ABSTRACT
PURPOSE: The field of immunotherapy combinations for advanced renal cell carcinoma (aRCC) has been expanded in recent years. However, the treatment response varies widely among individual patients. It is still a challenge to predict oncological outcome in clinical practice. We assessed the impact of an activated immune system reflected by changes in C-reactive protein (CRP) levels and the early onset of treatment-related adverse events (TRAEs) on the treatment response. METHODS: In this retrospective analysis of 57 aRCC patients, CRP kinetics based on previous descriptions of CRP flare-response, CRP response or CRP non-response, and the TRAEs, which occurred within a month after therapy initiation, were obtained for this study. According to logistic regression analysis of both factors, we stratified the patients into risk groups: the presence of CRP flare-response/response and early onset of TRAE (low-risk group); the presence of a single factor (intermediate-risk group); and without both factors (high-risk group). RESULTS: Ten patients (17%) experienced primary disease progression. No progressive disease was observed in the low-risk group, while 60% (n = 6/10) of the high-risk group showed a primary disease progression. Significantly, an increased risk of disease progression was observed by patients without CRP response and TRAEs (p < 0.001). CONCLUSION: The present analysis displays the predictive value of the on-treatment risk model based on CRP kinetics and the early onset of TRAEs, which can be easy to implement in clinical practice to optimize the treatment monitoring.
Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Humans , Carcinoma, Renal Cell/drug therapy , Kidney Neoplasms/drug therapy , Retrospective Studies , C-Reactive Protein/metabolism , Disease ProgressionABSTRACT
OBJECTIVE: To evaluate predictive ability of a novel combined index, Charlson comorbidity index and C-reactive protein (CCI-CRP), for outcomes in renal cell carcinoma (RCC), and compare predictive outcomes with of CCI-CRP to its separate components and to the UCLA integrated staging system (UISS). PATIENTS AND METHODS: We retrospectively analyzed INMARC registry of RCC patients. Receiver Operator Characteristics (ROC) analysis was fitted to identify threshold defining low-CRP (LCRP) and high-CRP (HCRP). Patients were stratified according to CCI [low-CCI ≤ 3 (LCCI); intermediate-CCI 4-6 (ICCI); high-CCI > 6 (HCCI)] and CRP level. Kaplan-Meier analysis (KMA) was conducted for overall (OS) and cancer-specific survival (CSS). Based on survival analysis distribution we proposed a new stratification: CCI-CRP. Model performance was assessed with ROC/area under the curve (AUC) analysis and compared to CCI and CRP alone, and UISS. RESULTS: We analyzed 2,890 patients (median follow-up 30 months). ROC identified maximum product sensitivity and specificity for CRP at 3.5 mg/L. KMA revealed 5-year OS of 95.6% for LCRP/LCCI, 83% LCRP/ICCI, 73.3% LCRP/HCCI, 62.6% HCRP/LCCI, 51.6% HCRP/ICCI and 40.5% HCRP/HCCI (P < .001). From this distribution, new CCI-CRP is proposed: low CCI-CRP (LCRP/LCCI and LCRP/ICCI), intermediate CCI-CRP (LCRP/HCCI and HCRP/LCCI), and high CCI-CRP (HCRP/ICCI and HCRP/HCCI). AUC for CCI-CRP showed improved performance for predicting OS/CSS vs. CCI alone (0.73 vs. 0.63/0.77 vs. 0.60), CRP alone (0.73 vs. 0.71/0.77 vs. 0.74) and UISS (0.73 vs 0.67/0.77 vs 0.73). CONCLUSIONS: CCI-CRP, exhibits increased prognostic performance for survival outcomes in RCC compared to CCI and CRP alone, and UISS. Further investigation is requisite.
ABSTRACT
PURPOSE: Given the emergence of PSMA-targeted diagnostic agents and therapeutics, we sought to investigate patterns of FOLH1 expression in RCC and their impacts on RCC outcomes. METHODS: We conducted a pooled multi-institutional analysis of patients with RCC having undergone DNA and RNA next-generation sequencing. FOLH1-high/low expression was defined as the ≥75th/<25th percentile of RNA transcripts per million (TPM). Angiogenic, T-effector, and myeloid expression signatures were calculated using previously defined gene sets. Kaplan-Meier estimates were calculated from the time of tissue collection or therapy start. RESULTS: We included 1,724 patients in the analysis. FOLH1 expression was significantly higher in clear cell (71%) compared to non-clear cell RCC tumors (19.0 versus 3.3 TPM, p < 0.001) and varied by specimen site (45% primary kidney/55% metastasis, 13.6 versus 9.9 TPM, p < 0.001). FOLH1 expression was correlated with angiogenic gene expression (Spearman = 0.76, p < 0.001) and endothelial cell abundance (Spearman = 0.76, p < 0.001). While OS was similar in patients with FOLH1-high versus -low ccRCC, patients with FOLH1-high clear cell tumors experienced a longer time on cabozantinib treatment (9.7 versus 4.6 months, respectively, HR 0.57, 95% CI 0.35-0.93, p < 0.05). CONCLUSIONS: We observed differential patterns of FOLH1 expression based on histology and tumor site in RCC. FOLH1 was correlated with angiogenic gene expression, increased OS, and a longer duration of cabozantinib treatment.