Tissue‐Agnostic Cellular Morphometric Biomarkers for Risk‐Adapted Management Across Gastrointestinal Precancerous Lesions and Cancers
While precision oncology increasingly adopts tissue-agnostic paradigms, current strategies remain heavily reliant on molecular alterations, with limited relevance to early-stage cancers and precancerous lesion management. Here we present an unsupervised and interpretable artificial intelligence framework that defines tissue-agnostic cellular morphometric biomarkers (CMBs) capturing conserved tumor microenvironment (TME) architectures associated with cancer progression across gastrointestinal (GI) organs. Discovered from colorectal cancer whole-slide images and validated in gastric and esophageal malignancies within a multi-center cohort of 2,602 patients, a 13-CMB signature demonstrates robust cross-GI tissue transferability and prognostic impact. Importantly, beyond prognostic value in pan-GI cancers, the 13-CMB signature enables risk stratification of precancerous lesions and early-stage cancers, addressing a key unmet need in clinical decision-making where molecular profiling is often impractical or insufficient. The CMB-based risk scores support risk-adapted management, including individualized surveillance intervals and tailored intervention strategies. Integrative analyses using bulk and single-cell RNA sequencing and immunohistochemistry profiling show that CMBs correspond to biologically interpretable morphological states of the TME, including immune-excluded and stromal-dominant architectures. Together, this study establishes a biologically transparent, tissue-agnostic CMB framework that links conserved TME organization to clinically actionable risk assessment, providing a scalable approach for early cancer management and precision oncology.
Authors
- Bo Hang (ORCID: https://orcid.org/0000-0002-5303-3442)
- Aiqin Mao
- Chengfei Jiang
- Jingjing Wei (ORCID: https://orcid.org/0000-0002-2197-8062)
- Jamie L. Inman (ORCID: https://orcid.org/0000-0002-6056-1219)
- David W. Threadgill (ORCID: https://orcid.org/0000-0003-3538-1635)
- Jian‐Hua Mao (ORCID: https://orcid.org/0000-0001-9320-6021)
- Allan Balmain (ORCID: https://orcid.org/0000-0001-6549-7861)
- Antoine M. Snijders (ORCID: https://orcid.org/0000-0002-7086-1063)
- S Celniker (ORCID: https://orcid.org/0000-0002-8019-0267)
- Lei Wang (ORCID: https://orcid.org/0000-0003-0178-5930)
- Pin Wang (ORCID: https://orcid.org/0000-0001-8939-5413)
- Qi Sun (ORCID: https://orcid.org/0000-0001-8276-0027)
- Yijun Lu
- Hang Chang
Institutions
- Lawrence Berkeley National Laboratory (US)
- University of California, Los Angeles (US)
- University of California, San Francisco (US)
- Fudan University (CN)
- National Clinical Research Center for Digestive Diseases (CN)
- Texas A&M Health Science Center (US)
- Nanjing Drum Tower Hospital (CN)
- Zhongshan Hospital (CN)
- Ministry of Education (ET)
- Texas A&M University (US)
Publication Details
- Journal
- Advanced Science
- Published
- 2026-08-25
- DOI
- https://doi.org/10.1002/advs.77353
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Government of Jiangsu Province
- Natural Science Foundation of Jiangsu Province