Abstract
BACKGROUND: We previously described the enrichment of plasma exosome metabolites in CRPC, PCa, and TFC cohorts, and found significant differences in pyrimidine metabolites. The PMGs is associated with the clinical prognosis of several cancers, but its biological role in PCa is still unclear. METHODS: This study extracted 98 reliable PMGs, and analyzed their somatic mutations, expression levels, and prognostic significance. Unsupervised clustering was applied to classify patients with PCa into clusters based on six PMGs that were related to the prognosis of PCa. The TME, gene mutations, and immune escape ability were compared among the clusters. A scoring algorithm based on prognostic PMGs, referred to as the PMGscore, was developed. TK1 was identified and the biological functions of TK1 were determined using loss-of-function experiments. RNA sequencing was subsequently performed to determine the molecules associated with the underlying mechanisms of TK1 function. RESULTS: In total, six out of 98 PMGs simultaneously exhibited differential expression in PCa and were correlated with BCR. Patients were clustered into two clusters according to the expression levels of these six PMGs, which reflected distinct clinical outcomes and immune cell infiltration characteristics. Clinical features, tumor prognosis, and functional annotation were analyzed. Subsequently, we constructed a prognostic signature using these six PMGs. In combination with other clinical traits, we found that the six PMGs' prognostic signature was an independent prognostic factor for patients with PCa. Finally, we found that the expression of TK1 was higher in CRPC tissues than in PCa tissues in three GEO datasets. The results indicated that TK1 promotes the growth and metastasis of PCa cells. CONCLUSIONS: We provide evidence for a PMG signature for PCa patients to accurately predict clinical prognosis. TK1 plays crucial roles in the progression of PCa cells and can be used as a potential therapeutic target for CRPC.