Gene signatures of tumor inflammation and epithelial-to-mesenchymal transition (EMT) predict responses to immune checkpoint blockade in lung cancer with high accuracy.
By: Jeffrey C Thompson, Wei-Ting Hwang, Christiana Davis, Charuhas Deshpande, Seth Jeffries, Yashoda Rajpurohit, Vinod Krishna, Denis Smirnov, Raluca Verona, Matthew V Lorenzi, Corey J Langer, Steven M Albelda

Division of Pulmonary, Allergy and Critical Care Medicine, Thoracic Oncology Group, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States. Electronic address: jeffrey.thompson@uphs.upenn.edu.
2019-09-05; doi: 10.1016/j.lungcan.2019.10.012
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

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.



Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

PMID:31683225






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