Effect of genetic polymorphisms on outcomes following nivolumab for advanced renal cell carcinoma in the SNiP-RCC trial.

Background: Anti-PD-1 antibodies are widely used for cancer treatment including advanced renal cell carcinoma (RCC). However, their therapeutic and adverse effects vary among patients. This study aimed to identify genetic markers that predict outcome after nivolumab anti-PD-1 antibody treatment for advanced RCC.

Methods: This study was registered on the website of the University Hospital Medical Information Network (protocol ID, UMIN000037739). Patient enrollment was conducted at 23 institutions in Japan between August 19, 2019, and September 30, 2020. Patient follow-up ended on March 31, 2021. Patients were treated with nivolumab for advanced clear cell RCC. A genome-wide association study was performed in the development set, while genotyping of target regions in the validation set was undertaken. Single nucleotide polymorphisms (SNPs) in genes of interest CD274, PDCD1LG2 and PDCD1 were genotyped in the combined set. The primary endpoint was the association of SNPs with objective response following nivolumab treatment. As secondary endpoints, the associations of SNPs with radiographic progression-free survival (rPFS) and treatment-related grade  ≥ 3 adverse events (AEs) were evaluated.

Results: A genome-wide association study followed by a validation study identified that SNPs in FARP1 (rs643896 and rs685736) were associated with objective response and rPFS but not AEs following nivolumab treatment. Furthermore, SNPs in PDCD1LG2 (rs822339 and rs1411262) were associated with objective response, rPFS, and AEs following nivolumab treatment. Genetic risk category determined according to the number of risk alleles in SNPs (rs643896 in FARP1 and rs4527932 in PDCD1LG2) excellently predicted objective response and rPFS in nivolumab treatment.

Conclusion: This study revealed that SNPs in FARP1 and PDCD1LG2 were correlated with outcome in nivolumab treatment. The use of these SNPs may be beneficial in selecting appropriate treatment for individual patients and may contribute to personalized medicine.