Background: Immune checkpoint inhibitor (ICI) therapies represent a major advance in treating a variety of advanced-stage malignancies. Nevertheless, only a subset of patients benefit, even when selected based on approved biomarkers such as PD-L1 and tumor mutational burden. New biomarkers are needed to maximize the therapeutic ratio of these therapies.
Methods: In this retrospective cohort, we assessed a 27-gene RT-qPCR immuno-oncology (IO) gene expression assay of the tumor immune microenvironment and determined its association with the efficacy of ICI therapy in 67 advanced-stage NSCLC patients. The 27-gene IO test score (IO score), programmed cell death ligand 1 immunohistochemistry tumor proportion score (PD-L1 TPS), and tumor mutational burden (TMB) were analyzed as continuous variables for response and as binary variables for one-year progression free survival. The threshold for the IO score was prospectively set based upon a previously described training cohort. Prognostic implications of the IO score were evaluated in a separate cohort of 104 advanced-stage NSCLC patients from The Cancer Genome Atlas (TCGA) who received non-ICI therapy.
Results: The IO score was significantly different between responders or non-responders (p = 0.007) and associated with progression-free survival (p = 0.001). Bivariate analysis established that the IO score was independent of PD-L1 TPS and TMB in identifying patients benefiting from ICI therapy. In a separate cohort of late-stage NSCLC patients from TCGA, the IO score was not prognostic of outcome from non-ICI-treated patients.
Conclusions: This study is the first application of this 27-gene IO RT-qPCR assay in a clinical cohort with outcome data. IO scores were significantly associated with response to ICI therapy and prolonged progression-free survival. Together, these data suggest the IO score should be further studied to define its role in informing clinical decision-making for ICI treatment in NSCLC.
Keywords: Gene expression profiling; Immunotherapy; Programmed death ligand 1; Tumor biomarkers; Tumor microenvironment.
© 2022. The Author(s).