Metabolic Reprogramming：Application of lipid metabolism related genes in the risk model of clinical prognosis of pancreatic cancer

Abstract

Abstract Pancreatic cancer(PC) is a highly invasive digestive system tumor, with a 5-year survival rate of less than 10%. However, the mechanism of its occurrence remains unclear. Metabolic alterations in malignant tumor cells have been found to occur throughout the processes of uptake, synthesis, and degradation, making metabolic reprogramming one of the characteristics of malignant tumors. Disturbances in lipid metabolism have also been observed in pancreatic cancer cells. To explore the relationship between lipid metabolism and the survival of pancreatic cancer patients, we constructed a prognostic analysis model related to lipid metabolism using public databases such as TCGA and GEO. This model includes two risk genes (PLAAT2 and PTGES) and five protective genes (PEMT, CYP46A1, LTC45, TMEM86B, and LIPE). We validated the model using a validation dataset and found that it had good predictive performance. We also discovered distinct differences in immune levels and drug susceptibility between the high and low-risk groups. In summary, this model is helpful for predicting the survival of pancreatic cancer patients and provides insights into the identification of new therapeutic targets for pancreatic cancer.