Researchers recently applied a previously established 27-gene classifier to renal cell carcinoma (RCC) to estimate the efficacy of immune checkpoint inhibitor (ICI) therapy for this condition. Their findings were presented in a poster at the 2021 American Society of Clinical Oncology (ASCO) Annual Meeting by Robert Seitz of Oncocyte Inc in Nashville, Tennessee, and colleagues.
The 27-gene binary classifier DetermaIOTM uses tumor immune microenvironment gene expression data to predict efficacy of ICI therapy. It was previously shown to predict ICI response in patients with triple-negative breast cancer, non-small cell lung cancer, and bladder cancer. In this study, the researchers applied the classifier to predict the efficacy of ICI therapy, defined as progression-free survival (PFS), in patients with RCC.
The researchers initially used data from The Cancer Genome Atlas (TCGA) pertaining to RCC for model development and comparison with classifier function in other cancer types. These data included gene expression information from 606 patients with RCC and survival outcomes from 575 patients with RCC. The model was then tested on RNA sequencing data retrieved from 43 patients with RCC who were treated with ICI agents, with the 2 most common treatment approaches being nivolumab and nivolumab plus ipilimumab.
In the analysis of patients treated with ICI agents, those categorized as having a positive immune-oncology (IO) signature using the classifier demonstrated superior 1-year PFS compared with patients who were considered to have a negative IO score (hazard ratio, 0.235; 95% CI, 0.069-0.803; P <.01). A positive IO score was also associated with a median PFS of 8.6 months, compared with 5.2 months for a negative IO score. Using survival data from TCGA, the model did not show an association with outcomes for patients treated with conventional (nonimmune) therapy.
The research team concluded that the classifier was able to identify response to ICI therapy in patients with RCC. “These data further support this assay as a potential pan-cancer classifier worthy of study in other tumor types,” Seitz said in a video accompanying the research team’s poster.
Disclosures: Some study authors declared affiliations with biotech, pharmaceutical, and/or device companies. Please see the original reference for a full list of authors’ disclosures.
Seitz R, Nielsen TJ, Schweitzer BL, Gandara DR, Parikh M, Ross DT. Association with immune checkpoint inhibitor efficacy of a 27-gene classifier in renal cell cancer. J Clin Oncol. 2021;39(suppl 15; abstr 4575). doi:10.1200/JCO.2021.39.15_suppl.4575