23P Immunological signature meta-analysis across lung cancer cohorts within the NanoString Clinical Transcriptional Atlas Group (CTAG) associated with patient outcome and history. (15th December 2019) - Radosevic-Robin, N; Reeves, J; Leroy, K; Duruisseaux, M; Morel, P; Bhagat, M; Penault-Llorca, F; Damotte, D; Goldwasser, F; Brindel, A; Cumberbatch, M; Ong, S; et al.
Abstract: Background: With the approval of anti-PD1 blocking antibodies in a growing number of indications, understanding the mechanisms responsible for potentiating response to these agents has been a critical avenue of research. However, most studies rely on the use of single cohorts and are relatively limited in their scope, thus limited their utility. Methods: We created a consortium of investigators who share clinical and accompanying transcriptional data collected on the NanoString® nCounter® platform from patients treated with single agent immunotherapy to facilitate biomarker research. In this study, we apply a meta-analysis to a combined cohort of 4 lung cancer studies (n = 150) to identify transcriptional correlates of response to identify patients who are likely to experience clinical benefit. Results: RNA was profiled with the NanoString IO360 and IO360 beta gene expression panels, and 43 signatures that describe facets of the immune response, tumor biology, and the tumor microenvironment were calculated. Included in these signatures is the Tumor Inflammation Signature (TIS), an investigational 18 gene signature of a suppressed adaptive immune response which enriches for clinical response to pembrolizumab. These signatures, as well as genes of interest identified in a given cohort, were compared to objective response, overall survival, or progression free survival across the cohorts. We confirm previously reported association of TIS with patient outcome and identify immune cell subsets that are also associated with response. In addition, we examine differences between patients with distinct mutational backgrounds, smoking histories, or histological classifications, as well as differences attributable to biopsy location. Conclusion: This multi-cohort study allows for the development of multi-variate predictors of response to anti-PD1 monotherapy using a single research assay to transcriptionally profile the tumors. We can generate robust predictions from real-world cohorts, which may lead to the development of improved diagnostic assays to guide treatment decisions. Legal entity responsible for the study: NanoString Technologies. Funding: NanoString Technologies. Disclosure: N. Radosevic-Robin: Research grant / Funding (institution): NanoString Technologies. J. Reeves: Full / Part-time employment: NanoString Technologies. K. Leroy: Research grant / Funding (self): NanoString Technologies. M. Duruisseaux: Research grant / Funding (self): NanoString Technologies. P. Morel: Full / Part-time employment: NanoString Technologies. M. Bhagat: Research grant / Funding (institution): NanoString Technologies. F. Penault-Llorca: Advisory / Consultancy, Research grant / Funding (institution): NanoString Technologies. D. Damotte: Research grant / Funding (institution): NanoString Technologies. F. Goldwasser: Research grant / Funding (institution): NanoString Technologies. A. Brindel: Research grant / Funding (institution): NanoString Technologies. M. Cumberbatch: Research grant / Funding (institution): NanoString Technologies. S. Ong: Full / Part-time employment: NanoString Technologies. J. Lopez: Research grant / Funding (institution): NanoString Technologies. S. Warren: Full / Part-time employment: NanoString Technologies.