Abstract Purpose Colon cancer (CC) is a malignant tumor with high morbidity and mortality. Fatty acid metabolism, has attracted more attention as an essential part of tumor metabolic reprogramming. This study aimed to investigate the relationship between fatty acid metabolism-related genes and clinical survival outcomes in CC. Method We downloaded the mRNA expression profiles and clinical information of CC from the TCGA data portal. Expression of fatty acid metabolism-related genes and survival data of CC samples were extracted. Univariate Cox analysis and LASSO regression analysis were used to identify the fatty acid metabolism-related genes correlated with the prognosis of CC patients. Then, those six prognostic fatty acid metabolism-related genes were used to construct a prognostic model to predict the survival probability of CC patients. Patients were divided into two groups at high and low risk, and the differences in GSEA enrichment, drug sensitivity, immune cell infiltration, the efficacy of immunotherapy, and immune checkpoint expression level between the two groups were discussed. Finally, a novel nomogram integrating the risk score, age, gender, and clinical stages was established to predict the prognosis of CC patients. The Nomogram prediction model's accuracy was evaluated by using calibration plots, ROC curve, and DCA. Result 449 CC and 41 normal samples were included in this study. A prognostic model based on six fatty acid metabolism-related genes was built to evaluate the prognosis of CC patients. Patients in the high-risk group had poorer overall survival than those in the low-risk group (P < 0.001). The expression level of macrophages and T helper cells were higher, and the expression level of Tregs was lower in the high-risk group. The expression levels of PD-1, LAG3, and CTLA4 were higher in high-risk patients, and the high-risk group had a higher TIDE score, indicating a worse response to immunotherapy. The Calibration plots, ROC curve, and DCA have all proved that the Nomogram system can accurately predict the survival rate of CC patients. Conclusion Fatty acid metabolism-related genes can be used as a new therapeutic target for CC and further improve the survival rate of CC patients through individualized therapy.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
A mixed catalyst Fe2(SO4)3· xH2O/concentrated H2SO4 has been used to catalyze the esterification of aromatic acids with ethanol and methanol. This catalyst system is found to be effective for the rapid reactions and the esterification yields are excellent.
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