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.