A glutamine metabolism gene signature with prognostic and predictive value for colorectal cancer survival and immunotherapy response.

BACKGROUND

Colorectal cancer (CRC) remains a major cause of cancer mortality, and dysregulated glutamine metabolism has emerged as a potential therapeutic target. However, the precise role of glutamine in CRC progression and treatment response remains debated.

METHODS

The authors collected transcriptome and microbiome information, from multiple sources to construct the GLMscore, a prognostic signature in CRC. To comprehensively characterize the biological features of GLMscore groups, the integration of transcriptomic profiling, KEGG pathway enrichment analysis, immune infiltration analysis, tumor immune microenvironment characterization, microbiome analysis, and tissue imaging were applied. Furthermore, CRC patients were stratified into GLMscore high and GLMscore low groups. The robustness of GLMscore was validated in both training and validation cohorts, and the predictive value for immunotherapy response was assessed. Finally, single-cell RNA sequencing (scRNA-seq) analysis was conducted to delineate the differences between GLMscore high and GLMscore low groups.

RESULTS

High GLMscore was associated with elevated expression of pathways related to tumorigenesis, epithelial-mesenchymal transition (EMT), and angiogenesis. Furthermore, high GLMscore patients exhibited an immunosuppressive TME characterized by increased infiltration of M0 and M2 macrophages, reduced overall immune infiltration (supported by ESTIMATE and TIDE scores), and increased expression of immune exclusion and suppression pathways. Analysis of pathological whole-slide images (WSIs) revealed a lack of intratumoral tertiary lymphoid structures (TLSs) in high GLMscore patients. The GLMscore also predicted resistance to common chemotherapeutic agents (using GDSC data) and, importantly, predicted poor response to immunotherapy in the IMvigor210 cohort. Analysis of 16S rRNA gene sequencing data revealed an enrichment of potentially oncogenic microbiota, including Hungatella and Selenomonas, in high GLMscore group. Single-cell analysis further confirmed the immunosuppressive TME and identified increased cell-cell communication between inflammatory macrophages and tumor cells in high GLMscore group.

CONCLUSION

The authors innovatively constructed GLMscore, a robust scoring system in quantifying CRC patients, exploring the distinct biological features, tumor immune microenvironment and microbiome ecology, exhibiting high validity in predicting survival prognosis and clinical treatment efficacy.