UNMET analysed human colorectal cancer liver metastases representing different histopathological growth patterns, together with adjacent liver tissue, using single-nucleus RNA sequencing. During the project, existing methods for isolating nuclei from frozen tumour tissue were found to provide suboptimal recovery of several biologically important cell populations including endothelial and tumor cells. The workflow was therefore systematically optimized, resulting in improved recovery of intact nuclei and increased representation of tumour and endothelial cells.
In parallel, a three-dimensional experimental model combining patient-derived colorectal cancer organoids with human liver sinusoidal endothelial cells was established. A workflow was developed to recover viable single cells from these complex co-cultures for single-cell RNA sequencing, enabling tumour–endothelial interactions to be investigated at high molecular resolution.
These approaches enabled detailed characterization of endothelial heterogeneity in colorectal cancer liver metastases. Distinct endothelial states were identified across adjacent liver and metastatic tissue, including vascular changes associated with vessel co-option and adaptation to the tumour microenvironment. The results highlighted endothelial mechanosensing and mechanoadaptation as prominent features of replacement-type metastases. Experimental characterization of the physical tumour microenvironment, including atomic force microscopy-based analyses, was initiated and remained ongoing at the end of the project.
The project also contributed to a collaborative investigation of the immune microenvironment of colorectal cancer liver metastases. This work identified a spatially organized immunosuppressive niche enriched in SPP1-expressing macrophages in replacement-type metastases.
UNMET established optimized experimental and sequencing workflows, generated a human single-nucleus transcriptomic dataset of colorectal cancer liver metastases, developed a sequencing-compatible tumour–endothelial co-culture model, and identified endothelial mechanoadaptation and immune microenvironment features associated with vessel co-option.