BACKGROUND According to current statistics,renal cancer accounts for 3%of all cancers world-wide.Renal cell carcinoma(RCC)is the most common solid lesion in the kidney and accounts for approximately 90%of all renal ma...BACKGROUND According to current statistics,renal cancer accounts for 3%of all cancers world-wide.Renal cell carcinoma(RCC)is the most common solid lesion in the kidney and accounts for approximately 90%of all renal malignancies.Increasing evi-dence has shown an association between immune infiltration in RCC and clinical outcomes.To discover possible targets for the immune system,we investigated the link between tumor-infiltrating immune cells(TIICs)and the prognosis of RCC.AIM To investigate the effects of 22 TIICs on the prognosis of RCC patients and iden-tify potential therapeutic targets for RCC immunotherapy.METHODS The CIBERSORT algorithm partitioned the 22 TIICs from the Cancer Genome Atlas cohort into proportions.Cox regression analysis was employed to evaluate the impact of 22 TIICs on the probability of developing RCC.A predictive model for immunological risk was developed by analyzing the statistical relationship between the subpopulations of TIICs and survival outcomes.Furthermore,multi-variate Cox regression analysis was used to investigate independent factors for the prognostic prediction of RCC.A value of P<0.05 was regarded as statistically significant.RESULTS Compared to normal tissues,RCC tissues exhibited a distinct infiltration of im-mune cells.An immune risk score model was established and univariate Cox regression analysis revealed a significant association between four immune cell types and the survival risk connected to RCC.High-risk individuals were correlated to poorer outcomes according to the Kaplan-Meier survival curve(P=1E-05).The immunological risk score model was demonstrated to be a dependable predictor of survival risk(area under the curve=0.747)via the receiver operating characteristic curve.According to multivariate Cox regression analysis,the immune risk score model independently predicted RCC patients'prognosis(hazard ratio=1.550,95%CI:1.342–1.791;P<0.001).Finally,we established a nomogram that accurately and comprehensively forecast the survival of patients with RCC.CONCLUSION TIICs play various roles in RCC prognosis.The immunological risk score is an independent predictor of poor survival in kidney cancer cases.展开更多
基金Supported by The Medical Scientific Research Project of the Jiangsu Health Commission,China,No.M2020055The Nanjing Medical Science and Technology Development Project,China,No.YKK22130The Postgraduate Research and Practice Innovation Program of Jiangsu Province,China,No.KYCX23_2105.
文摘BACKGROUND According to current statistics,renal cancer accounts for 3%of all cancers world-wide.Renal cell carcinoma(RCC)is the most common solid lesion in the kidney and accounts for approximately 90%of all renal malignancies.Increasing evi-dence has shown an association between immune infiltration in RCC and clinical outcomes.To discover possible targets for the immune system,we investigated the link between tumor-infiltrating immune cells(TIICs)and the prognosis of RCC.AIM To investigate the effects of 22 TIICs on the prognosis of RCC patients and iden-tify potential therapeutic targets for RCC immunotherapy.METHODS The CIBERSORT algorithm partitioned the 22 TIICs from the Cancer Genome Atlas cohort into proportions.Cox regression analysis was employed to evaluate the impact of 22 TIICs on the probability of developing RCC.A predictive model for immunological risk was developed by analyzing the statistical relationship between the subpopulations of TIICs and survival outcomes.Furthermore,multi-variate Cox regression analysis was used to investigate independent factors for the prognostic prediction of RCC.A value of P<0.05 was regarded as statistically significant.RESULTS Compared to normal tissues,RCC tissues exhibited a distinct infiltration of im-mune cells.An immune risk score model was established and univariate Cox regression analysis revealed a significant association between four immune cell types and the survival risk connected to RCC.High-risk individuals were correlated to poorer outcomes according to the Kaplan-Meier survival curve(P=1E-05).The immunological risk score model was demonstrated to be a dependable predictor of survival risk(area under the curve=0.747)via the receiver operating characteristic curve.According to multivariate Cox regression analysis,the immune risk score model independently predicted RCC patients'prognosis(hazard ratio=1.550,95%CI:1.342–1.791;P<0.001).Finally,we established a nomogram that accurately and comprehensively forecast the survival of patients with RCC.CONCLUSION TIICs play various roles in RCC prognosis.The immunological risk score is an independent predictor of poor survival in kidney cancer cases.
