A Dysfunctional T-cell Gene Signature for Predicting Nonresponse to PD-1 Blockade in Non-small Cell Lung Cancer That Is Suitable for Routine Clinical Diagnostics

• Published in: Clinical cancer research 2024-02, Vol.30 (4), p.814-823
• Main Authors: Hummelink, Karlijn, Tissier, Renaud, Bosch, Linda J W, Krijgsman, Oscar, van den Heuvel, Michel M, Theelen, Willemijn S M E, Damotte, Diane, Goldwasser, François, Leroy, Karen, Smit, Egbert F, Meijer, Gerrit A, Thommen, Daniela S, Monkhorst, Kim
• Format: Article
• Language: English
• Subjects: B7-H1 Antigen - metabolism; Carcinoma, Non-Small-Cell Lung - diagnosis; Carcinoma, Non-Small-Cell Lung - drug therapy; Carcinoma, Non-Small-Cell Lung - genetics; Humans; Lung Neoplasms - diagnosis; Lung Neoplasms - drug therapy; Lung Neoplasms - genetics; Lymphocytes, Tumor-Infiltrating - metabolism; Programmed Cell Death 1 Receptor - genetics; Programmed Cell Death 1 Receptor - therapeutic use; RNA, Messenger - genetics; Treatment Outcome
• ISSN: 1078-0432; 1557-3265; 1557-3265
• DOI: 10.1158/1078-0432.CCR-23-1061

Because PD-1 blockade is only effective in a minority of patients with advanced-stage non-small cell lung cancer (NSCLC), biomarkers are needed to guide treatment decisions. Tumor infiltration by PD-1T tumor-infiltrating lymphocytes (TIL), a dysfunctional TIL pool with tumor-reactive capacity, can be detected by digital quantitative IHC and has been established as a novel predictive biomarker in NSCLC. To facilitate translation of this biomarker to the clinic, we aimed to develop a robust RNA signature reflecting a tumor's PD-1T TIL status. mRNA expression analysis using the NanoString nCounter platform was performed in baseline tumor samples from 41 patients with advanced-stage NSCLC treated with nivolumab that were selected on the basis of PD-1T TIL infiltration by IHC. Samples were included as a training cohort (n = 41) to develop a predictive gene signature. This signature was independently validated in a second cohort (n = 42). Primary outcome was disease control at 12 months (DC 12 m), and secondary outcome was progression-free and overall survival. Regularized regression analysis yielded a signature using 12 out of 56 differentially expressed genes between PD-1T IHC-high tumors from patients with DC 12 m and PD-1T IHC-low tumors from patients with progressive disease (PD). In the validation cohort, 6/6 (100%) patients with DC 12 m and 23/36 (64%) with PD were correctly classified with a negative predictive value (NPV) of 100% and a positive predictive value of 32%. The PD-1T mRNA signature showed a similar high sensitivity and high NPV as the digital IHC quantification of PD-1T TIL. This finding provides a straightforward approach allowing for easy implementation in a routine diagnostic clinical setting.