Tumor-infiltrating immune cells (TIICs) are crucial for the clinical outcome of renal cell carcinoma (RCC), as they regulate cancer progression. TIICs have therefore the potential to become novel targets of immunotherapies. The present study used CIBERSORT analytical tool, which is a deconvolution algorithm, to comprehensively analyze the composition of immune cells in RCC and normal tissues from The Cancer Genome Atlas (TCGA) cohort, and to determine the prognostic value of TIICs in RCC. A landscape of infiltrating immune cells was determined as containing 13 subpopulations of immune cells, with significant differences between normal and tumor tissues. Subsequently, Kaplan-Meier analysis and log-rank test were used to estimate the prognostic value of TIICs in RCC. The results demonstrated that a higher proportion of regulatory T cells (Tregs) [hazard ratio (HR)=1.596; 95% confidence interval (CI), 1.147-2.222; P=0.006] and follicular helper T cells (HR=1.516; 95% CI, 1.089-2.111; P=0.014) were associated with poor outcome in patients with RCC. Conversely, resting mast cells (HR=0.678; 95% CI, 0.487-0.943; P=0.021) and monocytes (HR=0.701; 95% CI, 0.503-0.977; P=0.036) were associated with a favorable prognosis in patients with RCC. Furthermore, the results from multivariate Cox regression analysis indicated that Tregs and monocytes represented independent risk factors for prognosis in patients with RCC. These findings demonstrated that gene profiling deconvolution by CIBERSORT served to determine the composition of immune cells infiltrated in RCC and may provide some crucial information for the development of immunotherapies.

Oncology letters. 2019 Sep 20 [Epub]

Gongmin Zhu, Lijiao Pei, Hubin Yin, Fan Lin, Xinyuan Li, Xin Zhu, Weiyang He, Xin Gou

Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P.R. China., The State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China.