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. Oct 14, 2026; 32(38): 121425
Published online Oct 14, 2026. doi: 10.3748/wjg.121425
Published online Oct 14, 2026. doi: 10.3748/wjg.121425
Single-cell and bulk transcriptomics with machine learning decode B cell hub genes and diagnostic biomarkers in anal fistula
Ting-Ting Li, Jia-Nan Li, Han-Wen Yang, Li-Xia Lai, Qiang Yu, Xiao-Yu Chen, Yue Wang, Xue-Cheng Zhang, Huang-Fu Ma, Xin-Bo Song, Department of Proctology, China-Japan Friendship Hospital, Beijing 100029, China
Xin-Yu Dou, Department of Pain Medicine, China-Japan Friendship Hospital, Beijing 100029, China
Li Jiang, Integrated Chinese and Western Medicine Department of Diabetes, China-Japan Friendship Hospital, Beijing 100029, China
Co-first authors: Ting-Ting Li and Jia-Nan Li.
Author contributions: All authors contributed significantly to the research and approved the submitted manuscript; the study was conceived and designed by Li JN and Li TT; Li TT drafted the manuscript, which was revised and refined by Yang HW, Song XB and Dou XY; Jiang L, Lai LX, Yu Q, and Ma HF analyzed, interpreted, and visualized the data; Wang Y, Zhang XC, and Chen XY accessed and validated the data presented in the manuscript; and Li TT and Li JN contributed equally to this work as co-first authors.
AI contribution statement: AI tools (specifically ChatGPT) were used solely for linguistic refinement and formatting assistance. No AI tool was involved in the generation of research data, interpretation of results, or formulation of conclusions. All AI-generated outputs were critically reviewed and revised by the authors. In addition, an AI assistant (ChatGPT) was used during the preparation of the response letter to the reviewers for language polishing purposes. All AI-generated outputs in both the manuscript and the response letter were critically reviewed and revised by the authors. No AI tool is listed as an author of this work.
Supported by the Elite Medical Professionals Initiative of the China-Japan Friendship Hospital, No. ZRJY2025-QM11; and National High Level Hospital Clinical Research Funding, No. 2023-NHLHCRF-YYPPLC-ZR-03 and No. 2025-NHLHCRF-DLYJ-PY-08.
Institutional review board statement: This study was reviewed and authorized by the Ethics Committee of the China-Japan Friendship Hospital (Approval No. 2023-KY-363).
Conflict-of-interest statement: The authors declare no conflicting financial or personal interests.
Data sharing statement: The raw single-cell and bulk RNA sequencing data will be deposited in the Gene Expression Omnibus database upon acceptance and will be available at https://www.ncbi.nlm.nih.gov/geo/.
Corresponding author: Jia-Nan Li, Department of Proctology, China-Japan Friendship Hospital, No. 2 Yingyuan Garden East Street, Chaoyang District, Beijinjavascript:;g 100029, China.
Received: March 25, 2026
Revised: May 6, 2026
Accepted: June 4, 2026
Published online: October 14, 2026
Processing time: 166 Days and 4.5 Hours
Revised: May 6, 2026
Accepted: June 4, 2026
Published online: October 14, 2026
Processing time: 166 Days and 4.5 Hours
Core Tip
Core Tip: This study is the first to combine single-cell RNA sequencing (RNA-seq) with bulk RNA-seq and machine learning to systematically characterize B-cell-associated immune networks in anal fistula (AF). Three hub genes, LINC-PINT, LRBA, and SYK, were identified as central signaling nodes linking inflammatory amplification, angiogenesis, and fibrosis within the AF microenvironment. A predictive model incorporating these genes achieved robust diagnostic accuracy, offering promising biomarker candidates for precision diagnosis and targeted therapeutic intervention in AF.