Editor's Note: In recent years, significant progress has been made in the treatment of renal cell carcinoma (RCC). However, selecting the appropriate treatment strategy remains a critical challenge. Traditional tumor markers have limited predictive value in RCC, making the search for new and reliable biomarkers to guide treatment decisions a hot topic in RCC research. As one of the major oncology events of 2024, the ASCO Annual Meeting is set to take place soon. Oncology Outlook has invited Professor Guohai Shi from Fudan University Cancer Hospital to share the major research findings on kidney cancer biomarkers that will be presented at the conference.

Biomarker Analysis of Pembrolizumab Plus Axitinib vs. Sunitinib in Advanced Renal Cell Carcinoma in the Phase 3 KEYNOTE-426 Study (Abstract 4505)

Background: The KEYNOTE-426 study demonstrated that pembrolizumab plus axitinib improved OS, PFS, and ORR compared to sunitinib as first-line treatment for advanced RCC. This exploratory analysis investigated relevant biomarkers, including RNAseq, WES, and PD-L1.

Methods: Patients with previously untreated advanced RCC were randomized 1:1 to receive pembrolizumab plus axitinib or sunitinib. The association between T-cell inflammation gene profile (TcellinfGEP), angiogenesis gene profile (RNAseq), PD-L1 CPS (22C3 IHC), and clinical outcomes was analyzed at α=0.05. Other RNA characteristics and molecular subtypes based on the IMmotion151 study were analyzed at α=0.10.

Results: Among 861 patients, RNAseq archival samples were available for 369 and 361 patients in the combination and sunitinib groups, respectively, and WES samples for 347 and 351 patients, respectively. In the sunitinib group, PD-L1 CPS was negatively correlated with OS (P=0.013). In the pembrolizumab plus axitinib group, TcellinfGEP was significantly positively correlated with OS (P=0.003), PFS (P<0.0001), and ORR (P<0.0001), while angiogenesis was positively correlated with OS (P=0.013). In the sunitinib group, angiogenesis was positively correlated with OS (P<0.0001), PFS (P<0.001), and ORR (P=0.002). Other RNA characteristics showed that mMDSC was positively correlated with PFS (P=0.018) and ORR (P=0.093) in the combination group. Hypoxia was positively correlated with OS (P=0.034) and ORR (P=0.071), and MYC was negatively correlated with OS (P<0.001) and PFS (P=0.012) in the sunitinib group. Proliferation was also negatively correlated with OS (P=0.002). ORR was higher in the combination group across all molecular clusters, with the highest ORR in the immune/proliferation cluster. WES analysis showed that PBRM1 mutations were positively correlated with ORR (P=0.004) and PFS (P=0.079) in the combination group. In the sunitinib group, VHL (P=0.073) and PBRM1 (P=0.001) were positively correlated with OS, while BAP1 mutations (P=0.046) were negatively correlated with OS. The combination group showed improved ORR regardless of mutation status.

Conclusion: TcellinfGEP was strongly correlated with clinical outcomes in the pembrolizumab plus axitinib group. Angiogenesis was positively correlated with outcomes in the sunitinib group and only with OS in the combination group. Understanding the role of the immune microenvironment in combination therapy is crucial for improving treatment strategies.