Multi-omics analysis reveals different cholesterol metabolism subtypes in colorectal cancer

Cholesterol metabolism (CM) plays a critical role in the progression of colorectal cancer (CRC), yet its molecular and immunological implications remain incompletely understood. Therefore, we aimed to identify CRC subtypes according to CM-related genes and reveal their distinct characteristics.

Based on CM-related genes, we applied unsupervised clustering to classify CRC into two subtypes using transcriptomic data from TCGA and comprehensively compared their transcriptomic, genomic and clinical characteristics. We utilized single-cell RNA sequencing data and classified the samples into two subtypes and investigated the distinctions in the tumor microenvironment (TME) between these subtypes.

Two distinct CM subtypes were identified: Subtype A, characterized by cholesterol esterification and storage, was associated with inflammatory activation and cellular senescence. This subtype exhibited a poor prognosis and reduced predicted response to chemotherapy and immunotherapy. Tumor cells in Subtype A exhibited characteristics of epithelial-mesenchymal transition and angiogenesis. The TME in Subtype A contained higher infiltration of myeloid cells, fibroblasts, and pericytes, with dominant immunosuppressive tumor-associated macrophages (TAMs), especially TAM_SPP1, which interacted closely with Fibro_IL32, promoting immune exclusion. In contrast, Subtype B was marked by enhanced cholesterol catabolism and regulation. Tumor cells in this subtype displayed features of proliferation and stem-like properties. It showed a more active immune microenvironment with increased plasma cell infiltration and fewer immunosuppressive TAMs. Finally, we constructed a prognostic signature and validated its performance across multiple datasets.

These findings provide comprehensive insights into CM subtypes in CRC, highlighting their clinical significance and potential therapeutic implications.