Abstract
Background: Colorectal cancer liver metastasis is a major risk factor of poor outcomes, necessitating proactive interventions and treatments. Cancer-associated fibroblasts (CAFs) play essential roles in metastasis, with a focus on metabolic reprogramming. However, knowledge about associations between Cancer-associated fibroblasts metabolic phenotypes and immune cell is limited. This study uses single-cell and bulk transcriptomics data to decode roles of metabolism-related subtype of Cancer-associated fibroblasts and immune cells in liver metastasis, developing a CAF-related prognostic model for colorectal cancer liver metastases. Methods: In this study, Cancer-associated fibroblasts metabolism-related phenotypes were screened using comprehensive datasets from The Cancer Genome Atlas and gene expression omnibus (GEO). Cox regression and Lasso regression were applied to identify prognostic genes related to Cancer-associated fibroblasts, and a model was constructed based on the Cancer-associated fibroblasts subtype gene score. Subsequently, functional, immunological, and clinical analyses were performed. Results: The study demonstrated the metabotropic heterogeneity of Cancer-associated fibroblasts cells. Cancer-associated fibroblasts cells with varying metabolic states were found to exhibit significant differences in communications with different immune cells. Prognostic features based on Cancer-associated fibroblasts signature scores were found to be useful in determining the prognostic status of colorectal cancer patients with liver metastases. High immune activity and an enrichment of tumor-related pathways were observed in samples with high Cancer-associated fibroblasts signature scores. Furthermore, Cancer-associated fibroblasts signature score could be practical in guiding the selection of chemotherapeutic agents with higher sensitivity. Conclusion: Our study identified a prognostic signature linked to metabotropic subtype of Cancer-associated fibroblasts. This signature has promising clinical implications in precision therapy for colorectal cancer liver metastases.