Letter to the Editor
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Aug 24, 2025; 16(8): 109934
Published online Aug 24, 2025. doi: 10.5306/wjco.v16.i8.109934
Integrating tumor location into artificial intelligence-based prognostic models in cancer
Chen Wang, Meng-Yan Chen, Yu-Gang Wang, Min Shi
Chen Wang, Meng-Yan Chen, Yu-Gang Wang, Min Shi, Department of Gastroenterology, Shanghai Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200336, China
Co-first authors: Chen Wang and Meng-Yan Chen.
Co-corresponding authors: Yu-Gang Wang and Min Shi.
Author contributions: Wang C and Chen MY were the primary contributors to the manuscript writing as the co-first authors of the paper; Shi M and Wang YG conceptualized the theme and structure of this letter as the co-corresponding authors; all authors have read and approved the final manuscript.
Supported by Natural Science Foundation of the Science and Technology Commission of Shanghai Municipality, No. 23ZR1458300; Key Discipline Project of Shanghai Municipal Health System, No. 2024ZDXK0004; Doctoral Innovation Talent Base Project for Diagnosis and Treatment of Chronic Liver Diseases, No. RCJD2021B02; and Pujiang Project of Shanghai Magnolia Talent Plan, No. 24PJD098.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
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: Min Shi, MD, Chief Physician, Professor, Department of Gastroenterology, Shanghai Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111 Xianxia Road, Changning District, Shanghai 200336, China. sm1790@shtrhospital.com
Received: May 27, 2025
Revised: June 20, 2025
Accepted: July 17, 2025
Published online: August 24, 2025
Processing time: 86 Days and 17.8 Hours
Core Tip

Core Tip: This study highlights the prognostic significance of tumor location in gastric cancer, showing that proximal tumors are associated with worse survival outcomes. Gender differences, particularly in carbohydrate antigen 72-4 expression, further influence prognosis. The letter proposes integrating tumor location into artificial intelligence-based clinical prediction models to improve prognostic accuracy. It outlines a stepwise framework for model development, multicenter validation, and clinical implementation, while addressing critical technical, ethical, and interoperability challenges for real-world application.