KIF2C Expression Combined With Regulatory T Cell (Tregs) Infiltration Density To Predict The Progression Of CRPC

[Background]Prostate cancer is one of the most common cancers in the world.It is also a disease with high mortality in men and a serious threat to mens health.Although early prostate cancer can be effectively controlled by endocrine therapy,a large proportion of patients still transform into castration-resistant prostate cancer(CRPC)after 2-3years of endocrine therapy,followed by biological recurrence or metastasis.Studies have shown that once prostate cancer progresses to castration-resistant prostate cancer(CRPC),many patients will die of prostate cancer within 3 years.[Objective]In view of the obvious poor prognosis of CRPC in patients with prostate cancer,this study intends to find out the factors closely related to the progression of prostate cancer and can effectively predict the progression of CRPC through bioinformatics methods,and construct an effective prediction model to effectively predict the progression of CRPC in the early stage.[Materials and Methods]In this study,the prostate cancer data of the latest TCGA public database were used to screen the differential genes closely related to the progression of prostate cancer through the Gleason high＿risk group and the Medium＿low risk group,and to find the genes closely related to the progression of CRPC.Using the STRING for functional protein association network analysis,we searched for hub genes closely related to the clinical TNM stage and the progression-free survival of prostate cancer,and then explored the relationship between hub genes and tumor microenvironment through GSEA functional enrichment and immune difference.At the same time,the same results were verified by immunohistochemistry using clinical patient specimens(N=262)collected by our center.Finally,LASSO Cox regression was used to construct a predictive model for predicting CRPC progression in clinical patients(N =190)with complete follow-up information collected by our center.[Results]Differential genes closely related to the progression of prostate cancer were screened between the Gleason high-risk group and the Medium＿low risk group,which were also closely related to the progression of CRPC.After using STRING for functional protein association network analysis,it was found that the hub gene KIF2 C was closely related to the clinical TNM stage and the progression-free survival of prostate cancer.Then KIF2 C was identified as the core gene of this study.Through the difference of immune cell infiltration and immune function enrichment,it was found that KIF2 C was closely related to regulatory T cells(Tregs).The same conclusion was also verified by immunohistochemistry of clinical case sections collected by our center.In addition,in the clinical patient specimens collected by our center,a CRPC prediction model(CRPCHS)that can effectively predict the progression of CRPC in patients with prostate cancer was constructed using clinical T.N.M stage,KIF2 C and TREGS.Through systematic evaluation,the CRPSHS prediction model has good predictive value in predicting the progression of CRPC.[Conclusion]In patients with prostate cancer,the CRPCHS prediction model can predict the probability of CRPC progression in patients in advance,which is expected to provide strong evidence for clinical prostate cancer patients to choose specific treatment options and strive for more survival time for more patients.