Molecular subtyping of colorectal cancer based on inositol metabolism identifies PLCG2 as a key prognostic biomarker.

BACKGROUND: Inositol metabolism, a crucial regulatory mechanism in cellular signaling, plays a pivotal role in colorectal cancer (CRC) tumorigenesis and progression. While multiple inositol-metabolizing enzymes have been implicated in CRC development, a systematic characterization of inositol metabolism-associated gene signatures and molecular subtyping based on these regulators remains unexplored. METHODS: Transcriptomic profiles and clinical data of CRC patients were obtained from TCGA and GEO databases. Integrated transcriptomic analysis enabled the stratification of CRC into distinct inositol metabolism-associated molecular subtypes via unsupervised consensus clustering. An inositol metabolism-related prognostic signature was constructed using LASSO-Cox regression. The functional role of the key identified gene was validated through in vitro experiments. RESULTS: CRC was stratified into two distinct subtypes (Cluster 1 and Cluster 2) exhibiting significant heterogeneity in clinical outcomes, tumor microenvironment features, and therapeutic vulnerabilities. The Cluster 1 subtype demonstrated strong associations with microsatellite stability (MSS), cell cycle processes, MYC signaling, and better patient prognosis. In contrast, the Cluster 2 subtype was closely linked to microsatellite instability (MSI), epithelial-mesenchymal transition (EMT), and TGF-β signaling. Additionally, a low Inositol Score was associated with increased sensitivity to multiple chemotherapeutic and targeted agents. Notably, phospholipase C gamma 2 (PLCG2) was identified as a key discriminator between subtypes and a top prognostic biomarker. PLCG2 was upregulated in CRC tissues, and its knockdown significantly suppressed tumor cell proliferation and migration in vitro. CONCLUSIONS: This study delineates novel inositol metabolism-based molecular subtypes in CRC, proposes PLCG2 as a promising prognostic biomarker and functional oncogene, and provides a conceptual framework for targeting inositol metabolism in clinical translation.