Multi-omics analysis reveals features improving outcomes and immunotherapy resistance in MSS colorectal cancer

In contrast to the MSI-H subtype, most microsatellite-stable (MSS) colorectal cancer (CRC) patients exhibit poor prognosis and limited responsiveness to immunotherapy, highlighting the urgent need for robust biomarkers to stratify prognosis and predict immunotherapy responsiveness. Here, 68 single-cell and 3,767 bulk transcriptome samples were integrated to identify and validate MSS patients with high immune infiltration. Multidimensional, prognosis-related, and immunological features specific to MSS CRC were characterized at cellular and genetic levels. To reduce algorithm selection bias, 93 artificial intelligence algorithms were applied to construct a machine learning-derived MSS prognostic-immune signature (MLDMPIS). MLDMPIS demonstrated robust prognostic and immunotherapy response prediction performance in 1,323 MSS patients and six independent immunotherapy cohorts, outperforming clinical indicators, published prognostic signatures, and immune response models. Mechanistically, CADM1 was identified as a key molecule associated with MLDMPIS. Functional analyses revealed that CADM1 promotes tumor stemness, thereby enhancing proliferation, invasion, and metastasis in MSS CRC.

Authors

Institutions

Publication Details

Journal
iScience
Published
2026-01-29
DOI
https://doi.org/10.1016/j.isci.2026.114817
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-omics analysis reveals features improving outcomes and immunotherapy resistance in MSS colorectal cancer

Shutong Liu, Anning Zuo, Yuhao Ba, Hui Xu et al.
iScience
Cancer Immunotherapy and Biomarkers
article

Multi-omics analysis reveals features improving outcomes and immunotherapy resistance in MSS colorectal cancer

Shutong Liu, Anning Zuo, Yuhao Ba, Hui Xu, Haidong Zhu, Zaoqu Liu, Xinwei Han
article en

Abstract

In contrast to the MSI-H subtype, most microsatellite-stable (MSS) colorectal cancer (CRC) patients exhibit poor prognosis and limited responsiveness to immunotherapy, highlighting the urgent need for robust biomarkers to stratify prognosis and predict immunotherapy responsiveness. Here, 68 single-cell and 3,767 bulk transcriptome samples were integrated to identify and validate MSS patients with high immune infiltration. Multidimensional, prognosis-related, and immunological features specific to MSS CRC were characterized at cellular and genetic levels. To reduce algorithm selection bias, 93 artificial intelligence algorithms were applied to construct a machine learning-derived MSS prognostic-immune signature (MLDMPIS). MLDMPIS demonstrated robust prognostic and immunotherapy response prediction performance in 1,323 MSS patients and six independent immunotherapy cohorts, outperforming clinical indicators, published prognostic signatures, and immune response models. Mechanistically, CADM1 was identified as a key molecule associated with MLDMPIS. Functional analyses revealed that CADM1 promotes tumor stemness, thereby enhancing proliferation, invasion, and metastasis in MSS CRC.

iScienceVol. 29(3)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Zhongda Hospital Southeast University (CN), First Affiliated Hospital of Zhengzhou University (CN), Southeast University (CN)
Good health and well-being
Openalex Percentile: Top 74%
Cancer Immunotherapy and Biomarkers
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.