An epithelial cell fate-driven predictive model for liver metastasis risk in primary colorectal cancer through single-cell and multi-omics integration.

BACKGROUND

Colorectal cancer (CRC) is the third most prevalent form of cancer worldwide, with colorectal cancer liver metastases (CRLM) representing a principal cause of CRC-related mortality. However, a lack of molecular subgroups based on the differentiation states of diverse cell types in CRLM poses a significant barrier to progress in precision therapy.

METHODS

We integrated single-cell RNA sequencing (scRNA-seq, GSE178318) of paired CRLM tissues to define an epithelial cell fate gene signature. To evaluate the intrinsic "malignant seed" potential, this signature was projected onto a large-scale primary reference cohort (TCGA-COAD/READ, N = 433) using consensus clustering to establish the Malignant Development Signature of CRLM (MDSCRLM). Comprehensive multi-omics analyses-encompassing somatic mutations, copy number variations, tumor mutational burden (TMB), and ATAC-seq chromatin accessibility (N = 81)-alongside immune microenvironment deconvolutions and proteomic data integration were performed. The clinical relevance of the MDSCRLM model was externally validated using immunohistochemistry in an independent clinical cohort of 45 patients. Furthermore, the biological function of HSPA1A, a core marker, was experimentally verified through in vitro assays and in vivo metastasis models.

RESULTS

The MDSCRLM system discriminates three distinctmetastatic risk trajectories: Cluster 1-Aggressive-Metastasis-Enhanced CRLM (AMECRLM), Cluster 2-Cell Cycle-Active CRLM (CCACRLM), and Cluster 3-Growth-Inhibited CRLM (GICRLM). Survival analyses in the primary reference cohort validated the biological plausibility and prognostic impact of this model, revealing that GICRLM is associated with the most favorable prognosis while AMECRLM confers the poorest outcome. Our findings delineate distinct patterns of cellular heterogeneity, genomic instability (TP53 mutations), and gene expression across CRLM developmental stages. Prognostic validation in the clinical cohort and functional validation demonstrating that HSPA1A knockout attenuates tumor invasion and metastasis robustly supported the robustness of the MDSCRLM risk stratification.

CONCLUSIONS

We established a novel, clinically relevant CRLM risk stratification model with strong diagnostic and prognostic potential. By identifying pre-existing malignant features and stage-specific therapeutic vulnerabilities within the primary tumor, this model bridges the gap between biological discovery and precision medicine in advanced colorectal cancer.