- Poster presentation
- Open Access
Relationship between immune gene signatures and clinical response to PD-1 blockade with pembrolizumab (MK-3475) in patients with advanced solid tumors
© Ayers et al. 2015
- Published: 4 November 2015
- Gastric Cancer
- Immune Checkpoint
- Advanced Solid Tumor
- Immune Signature
Immune checkpoint inhibition with anti–PD-1 monoclonal antibodies such as pembrolizumab has demonstrated robust, durable anti-tumor activity against many advanced malignancies. We analyzed immune-related gene expression profiles in pembrolizumab-treated patients with advanced solid tumors to identify immune gene signatures correlated with clinical benefit.
RNA was extracted from formalin-fixed, paraffin-embedded sections of baseline tumor samples and analyzed using a custom 680-gene set on the NanoString nCounter platform. A 10-gene preliminary “interferon-gamma” (IFN-γ) signature was developed in a discovery set of 19 patients with melanoma treated with pembrolizumab in the Phase 1b KEYNOTE-001 study (NCT01295827) and was later complemented with a 28-gene preliminary “expanded immune” signature. These 2 signatures were subsequently tested and refined in an independent cohort of 62 additional patients with melanoma treated in KEYNOTE-001. Further evaluation of the refined signatures was performed in 43 patients with head and neck squamous cell carcinoma (HNSCC) and 33 patients with gastric cancer enrolled in the Phase 1b KEYNOTE-012 study (NCT01848834).
Nominal 1-sided P values for ORR and PFS calculated from logistic and Cox regression, respectively, using signature score as a continuous variable.
Immune-related gene expression signatures composed of genes associated with T cell cytotoxic function, antigen presentation machinery, and IFN-γ signaling represent reproducible and sensitive tools that define common features of the immune microenvironment associated with response to pembrolizumab across multiple tumor types.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.