Multi-omics driven immune classification of colorectal cancer: Implications for immunotherapy efficacy prediction and enhancement with WNT signaling inhibition
Mar 11, 2026·




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Chu-Ling HU
1st Author
Du CAI
Co-1st Author
,Weiqiang You
Co-1st Author
,Zhengran Zhou
Co-1st Author
,Junwei Liu
Cheng-Hang LI
Min-Yi LV
Bao-Wen GAI
Chong Chen
Xinxin Huang
Run-Xian WANG
Xiao-Jian Wu
Co-corresponding Author
,Peishan Hu
Co-corresponding Author
Feng GAO
Corresponding Author
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0 min readAbstract
This study established a multi-omics immune classification framework for colorectal cancer by integrating transcriptomic, mutational, and methylation features across large discovery and validation cohorts. The authors identified three immune subtypes with distinct prognosis, tumor microenvironment states, and therapeutic implications, including an immune-cold subgroup marked by strong WNT pathway activation. Functional experiments further supported WNT-targeted inhibition as a strategy to enhance antitumor immunity and improve immunotherapy response in colorectal cancer.
Type
Publication
Cancer Letters
Highlight
Journal Article
Colorectal Cancer
Immunotherapy
Multi-Omics
WNT Signaling
Tumor Microenvironment

Authors
PhD Student
I am a PhD student focusing on AI-driven colorectal cancer research and clinically useful model development.

Authors
Postdoc
I focus on leveraging explainable AI and large foundation models to advance medical imaging and digital pathology in colorectal cancer research.

Authors
Research Assistant
I am a research assistant focusing on deep learning, multimodal feature fusion, and medical AI system development.

Authors
PhD Student
I am a PhD student at Guangzhou National Laboratory, focusing on colorectal cancer research, biostatistics, and evidence-driven clinical modeling.

Authors
PhD Student
I am a PhD student working on AI methods for colorectal cancer diagnosis and prognosis.

Authors
Research Student
I am a PhD student focusing on AI-based colorectal cancer research and predictive clinical modeling.

Authors
Professor
My research leverages AI and big data to improve diagnostics, prognostics, and ultimately, outcomes in cancer and other biomedical fields.