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World J Gastrointest Oncol. Mar 15, 2023; 15(3): 372-388
Published online Mar 15, 2023. doi: 10.4251/wjgo.v15.i3.372
Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer
Yuan-Yi Huang, Ting-Yu Bao, Xu-Qi Huang, Qi-Wen Lan, Ze-Min Huang, Yu-Han Chen, Zhi-De Hu, Xu-Guang Guo
Yuan-Yi Huang, Ting-Yu Bao, Xu-Qi Huang, Qi-Wen Lan, Ze-Min Huang, Yu-Han Chen, Xu-Guang Guo, Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
Yuan-Yi Huang, Department of Clinical Medicine, The First Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
Ting-Yu Bao, Ze-Min Huang, Yu-Han Chen, Xu-Guang Guo, Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
Xu-Qi Huang, Department of Clinical Medicine, The Sixth Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
Qi-Wen Lan, Department of Medical Imageology, The Second Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
Zhi-De Hu, Department of Laboratory Medicine, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010010, Inner Mongolia Autonomous Region, China
Xu-Guang Guo, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
Xu-Guang Guo, Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China
Xu-Guang Guo, Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, King Med School of Laboratory Medicine, Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China
Author contributions: Huang YY collected and assessed the data; Huang YY, Bao TY, and Huang XQ wrote the manuscript; Lan QW and Huang ZM participated in revising the manuscript; Chen YH and Hu ZD worked together to finalize the submission; Guo XG proposed and designed the study; All authors contributed to the article and approved the submitted version.
Conflict-of-interest statement: The authors report having no conflict of interest.
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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Xu-Guang Guo, MD, PhD, Associate Professor, Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, No. 63 Duobao Road, Liwan District, Guangzhou 510150, Guangdong Province, China. gysygxg@gmail.com
Received: November 23, 2022
Peer-review started: November 23, 2022
First decision: December 9, 2022
Revised: December 22, 2022
Accepted: February 15, 2023
Article in press: February 15, 2023
Published online: March 15, 2023
Processing time: 111 Days and 14.1 Hours
Core Tip

Core Tip: We comprehensively analyzed the effect of cuproptosis and immunity on the prognosis of colon cancer based on the close association between the three. Scrupulously, a variety of algorithms were applied to analyze and construct a three-gene prognostic model whose efficacy was statistically significant in both the training set and the external validation set. Moreover, in order to provide help for prognosis assessment and personalized treatment of colon cancer, we performed immunoinfiltration analysis and immunocheckpoint inhibitor-related genes expression analysis in different risk groups according to the cuproptosis- and immune-related combination model.