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.

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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

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article

Tissue‐Agnostic Cellular Morphometric Biomarkers for Risk‐Adapted Management Across Gastrointestinal Precancerous Lesions and Cancers

Bo Hang, Aiqin Mao, Chengfei Jiang, Jingjing Wei et al.
Advanced Science
Single-cell and spatial transcriptomics
article

Tissue‐Agnostic Cellular Morphometric Biomarkers for Risk‐Adapted Management Across Gastrointestinal Precancerous Lesions and Cancers

Bo Hang, Aiqin Mao, Chengfei Jiang, Jingjing Wei, Jamie L. Inman, David W. Threadgill, Jian‐Hua Mao, Allan Balmain, Antoine M. Snijders, S Celniker, Lei Wang, Pin Wang, Qi Sun, Yijun Lu, Hang Chang
article en

Abstract

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.

Advanced Science
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)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province
Peace, Justice and strong institutions
Openalex Percentile: Top 17%
Single-cell and spatial transcriptomics
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