Yu Y, Ren KM. Development of a prognostic prediction model based on microRNA-1269a in esophageal cancer. World J Gastrointest Oncol 2021; 13(8): 943-958 [PMID: 34457197 DOI: 10.4251/wjgo.v13.i8.943]
Corresponding Author of This Article
Kai-Ming Ren, MD, PhD, Professor, Department of Thoracic Surgery, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang 110004, Liaoning Province, China. renkmcmu@163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective 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/
World J Gastrointest Oncol. Aug 15, 2021; 13(8): 943-958 Published online Aug 15, 2021. doi: 10.4251/wjgo.v13.i8.943
Development of a prognostic prediction model based on microRNA-1269a in esophageal cancer
Yong Yu, Kai-Ming Ren
Yong Yu, Department of Ophtalmology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China
Kai-Ming Ren, Department of Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang 110004, China
Author contributions: All authors contributed to this manuscript; Yu Y and Ren KM designed and coordinated the study, performed the experiments, acquired and analyzed data, and interpreted the data and wrote the manuscript; all authors approved the final version of the article.
Supported byThe National Natural Science Foundation of China, No. 81570866; and the Outstanding Doctor Foundation of China Medical University, No. M0554.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee in The Shengjing Hospital of China Medical University.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: The authors declare no conflicts of interest.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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: Kai-Ming Ren, MD, PhD, Professor, Department of Thoracic Surgery, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang 110004, Liaoning Province, China. renkmcmu@163.com
Received: April 8, 2021 Peer-review started: April 8, 2021 First decision: May 24, 2021 Revised: May 27, 2021 Accepted: July 9, 2021 Article in press: July 9, 2021 Published online: August 15, 2021 Processing time: 128 Days and 2.5 Hours
ARTICLE HIGHLIGHTS
Research background
Esophageal cancer (ESCA) is a heterogeneous cancer with variable outcomes that are challenging to predict. MicroRNA (miR)-1269a is a newly discovered non-coding RNA that shows promising prognostic prediction in other cancers, but its clinical value in ESCA remains unclear.
Research motivation
This study established a comprehensive staging system that combines clinical characteristics with genetic mutations in ESCA.
Research objectives
This study aimed to determine the prognostic value of miR-1269a, and to develop a nomogram to succinctly predict the prognosis in esophageal carcinoma.
Research methods
miR-1269a expression in ESCA were detected using quantitative real-time polymerase chain reaction. Then we determined its prognostic value with clinical variables through multivariate Cox analysis. A nomogram based on miR-1269a expression using age and American Joint Committee on Cancer (AJCC) stage was developed and assessed its prognostic performance. Finally, we predicted the target genes of miR-1269a and analyzed their potential function in caner development using Gene Ontology and Kyoto Encyclopedia of Gene and Genomes analyses.
Research results
High expression of miR-1269a in ESCA showed poor prognosis in overall survival (OS) and cancer-specific survival (CSS), suffered increased rates of low differentiation and metastasis, and exhibited tumor stage T3 + T4, positive lymph stage, and AJCC stage III + IV. The area under the receiver operating characteristic curve of miR-1269a was 0.716 for OS and 0.764 for CSS. Multivariate Cox analysis revealed that AJCC stage and miR-1269a were independent factors for OS and CSS. Combing with age, we constructed a nomogram for prognostic prediction, which showed excellent performance for OS and CSS after 3 years and 5 years and was easy to use. And functional analysis indicated that miR-1269a was closely related to PI3K-AKT signaling pathway.
Research conclusions
miR-1269a can be used as a potential indicator for the prognosis of esophageal cancer. We developed an easy-to-use nomogram with excellent prognostic prediction for clinical use.
Research perspectives
In further research, the molecular mechanism of miR-1304 in esophageal cancer will be elucidated.
