Combining AI to reveal CCDC3-mediated pathways of colorectal cancer liver metastasis

In colorectal cancer liver metastases, chromosomal instability (CIN) serves as a critical hallmark linked to tumor aggressiveness and poor prognosis. This study integrated single-cell RNA sequencing, weighted gene co-expression network analysis, and non-negative matrix factorization to construct a comprehensive CIN index, revealing that CIN-high tumor cells exhibit more aggressive phenotypes and reside in an immune-excluded tumor microenvironment. Cancer-associated fibroblasts (CAFs) showed enhanced communication with CIN-high tumor cells, and a key CAF-derived gene, CCDC3, was experimentally validated to promote metastasis, proliferation, and CIN in vitro and in vivo. The bio-knowledge graph analysis based on artificial intelligence further revealed the core regulation of CCDC3 in chromosomal instability and liver metastasis of colorectal cancer. Mechanistically, CCDC3 physically interacts with CXCR3 on CRC cells, activating STAT3 phosphorylation and subsequent CDT1 transcription, forming a CCDC3/CXCR3/STAT3/CDT1 signaling axis. Disruption of this axis-either by genetic knockdown or pharmacological inhibition-significantly suppressed metastatic traits, tumor growth, and liver colonization in mouse models. Clinically, high CCDC3 expression correlated with elevated CIN signatures and worse patient survival. These findings uncover a novel CAF-driven signaling pathway that promotes CIN and metastatic progression in CRC, highlighting its potential as a therapeutic target for aggressive, CIN-high colorectal cancer.

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Publication Details

Journal
npj Digital Medicine
Published
2026-03-07
DOI
https://doi.org/10.1038/s41746-026-02457-0
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

Combining AI to reveal CCDC3-mediated pathways of colorectal cancer liver metastasis

Ziting Jiang, Yongfa Zhang, R. Stephanie Huang, X. Jin et al.
npj Digital Medicine
Single-cell and spatial transcriptomics
article

Combining AI to reveal CCDC3-mediated pathways of colorectal cancer liver metastasis

Ziting Jiang, Yongfa Zhang, R. Stephanie Huang, X. Jin, Yibin Wu, Weiping Zhu, Yixiu Wang, Lu Wang, Xuanci Bai, Yi Shi, Qinyu Liu, Xigan He
article en

Abstract

In colorectal cancer liver metastases, chromosomal instability (CIN) serves as a critical hallmark linked to tumor aggressiveness and poor prognosis. This study integrated single-cell RNA sequencing, weighted gene co-expression network analysis, and non-negative matrix factorization to construct a comprehensive CIN index, revealing that CIN-high tumor cells exhibit more aggressive phenotypes and reside in an immune-excluded tumor microenvironment. Cancer-associated fibroblasts (CAFs) showed enhanced communication with CIN-high tumor cells, and a key CAF-derived gene, CCDC3, was experimentally validated to promote metastasis, proliferation, and CIN in vitro and in vivo. The bio-knowledge graph analysis based on artificial intelligence further revealed the core regulation of CCDC3 in chromosomal instability and liver metastasis of colorectal cancer. Mechanistically, CCDC3 physically interacts with CXCR3 on CRC cells, activating STAT3 phosphorylation and subsequent CDT1 transcription, forming a CCDC3/CXCR3/STAT3/CDT1 signaling axis. Disruption of this axis-either by genetic knockdown or pharmacological inhibition-significantly suppressed metastatic traits, tumor growth, and liver colonization in mouse models. Clinically, high CCDC3 expression correlated with elevated CIN signatures and worse patient survival. These findings uncover a novel CAF-driven signaling pathway that promotes CIN and metastatic progression in CRC, highlighting its potential as a therapeutic target for aggressive, CIN-high colorectal cancer.

npj Digital Medicine
Shanghai Medical College of Fudan University (CN), Fudan University (CN), Fudan University Shanghai Cancer Center (CN), Shanghai Institutes for Biological Sciences (CN)
No poverty
Openalex Percentile: Top 30%
Single-cell and spatial transcriptomics
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