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Updated: Aug 5, 2026
Mining Spatial Transcriptomics Datasets using DeepSpaceDB
Published on: September 5, 2025
Spatial transcriptomics differences of histopathological growth patterns in colorectal cancer liver metastases
Maria Escriva Conde1, Axel Andersson2, Peter Vermeulen3
1Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden.
Background:
Histopathological growth patterns (HGPs) have emerged as prognostic and predictive biomarkers in colorectal liver metastases (CLM). The desmoplastic/encapsulating HGP (EHGP) is associated with improved survival after surgery, whereas the replacement HGP (RHGP) is associated with poorer outcomes. However, HGPs can only be reliably assessed postoperatively, limiting their use as preoperative biomarkers. A deeper molecular understanding of HGPs could inform biomarker development and therapeutic strategies, including approaches to promote EHGP.
Methods:
We applied in situ sequencing (ISS), an image-based spatial transcriptomics method, to map RNA expression in CLM tissue. Two custom gene panels (150 and 175 genes) were analysed in a chemonaïve cohort of resected CLM tissue from 19 patients with EHGP and RHGP.
Results:
Distinct molecular programmes characterised the two patterns. RHGP was associated with damaged SAA1+ hepatocytes, KRT18+ neoplastic cells, and bifunctional hepatocyte-cholangiocyte cells. EHGP showed interferon-γ signalling, cytotoxic T-cell infiltration, and a fibrotic capsule with zonation-specific features: hepatic stellate cell activation, angiogenesis, and immune recruitment on the liver-facing side, and cancer-associated fibroblasts on the tumour-facing side.
Conclusions:
These differences imply that growth patterns emerge from tumour-host driven interactions. They reveal new molecular features of the metastatic niche. These insights may inform the search for novel treatment strategies.
