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Saturday, 09/09/2017 1:40:03 PM

Saturday, September 09, 2017 1:40:03 PM

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Somatic Mutations and Neoepitope Homology in Melanomas Treated with CTLA-4 Blockade

Tavi Nathanson, Arun Ahuja, Alexander Rubinsteyn, Bulent Arman Aksoy, Matthew D. Hellmann, Diana Miao, Eliezer Van Allen, Taha Merghoub, Jedd D. Wolchok, Alexandra Snyderand Jeff Hammerbacher

DOI: 10.1158/2326-6066.CIR-16-0019 Published January 2017

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Abstract

Immune checkpoint inhibitors are promising treatments for patients with a variety of malignancies. Toward understanding the determinants of response to immune checkpoint inhibitors, it was previously demonstrated that the presence of somatic mutations is associated with benefit from checkpoint inhibition. A hypothesis was posited that neoantigen homology to pathogens may in part explain the link between somatic mutations and response. To further examine this hypothesis, we reanalyzed cancer exome data obtained from our previously published study of 64 melanoma patients treated with CTLA-4 blockade and a new dataset of RNA-Seq data from 24 of these patients. We found that the ability to accurately predict patient benefit did not increase as the analysis narrowed from somatic mutation burden, to inclusion of only those mutations predicted to be MHC class I neoantigens, to only including those neoantigens that were expressed or that had homology to pathogens. The only association between somatic mutation burden and response was found when examining samples obtained prior to treatment. Neoantigen and expressed neoantigen burden were also associated with response, but neither was more predictive than somatic mutation burden. Neither the previously described tetrapeptide signature nor an updated method to evaluate neoepitope homology to pathogens was more predictive than mutation burden. Cancer Immunol Res; 5(1); 84–91. ©2016 AACR.

Introduction

Checkpoint blockade therapies are improving outcomes for patients with metastatic solid tumors (1–4). As only a subset of patients responds, there is a critical need to identify determinants of response. Expression of programmed death ligand one (PD-L1) is the lead companion diagnostic for PD-1/PD-L1 blockade therapies, but sensitivity and specificity are limited (5–7). An association between elevated tumor mutation burden and benefit from checkpoint blockade therapies has been demonstrated (8–11).

In our study of melanomas treated with checkpoint blockade agents targeting cytotoxic T-lymphocyte associated protein 4 (CTLA-4; ref. 8), we present the hypothesis that responding tumors may share features with each other or with infectious agents and that such resemblance may predict response. In this report, we reanalyzed the data in that study using updated methods and integrating new RNA sequencing (RNA-Seq) data from a subset of 24 samples.

We found that in this small dataset, nonsynonymous mutation burden was associated with clinical benefit from therapy in samples collected before, but not after, treatment with CTLA-4 blockade. Predicted neoantigen burden and percentage of C?T transitions characteristic of ultraviolet damage were associated with, but did not outperform, mutation burden. We developed a publicly available tool, Topeology (https://github.com/hammerlab/topeology), to compare neoantigens to known pathogens. Neither the resemblance of tumor neoantigens to known antigens nor the previously published tetrapeptide signature outperformed mutation burden as a predictor of response.

Materials and Methods

Patient samples

All analyzed samples were collected in accordance with local Internal Review Board policies as described in ref. 8 and summarized in Table 1. Thirty-four patients had tumor samples collected prior to initiating CTLA-4 blockade, and 30 patients had samples collected after initiating CTLA-4 blockade. Clinical benefit was defined as progression-free survival lasting for greater than 24 weeks after initiation of therapy (Online Data File 1). Nine discordant lesions were present, where overall patient benefit did not match individual tumor progression. See Table 1 for details about this patient cohort.

http://cancerimmunolres.aacrjournals.org/content/5/1/84.long

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