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

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