RNASeq2 level III RSEM data from RCC patients included in the international initiative “The Cancer Genome Atlas” (TCGA), were obtained using the Bioconductor package TCGA2STAT. Analyses were performed with the Log2 transformed RSEM values.

For the study of biomarkers in our cohort of patients, sample size calculation was estimated based on a pivotal phase III trial and a response rate of 40% [23]. Assuming 10% dropout rate, 80% power and 5% risk alpha, the sample size would correspond to 53 patients. Overall response rate (ORR) (complete response [CR] + partial response [PR]) was reported using descriptive statistics with 95% confidence intervals (CI). Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan–Meier method. High or low levels of the biomarkers were established based on the median. To evaluate the effect of each biomarker on endpoints, Cox’s proportional hazards regression was used. Comparisons of circulating levels of cytokines/chemokines between responders and non-responders at baseline and 3 months post-treatment were performed with the Mann–Whitney U test. Correlation between biomarkers was evaluated by the Spearman’s test. We also generated a prognostic index (PI) including levels of HGF, IL-6, CXCL10 and CXCL11, using Cox’s regression analysis. The formulated PI was defined as the sum of the products of the B coefficient for each cytokine and its expression value (pg/mL). The discriminative ability of the PI was assessed by the use of Harrell’s concordance coefficient (C-index).

SPSS15.0 (Madrid, Spain), STATA/IC 12.1 (College Station, TX, USA) and GraphPad Prism 5 software (GraphPad) were used for statistical analysis and/or representation of the results. Data are expressed as means ± SD, statistical assessments were two-sided and p-values < 0.05 were deemed significant.

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