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Updated: Jun 17, 2026
Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones
Published on: November 30, 2016
Prognostic value and spatial transcriptomic landscape of histopathological growth patterns in synchronous colorectal
Background:
Histopathological growth patterns (HGPs) are critical prognostic biomarkers in colorectal liver metastases (CRLM), yet their molecular drivers remain unclear. This study aims to validate the prognostic value of HGPs in synchronous CRLM and explore their spatial transcriptomic underpinnings.
Methods:
Clinicopathological data from 182 patients with surgically resected synchronous CRLM were analyzed. HGPs were classified as desmoplastic (dHGP) or non-desmoplastic (ndHGP). Overall survival (OS) and disease-free survival (DFS) were evaluated via Kaplan-Meier curves and Cox regression. Public spatial transcriptomics datasets were integrated to characterize malignant epithelial programs across distinct HGPs using non-negative matrix factorization (NMF).
Results:
Clinical evaluation established ndHGP as an independent risk factor for mortality (adjusted Hazard Ratio [HR]: 1.91) and recurrence (adjusted HR: 1.62), showing significant associations with KRAS mutations and advanced nodal stage. Spatial transcriptomics revealed two divergent molecular strategies: desmoplastic-type tumors displayed hypoxia-driven angiogenesis and fibrotic confinement, supported by a fibrosis-related partial epithelial-mesenchymal transition (EMT) that formed a dense desmoplastic barrier. In contrast, replacement-type tumors showed enhanced proliferation and a distinctive hepatocyte mimicry metabolic phenotype, enabling metabolic co-option of the hepatic microenvironment to drive invasion.
Conclusions:
This study validates HGPs as versatile prognostic biomarkers for synchronous CRLM, and highlights two distinct transcriptomic adaptive strategies-angiogenic confinement versus metabolic co-option-as potential key determinants of clinical outcomes. These findings provide a morphological-molecular basis for precision risk stratification and targeted therapeutic development, justifying routine HGPs assessment in pathology reports.
