Biomarker analyses from the phase III randomized CLEAR trial: lenvatinib plus pembrolizumab versus sunitinib in advanced renal cell carcinoma.

BACKGROUND: In CLEAR, lenvatinib + pembrolizumab (L + P) significantly improved efficacy versus sunitinib in first-line treatment of patients with advanced renal cell carcinoma (aRCC). We report results from CLEAR biomarker analyses. PATIENTS AND METHODS: Programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) and next-generation sequencing assays (whole exome sequencing/RNA sequencing) were carried out on archival tumor specimens. For IHC-derived/RNA sequencing analyses, a continuous analysis was carried out adjusting by Karnofsky performance status (KPS) score for: PD-L1 combined positive score (CPS) versus best overall response (BOR)/progression-free survival (PFS); and each gene signature score [T-cell inflamed gene expression profile (TcellinfGEP)/non-TcellinfGEP signatures including proliferation and angiogenesis] versus BOR/PFS. Association between mutation status of RCC driver genes and PFS were analyzed for genes for which ≥20 patients per arm had oncogenic alterations. Association of molecular subtypes with outcome was evaluated with baseline KPS adjustments. The set of biomarkers evaluated and statistical significance criteria for PD-L1 CPS, gene signature scores, and molecular subtypes were prespecified. RESULTS: Within-arm analyses using continuous values showed no association between PD-L1 levels and BOR/PFS for either treatment. PFS hazard ratios between arms were similar regardless of the mutant or wild-type subgroups of RCC driver genes (VHL, PBRM1, SETD2, BAP1, KDM5C). No associations between PFS and gene signature scores were observed for L + P. With sunitinib, high proliferation and MYC signature scores showed shorter PFS; high angiogenesis and microvessel density signature scores showed longer PFS. Six new molecular subtypes were defined. Tumors of patients with favorable/intermediate risk were enriched in angiogenesis and angiogenesis/stromal clusters; those with poor risk were enriched in proliferative and unclassified (low-TcellinfGEP/low-angiogenesis/low-proliferation) clusters. No association between molecular subtypes and PFS for L + P/sunitinib was observed (after adjustment for KPS and gene signatures that were individually associated with PFS). CONCLUSIONS: Improvements in objective response rate and PFS for L + P versus sunitinib in aRCC were observed consistently across a range of biomarker subgroups defined using RCC driver mutations, PD-L1, gene expression signatures, and molecular subtypes.

Duke Scholars

Author Stephen L. George Biostatistics & Bioinformatics, Division of Biostatistics