Biomarkers before and after nephrectomy of locally advanced or metastatic renal cell carcinoma (RCC) treated with everolimus: Neorad phase 2 trial (PREDICT consortium)

Abstract

Background: Although many drugs are available in RCC, we still lack predictive biomarkers of disease recurrence or progression for personalized treatment. NEORAD clinical trial (NCT01715935) was designed to evaluate biomarkers modulation by everolimus (Ev) prior to nephrectomy on several tissue and circulating cells. Method(s): French open-label, exploratory, single-arm, multicenter trial, part of PREDICT consortium. Population: locally-advanced (LA), metastatic (M) RCC. Endpoints: primary: objective clinical benefit (CR, PR, SD upon RECIST 1.1) after 6 weeks neoadjuvant Ev (10 mg daily) prior nephrectomy; secondary: PFS, OS, toxicity. Multi-region sequencing (biopsy and surgery specimens) explored mutational status of genes of interest. After nephrectomy, Ev was reintroduced inMpts until PD or end of 12m follow-up. Treatment was continued until PD or unacceptable toxicity. Result(s): 25 pts accrued (44 screened) between 05/2012 and 07/2015: LA=14, M=11 underwent biopsy at screening for tissue sampling then further nephrectomy. Population (LA/M): clear-cell=13/10, papillary=1/1, median age(y): 60/63, sarcomatoid component: 3Mpts, ECOG-PS: 0=10/4, 1=4/7, extra-renal metastatic sites: bone, lung, nodes, adrenal. Change in renal tumor size between baseline and D42: 0%. In M, Ev was resumed for 8 pts after nephrectomy with 2 PR and 6 SD. PFS (mo): M=3.1 [1.41; 12.2]. Median follow-up (mo): 17.4 [3.3; 43.2]. PFS at 12 months: LA=78%, M=18% Toxicity of Ev was as expected and no adverse event in terms of surgical procedure was observed. Pts with following gene mutations exhibited a poor PFS: SEDT2: HR=2.54 (0.63 - 10.28), BAP1: HR=3.19 (0.78 - 13.12), TSC2: HR=2.37 (0.49 - 11.53); further correlations will be presented at ESMO meeting. Conclusion(s): NEORAD was the 1st neoadjuvant study of Ev in RCC. Despite limited number of pts, we generated a large amount of longitudinal data including exome sequencing, circulating biomarkers, angiogenesis and immunity factors. All these data could help decipher mechanisms of resistance, evaluate predictive signatures or add further knowledge to mechanisms involved in mTOR pathways.