Increased glycolysis correlates with elevated immune activity in tumor immune microenvironment.

BACKGROUND

Prior studies showed that tumor glycolysis and tumor immune evasion are interdependent. However, a systematic investigation of the association between tumor glycolysis and tumor immunity in various cancers remains lacking.

METHODS

Using the Cancer Genome Atlas (TCGA) datasets, we explored the association between glycolytic activity and immune signatures in 14 cancer types. We also explored the associations between glycolytic activity and tumor immunity associated genetic features, including PD-L1 expression, tumor mutation burden (TMB), and tumor aneuploidy. Moreover, we performed in vitro experiments to verify some findings from bioinformatics analysis. Furthermore, we explored the association between tumor glycolytic activity and immunotherapy response.

FINDINGS

Glycolytic activity was likely correlated with active immune signatures in various cancers and highly glycolytic tumors presented an immune-stimulatory tumor microenvironment. Compared to TMB and aneuploidy, glycolytic activity was a stronger and more consistent predictor for immune signatures in diverse cancers. Both computational and experimental analyses showed that glycolysis could increase PD-L1 expression in tumor. Glycolytic activity had a strong correlation with apoptosis which was a strong positive predictor for immune signatures, suggesting that apoptosis could be an important medium connecting glycolytic activity with immune activity in cancer. Finally, highly glycolytic tumors exhibited a better immunotherapy response and a favorable survival in the immunotherapy setting.

INTERPRETATION

Tumor glycolysis may increase tumor immunity in diverse cancers. Glycolytic activity enhances PD-L1 expression on tumor cells and thus promotes anti-PD-1/PD-L1 immunotherapy response. Thus, the tumor glycolytic activity could be a predictive biomarker for immunotherapy response in diverse cancers. FUND: This work was supported by the China Pharmaceutical University (grant numbers 3150120001, 2632018YX01 to XW).