, Department of Hepatobiliary and Pancreatic Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, Jilin Province, China
Hai-Ying Ju, Department of Hematology, Jilin Province Blood Center, Changchun 130000, Jilin Province, China
Author contributions: Zang HL performed the majority of experiments and analyzed the data; Huang GM performed the molecular investigations; Ju HY designed and coordinated the research; Tian XF wrote the paper.
Conflict-of-interest statement: The authors declare no conflict of interest.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Xiao-Feng Tian, MSc, Attending Doctor, Department of Hepatobiliary and Pancreatic Surgery, China-Japan Union Hospital of Jilin University, No.126 Sendai Street, Changchun 130033, Jilin Province, China. chuie03755@163.com
Telephone: +86-431-84995999
Received: May 5, 2019 Peer-review started: May 5, 2019 First decision: June 10, 2019 Revised: July 5, 2019 Accepted: July 19, 2019 Article in press: July 19, 2019 Published online: August 28, 2019 Processing time: 118 Days and 4.3 Hours
ARTICLE HIGHLIGHTS
Research background
Pancreatic diseases remain as one of the most feared and clinically challenging diseases to treat despite continual improvements in therapies.
Research motivation
To develop agents into a targeted drug for explicitly killing cancer cells.
Research objectives
To explore the molecular interpretation patterns of pancreas development and cancer progression.
Research methods
This study used the ANOVA method, self-organizing map-singular value decomposition analysis, enrichment analysis, and hypergeometric test.
Research results
The results investigate continuously dysregulated interpretation patterns in pancreas development and pancreatic cancer.
Research conclusions
Integrative analysis of continuously dysregulated interpretation patterns to establish the inverse interpretation in metabolites and gene levels. Through integrating the genes with metabolites, some key abnormal regions of metabolic pathways have been established.
Research perspectives
With the increase of human disease database, a larger-scale integrative analysis is needed for the correlation with pancreas development and cancer. We believe the more convince underlying mechanism and potential drug development targets could be supposed by the larger-scale development and integrative cancer analysis in further. Also, this method could be used for other diseases investigation.
