Definition of an Immune Signature Predictive of Anti-PD1 (Programmed Death-1) Antibody in the Treatment of Advanced Melanoma

Malignant Melanoma

AntiPD1

Melanoma is the most aggressive skin cancer. Major advances in metastatic melanoma treatment emerge from new immunotherapies that target specific immune inhibitory checkpoint receptors, mainly PD1 and CTLA-4, and overcome the exhaustion state of T cells. In this context, checkpoint inhibitors, such as Ipilimumab (anti-CTLA-4 monoclonal antibodies, mAb) and Nivolumab or Pembrolizumab (anti-PD1 mAb), have demonstrated survival benefit in advanced melanoma patients. Anti-PD1 agents and combination of anti-PD1 and anti CTLA-4 have now been approved as first line therapy in melanoma. However, the predictive factors of response to these immunotherapies remain so far elusive. Recent studies provided consistent evidence that the immune infiltration could be tested as a biomarker for such immunotherapies. Moreover, the very recent concept of tumor neoantigens as biomarkers of response to anti-CTLA-4 mAb, and potentially also to anti-PD1 or combination therapies, is promising but needs to be further explored. In this context, the aim of our program is to identify and validate an immune signature predictive of anti-PD-1 benefit in the treatment of advanced melanoma patients. To this aim, tumor samples from 120 melanoma patients enrolled prospectively, treated with anti-PD1 mAb alone or combined with anti CTLA4, will be collected as well as the corresponding peripheral blood mononuclear cells (PBMC). Tumor infiltration with immune cells will be characterized on paraffin embedded melanoma samples. The investigators will also perform whole-exome sequencing on tumors and matched PBMC samples. Our primary objective is to develop a combined immuno-signature based on an immuno-score (CD3, CD8, CD45RO…) to quantify the in situ immune populations with a dedicated image analysis system combined with the simultaneous detection of CD8-PD-1 and PD-L1 by immunofluorescence in baseline tumor samples. This will permit to predict 1-year survival of patients with advanced melanoma treated with anti-PD1 and transfer in patient's care. Our secondary objectives are: 1/ To assess the interest of the detection of tissue-resident memory (TRM) T cells (CD8-CD103) as a predictive biomarker of response and survival at 1-year; 2/ To extend the panel of neoantigens published by Snyder et al to other neoantigens using a next-generation sequencing (NGS) approach on tumor samples obtained before therapy; 3/ To establish the prognostic value of this panel of neoantigens to predict tumor response to anti-PD1 and 1-year survival; 4/ To functionally validate the identified tumor neoantigens by stimulating patient PBMC with neoantigen peptides and measuring tumor-specific T-cell reactivity; 5/ To define the best marker and/or the best combination of markers predicting the overall response rate and the survival at 12 and 18 months; 6/ To attempt to establish a correlation between immuno-signature and neoepitopes and 7/ To transfer this immune signature in routine basis if validated. Thus, our project will integrate two complementary strategies to define a robust and reliable score system for predicting anti-PD1 targeting immunotherapy response. This study will provide a unique opportunity to validate various putative biomarkers in an integrated way that could help in determining the respective value of each isolated parameter and potentially lead to the definition of a composite biomarker. The identified immune signature would be of major interest in the field of cancer immunotherapy in order to select and manage patient treatment, and to consider the benefice or toxicities expected. It will also help to identify new target antigens of effective antitumoral immune responses and to understand the resistance mechanisms established by the tumor and its influence on the response to current immunotherapies.

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