BPG is committed to discovery and dissemination of knowledge
Correspondence
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 Gastroenterol. Sep 28, 2026; 32(36): 120350
Published online Sep 28, 2026. doi: 10.3748/wjg.120350
Letter to the Editor: Autoantibody profiling in gastric cancer immunotherapy - dynamic monitoring, toxicity-benefit trade-off, and immune endotypes
Wan-Ting Huang, Bin-Bin Zhang, Jia-Nan Zhao
Wan-Ting Huang, School of Public Health and Nursing, Hangzhou Normal University, Hangzhou 311121, Zhejiang Province, China
Bin-Bin Zhang, School of Clinical Medicine, Hangzhou Normal University, Hangzhou 311121, Zhejiang Province, China
Jia-Nan Zhao, Department of Cardiovascular Sciences, Temple University, Philadelphia, PA 19140, United States
Co-corresponding authors: Bin-Bin Zhang and Jia-Nan Zhao.
Author contributions: Huang WT performed the literature retrieval and evidence synthesis, organized the references, and drafted the original manuscript; Zhang BB and Zhao JN conceptualized and designed the study framework, defined the academic positioning and core perspectives, provided substantial intellectual input, critically revised the manuscript for key scientific content, and supervised the entire work; they contributed equally to this article, they are the co-corresponding authors of this manuscript; and all authors reviewed and approved the final submitted version.
Supported by National Natural Science Foundation of China, No. 82204827.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Jia-Nan Zhao, Academic Fellow, Department of Cardiovascular Sciences, Temple University, North Carlisle Street, 3440 Carlisle st, Philadelphia, PA 19140, United States. tuv36393@temple.edu
Received: February 24, 2026
Revised: April 4, 2026
Accepted: May 12, 2026
Published online: September 28, 2026
Processing time: 178 Days and 14.9 Hours
Abstract

A study by Zheng et al published in the World Journal of Gastroenterology has reported that antinuclear antibody (ANA) and extractable nuclear antigen (ENA) positivity, together with carcinoembryonic antigen and tumor-node-metastasis stage, independently predict outcomes in gastric cancer patients receiving anti-programmed death 1/programmed death-ligand 1 based immunotherapy. However, although the findings of these authors support the clinical relevance of host autoimmunity, we believe that the implications can be further extended in three directions. Firstly, dependence on a single baseline ANA/ENA measurement overlooks the longitudinal dynamics that may distinguish pre-existing autoimmunity from treatment-induced seroconversion, which could be differentially associated with a durable response and acquired resistance. Secondly, interpreting ANA/ENA purely as a favorable prognostic marker neglects their potential value in signaling a heightened risk of immune-related adverse events, thereby indicating a need to evaluate the net clinical benefit rather than survival alone. Thirdly, the binary definition of ANA/ENA positivity ignores immunofluorescence patterns and specific ENA components that might define distinct “autoantibody immune endotypes” with different tumor-immune microenvironments. To refine immunotherapy-oriented risk stratification in gastric cancer, we propose prospective studies that integrate dynamic autoantibody profiling, detailed patterns, and toxicity data within composite host-tumor models.

Keywords: Gastric cancer; Antinuclear antibody; Extractable nuclear antigen; Immunotherapy; Immune endotype

Core Tip: Baseline antinuclear antibody/extractable nuclear antigen status may serve as a potential predictor of immunotherapy outcomes in gastric cancer. However, static indicators fail to capture dynamic autoantibody changes or the underlying differences in immune endotypes. We propose to build a composite host-tumor model that integrates longitudinal antibody profiles, detailed staining patterns, and safety data, and apply calibration curves and decision curve analysis to evaluate its net clinical benefit, thereby promoting the establishment of more refined risk stratification strategies and facilitating the practice of personalized immuno-oncology.

Write to the Help Desk