Gene signatures of tumor inflammation and epithelial-to-mesenchymal transition (EMT) predict responses to immune checkpoint blockade in lung cancer with high accuracy. (January 2020)

• Record Type: Journal Article
• Authors: Thompson, Jeffrey C.; Hwang, Wei-Ting; Davis, Christiana; Deshpande, Charuhas; Jeffries, Seth; Rajpurohit, Yashoda; Krishna, Vinod; Smirnov, Denis; Verona, Raluca; Lorenzi, Matthew V.; Langer, Corey J.; Albelda, Steven M.
• Is Part Of: Lung cancer. Volume 139(2020)
• Page Start: 1
• Page End: 8
• Publication Date: 2020-01
• Subjects: Non-small cell lung cancer -- Immunotherapy -- Gene signatures -- Cancer biomarkers; Lungs -- Cancer -- Periodicals; Lung Neoplasms -- Abstracts; Lung Neoplasms -- Periodicals; Poumons -- Cancer -- Périodiques; Lungs -- Cancer; Periodicals; Electronic journals; Electronic journals; 616.99424
• DOI: 10.1016/j.lungcan.2019.10.012
• Languages: English
• ISSNs: 0169-5002

Abstract

Highlights: Evaluation of gene signatures to predict response to immunotherapy in NSCLC. An EMT/Inflammation score was highly predictive of response and survival to ICB. Identifies potential role of EMT in primary resistance to immunotherapy in NSCLC. Abstract: Objectives: Treatment of non-small cell lung cancer (NSCLC) with immune checkpoint blockade (ICB) has resulted in striking clinical responses, but only in a subset of patients. The goal of this study was to evaluate transcriptional signatures previously reported in the literature in an independent cohort of NSCLC patients receiving ICB. Materials and methods: This retrospective study analyzed transcriptional profiles from pre-treatment tumor samples of 52 chemotherapy-refractory advanced NSCLC patients treated with anti-PD1/PD-L1 therapy. Gene signatures based on published reports were created and examined for their association with response to therapy and progression-free and overall survival (PFS, OS). Results: Two signatures predicting response and outcomes were identified. One reflected the degree of immune infiltration and upregulation of interferon-gamma-induced genes. A second reflected the EMT status. Compared to those not responding to therapy, patients whose tumors responded to ICB had higher scores in an inflammatory gene signature (6.0 ± 2.9 vs -5.5 ± 3.4, p = 0.014) or a more epithelial phenotype (-1.7 ± 1.0 vs 2.1 ± 1.2, p = 0.016). Both signatures demonstrated a satisfactory predictive accuracy for response: AUC of 0.69 (95% CI: 0.54, 0.84) for the inflammatory and 0.70 (95% CI: 0.55, 0.85) for EMT signatures, respectively. A weighted score combining EMT and inflammatory signatures showed increased predictive value with AUC of 0.92 (95% CI: 0.85, 0.99). Kaplan-Meier curves for patients above and below the median combined score showed a significant separation for PFS and OS (all p < 0.01, log rank test). Conclusions: The EMT/Inflammation signature score may be useful in directing checkpoint inhibitor therapy in lung cancer and suggests that reversal of EMT might augment efficacy of ICB.