An immune, stroma, and epithelial--mesenchymal transition-related signature for predicting recurrence and chemotherapy benefit in stage II--III colorectal cancer

Apr 1, 2023·
Du CAI
Du CAI
1st Author
,
Wei Wang
Min-Er ZHONG
Min-Er ZHONG
De-Jun FAN
De-Jun FAN
,
Xuanhui Liu
Cheng-Hang LI
Cheng-Hang LI
Ze-Ping HUANG
Ze-Ping HUANG
Qi-Qi ZHU
Qi-Qi ZHU
Min-Yi LV
Min-Yi LV
Chu-Ling HU
Chu-Ling HU
Xin DUAN
Xin DUAN
,
Xiao-Jian Wu
Co-corresponding Author
Feng GAO
Feng GAO
Corresponding Author
· 0 min read
Abstract

Background: Debates exist on the treatment decision of the stage II/III colorectal cancer (CRC) due to the insufficiency of the current TNM stage‐based risk stratification system. Epithelial–mesenchymal transition (EMT) and tumor microenvironment (TME) have both been linked to CRC progression in recent studies. We propose to improve the prognosis prediction of CRC by integrating TME and EMT.

Methods: In total, 2382 CRC patients from seven datasets and one in‐house cohort were collected, and 1640 stage II/III CRC patients with complete survival information and gene expression profiles were retained and divided into a training cohort and three independent validation cohorts. Integrated analysis of 398 immune, stroma, and epithelial‐mesenchymal transition (ISE)‐related genes identified an ISE signature independently associated with the recurrence of CRC. The underlying biological mechanism of the ISE signature and its influence on adjuvant chemotherapy was further explored.

Results: We constructed a 26‐gene signature which was significantly associated with poor outcome in Training cohort (p < 0.001, HR [95%CI] = 4.42 [3.25–6.01]) and three independent validation cohorts (Validation cohort‐1: p < 0.01, HR [95%CI] = 1.70 [1.15–2.51]; Validation cohort‐2: p < 0.001, HR [95% CI] = 2.30 [1.67–3.16]; Validation cohort‐3: p < 0.01, HR [95% CI] = 2.42 [1.25–4.70]). After adjusting for known clinicopathological factors, multivariate cox analysis confirmed the ISE signature’s independent prognostic value. Subgroup analysis found that stage III patients with low ISE score might benefit from adjuvant chemotherapy (p < 0.001, HR [95%CI] = 0.15 [0.04–0.55]). Hypergeometric test and enrichment analysis revealed that low‐risk group was enriched in the immune pathway while high‐risk group was associated with the EMT pathway and CMS4 subtype.

Conclusion: We proposed an ISE signature for robustly predicting the recurrence of stage II/III CRC and help treatment decision by identifying patients who will not benefit from current standard treatment.

Type
Publication
Cancer Medicine
publication
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.
Min-Er ZHONG
Authors
Surgeon
De-Jun FAN
Authors
Associate Professor
My research explores the intersection of gastrointestinal endoscopy (GIE) and artificial intelligence (AI), along with the biological mechanisms of colorectal cancer development.
Cheng-Hang LI
Authors
Research Assistant
I am a research assistant focusing on deep learning, multimodal feature fusion, and medical AI system development.
Ze-Ping HUANG
Authors
Medical Student
Qi-Qi ZHU
Authors
Surgeon
I am a surgeon focusing on colorectal cancer and translational bioinformatics in clinical practice.
Min-Yi LV
Authors
PhD Student
I am a PhD student focusing on colorectal cancer research, biostatistics, and evidence-driven clinical modeling.
Chu-Ling HU
Authors
PhD Student
I am a PhD student focusing on AI-driven colorectal cancer research and clinically useful model development.
Xin DUAN
Authors
Postdoc
Feng GAO
Authors
Professor
My research leverages AI and big data to improve diagnostics, prognostics, and ultimately, outcomes in cancer and other biomedical fields.