Publication Name	World Journal of Clinical Oncology
Manuscript ID	107646
Country	China

Category	Oncology
Manuscript Type	Review
Article Title	Advances and challenges in pathomics for liver cancer: From diagnosis to prognostic stratification
Manuscript Source	Invited Manuscript
All Author List	Ming-Hui Peng, Kai-Lun Zhang, Shi-Wei Guan, Quan Lin and Hai-Bo Yu
Funding Agency and Grant Number	Funding Agency Grant Number Wenzhou Municipal Science and Technology Bureau Y20240109
Corresponding Author	Hai-Bo Yu, Chief, PhD, Department of Hepatobiliary Surgery, The Dingli Clinical Institute of Wenzhou Medical University（Wenzhou central hospital), Wenzhou, Zhejiang, People’s Republic of China 325000, Wenzhou 325000, Zhejiang Province, China. zjuboby@zuaa.zju.edu.cn
Key Words	Pathomics; Liver cancer; Artificial intelligence; Deep learning; Microvascular invasion; Tumor recurrence; Prognostic biomarkers; Whole-slide imaging; Multiomics integration; Digital pathology
Core Tip	Artificial intelligence (AI)-powered pathomics revolutionizes liver cancer management by decoding histopathological patterns through the use of deep learning models such as microvascular invasion (MVI)-AI diagnostic model and CHOWDER, which excel in detecting MVI, immune biomarkers, and prognostic features. The integration of multiomics data links tumour morphology with molecular pathways (e.g., EZH2 dysregulation and immune evasion). Key challenges persist in model generalizability, interpretability, and clinical integration. Future advancements will require cross-modal AI systems combining radiogenomics and liquid biopsy alongside standardized platforms to translate pathomics results into personalized therapeutic strategies for hepatocellular carcinoma and metastatic liver malignancies.
Citation	<p>Peng MH, Zhang KL, Guan SW, Lin Q, Yu HB. Advances and challenges in pathomics for liver cancer: From diagnosis to prognostic stratification. <i>World J Clin Oncol</i> 2025; 16(6): 107646</p>

Received	2025-04-01 14:01
Peer-Review Started	2025-04-01 14:02
To Make the First Decision
Return for Revision	2025-04-09 12:44
Revised	2025-04-11 09:42
Second Decision	2025-05-28 02:42
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-05-28 10:47
Articles in Press	2025-05-28 10:47
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2025-05-30 05:32

ISSN	2218-4333 (online)
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/
Copyright	The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
Permissions	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher	Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website	http://www.wjgnet.com