Multi-modal integration of histopathology and transcriptomics reveals STAB1+ macrophage-associated efferocytosis as a suppressive immune mechanism in colon adenocarcinoma

Colon adenocarcinoma (COAD) has a limited response to immunotherapy due to its immunologically “cold” tumor microenvironment (TME). Efferocytosis is an important process that regulates the TME, but its mechanism and clinical significance in COAD are unclear. We integrated histopathological images, transcriptomic profiles, and clinical data from 387 COAD patients. Image features were extracted using ResNet50 and CellProfiler, followed by construction of a multimodal machine learning model to evaluate prognostic risk. We further combined bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics to comprehensively characterize efferocytosis-associated immune cell subsets and signaling pathways. The efferocytosis-based risk model demonstrated strong prognostic performance across multiple time points and remained independent of conventional clinical indicators. Mechanistically, we identified a subset of STAB1+ tumor-associated macrophages (TAMs) enriched in COAD tumors, exhibiting enhanced efferocytosis activity, M2-like polarization, and mTORC1 signaling activation. In vitro, STAB1 expression was essential for IL-4-induced M2 polarization, and its inhibition attenuated the formation of immunosuppressive TAMs. Single-cell and spatial transcriptomic analyses revealed that this macrophage population was transcriptionally distinct and increased in abundance following neoadjuvant therapy. This study establishes a multimodal prognostic system that integrates histopathological imaging with molecular profiling, and for the first time reveals the pivotal role of STAB1+ TAMs in orchestrating the immunosuppressive TME via efferocytosis and mTORC1 activation. Our findings provide both a clinically applicable risk assessment tool and a potential therapeutic target. Targeting STAB1 may broaden the benefit of immunotherapy for COAD patients with limited responses to immune checkpoint blockade. Identification of STAB1+ tumor-associated macrophages (TAMs) as a central immunosuppressive subpopulation enriched in apoptotic tumor regions and further expanded following neoadjuvant therapy. Demonstration that STAB1 drives M2 macrophage polarization and efferocytosis through activation of the mTORC1 signaling pathway. Revealing a complex cell–cell communication network linking STAB1+ TAMs, neutrophils, and malignant epithelial cells, forming a positive feedback loop that reinforces immune evasion. Development of a clinically applicable, deep learning–based prognostic model, which translates histopathological features into quantifiable risk indices and demonstrates predictive power comparable to that of the TNM staging system.

Authors

Institutions

Publication Details

Journal
Journal of Translational Medicine
Published
2025-12-08
DOI
https://doi.org/10.1186/s12967-025-07348-8
Primary Topic
Immune cells in cancer
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-modal integration of histopathology and transcriptomics reveals STAB1+ macrophage-associated efferocytosis as a suppressive immune mechanism in colon adenocarcinoma

Shukun Han, Shuo Xu, Xingqi Guo, Yu Tian et al.
Journal of Translational Medicine
Immune cells in cancer
article

Multi-modal integration of histopathology and transcriptomics reveals STAB1+ macrophage-associated efferocytosis as a suppressive immune mechanism in colon adenocarcinoma

Shukun Han, Shuo Xu, Xingqi Guo, Yu Tian, Zhiyuan Chang, Yuyang Zhang, Yu J, Zitong Xu, Chao Lv, Bing Han, Chongli Zhong
article en

Abstract

Colon adenocarcinoma (COAD) has a limited response to immunotherapy due to its immunologically “cold” tumor microenvironment (TME). Efferocytosis is an important process that regulates the TME, but its mechanism and clinical significance in COAD are unclear. We integrated histopathological images, transcriptomic profiles, and clinical data from 387 COAD patients. Image features were extracted using ResNet50 and CellProfiler, followed by construction of a multimodal machine learning model to evaluate prognostic risk. We further combined bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics to comprehensively characterize efferocytosis-associated immune cell subsets and signaling pathways. The efferocytosis-based risk model demonstrated strong prognostic performance across multiple time points and remained independent of conventional clinical indicators. Mechanistically, we identified a subset of STAB1+ tumor-associated macrophages (TAMs) enriched in COAD tumors, exhibiting enhanced efferocytosis activity, M2-like polarization, and mTORC1 signaling activation. In vitro, STAB1 expression was essential for IL-4-induced M2 polarization, and its inhibition attenuated the formation of immunosuppressive TAMs. Single-cell and spatial transcriptomic analyses revealed that this macrophage population was transcriptionally distinct and increased in abundance following neoadjuvant therapy. This study establishes a multimodal prognostic system that integrates histopathological imaging with molecular profiling, and for the first time reveals the pivotal role of STAB1+ TAMs in orchestrating the immunosuppressive TME via efferocytosis and mTORC1 activation. Our findings provide both a clinically applicable risk assessment tool and a potential therapeutic target. Targeting STAB1 may broaden the benefit of immunotherapy for COAD patients with limited responses to immune checkpoint blockade. Identification of STAB1+ tumor-associated macrophages (TAMs) as a central immunosuppressive subpopulation enriched in apoptotic tumor regions and further expanded following neoadjuvant therapy. Demonstration that STAB1 drives M2 macrophage polarization and efferocytosis through activation of the mTORC1 signaling pathway. Revealing a complex cell–cell communication network linking STAB1+ TAMs, neutrophils, and malignant epithelial cells, forming a positive feedback loop that reinforces immune evasion. Development of a clinically applicable, deep learning–based prognostic model, which translates histopathological features into quantifiable risk indices and demonstrates predictive power comparable to that of the TNM staging system.

Journal of Translational MedicineVol. 23(1)
First Hospital of China Medical University (CN), Liaoning Cancer Hospital & Institute (CN), China Medical University (CN)
Openalex Percentile: Top 55%
Immune cells in cancer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.