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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastrointest Oncol. Nov 15, 2026; 18(11): 120353
Published online Nov 15, 2026. doi: 10.4251/wjgo.120353
Dynamic programmed death-ligand 1 and multimodal biomarkers in gastric cancer immunotherapy
Abdellatif Bouayad
Abdellatif Bouayad, Department of Immunology, Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda 4867, Oriental Region, Morocco
Author contributions: Bouayad A wrote and designed the manuscript.
AI contribution statement: We only used ChatGPT and Grammarly for language polishing in the response to reviewers. All scientific content, ideas, analyses, interpretations, and conclusions are original work by the author. No AI was used for data analysis, study design, or result interpretation. Figures and tables are original and created by the author.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Abdellatif Bouayad, MD, Associate Professor, Department of Immunology, Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Hay Al Hikma, P.O. Box 4867, Oujda 4867, Oriental Region, Morocco. a.bouayad@ump.ac.ma
Received: February 24, 2026
Revised: March 31, 2026
Accepted: May 25, 2026
Published online: November 15, 2026
Processing time: 243 Days and 19.2 Hours
Core Tip

Core Tip: Emerging non-invasive, real-time biomarkers such as serial exosomal programmed death-ligand 1 (PD-L1), circulating tumor DNA, and circulating immune cells may help overcome the limitations of static PD-L1 assessment, thereby improving the efficacy of anti-programmed death-1/PD-L1 therapy in advanced gastric cancer. Validation of rapid, cost-effective, and point-of-care dynamic tumor biomarkers is essential before their integration into routine clinical practice. Moreover, integrating histopathological and radiological findings with standard tumor biomarker data through artificial intelligence offers the potential to overcome the main limitations of circulating tumor DNA next-generation sequencing and PD-L1 immunohistochemistry assessment.

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