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

Mar 11, 2026·
Chu-Ling HU
Chu-Ling HU
1st Author
Du CAI
Du CAI
Co-1st Author
,
Weiqiang You
Co-1st Author
,
Zhengran Zhou
Co-1st Author
,
Junwei Liu
Cheng-Hang LI
Cheng-Hang LI
Min-Yi LV
Min-Yi LV
Bao-Wen GAI
Bao-Wen GAI
,
Chong Chen
,
Xinxin Huang
Run-Xian WANG
Run-Xian WANG
,
Xiao-Jian Wu
Co-corresponding Author
,
Peishan Hu
Co-corresponding Author
Feng GAO
Feng GAO
Corresponding Author
· 0 min read
Abstract
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
publication
Chu-Ling HU
Authors
PhD Student
I am a PhD student focusing on AI-driven colorectal cancer research and clinically useful model development.
Du CAI
Authors
Postdoc
I focus on leveraging explainable AI and large foundation models to advance medical imaging and digital pathology in colorectal cancer research.
Cheng-Hang LI
Authors
Research Assistant
I am a research assistant focusing on deep learning, multimodal feature fusion, and medical AI system development.
Min-Yi LV
Authors
PhD Student
I am a PhD student at Guangzhou National Laboratory, focusing on colorectal cancer research, biostatistics, and evidence-driven clinical modeling.
Bao-Wen GAI
Authors
PhD Student
I am a PhD student working on AI methods for colorectal cancer diagnosis and prognosis.
Run-Xian WANG
Authors
Research Student
I am a PhD student focusing on AI-based colorectal cancer research and predictive clinical modeling.
Feng GAO
Authors
Professor
My research leverages AI and big data to improve diagnostics, prognostics, and ultimately, outcomes in cancer and other biomedical fields.