ABHD17C, a metabolic and immune-related gene signature, predicts prognosis and anti-PD1 therapy response in pancreatic cancer

Background: PDAC is a highly malignant and immune-suppressive tumor, posing great challenges to therapy.

Methods: In this study, we utilized multi-center RNA sequencing and non-negative matrix factorization clustering (NMF) to identify a group of metabolism-related genes that could effectively predict the immune status and survival (both disease-free survival and overall survival) of pancreatic ductal adenocarcinoma (PDAC) patients. Subsequently, through the integration of single cell sequencing and our center's prospective and retrospective cohort studies, we identified ABHD17C, which possesses metabolic and immune-related characteristics, as a potential biomarker for predicting the prognosis and response to anti-PD1 therapy in PDAC. We then demonstrated how ABHD17C participates in the regulation of the immune microenvironment through in vitro glycolytic function experiments and in vivo animal experiments.

Results: Through screening for pancreatic cancer metabolic markers and immune status, we identified a critical molecule that inhibits pancreatic cancer survival and prognosis. Further flow cytometry analysis confirmed that ABHD17C is involved in the inhibition of the formation of the immune environment in PDAC. Our research found that ABHD17C participates in the metabolic process of tumor cells in in vitro and in vivo experiments, reshaping the immunosuppressive microenvironment by downregulating the pH value. Furthermore, through LDHA inhibition experiments, we demonstrated that ABHD17C significantly enhances glycolysis and inhibits the formation of the immune suppressive environment. In in vivo experiments, we also validated that ABHD17C overexpression significantly mediates resistance to anti-PD1 therapy and promotes the progression of pancreatic cancer.

Conclusion: Therefore, ABHD17C may be a novel and effective biomarker for predicting the metabolic status and immune condition of PDAC patients, and provide a potential predictive strategy for anti-PD1 therapy in PDAC.