Malignant Melanoma Clinical Trial
Official title:
Definition and Validation of an Immune Signature Predictive of Anti-PD1 Antibody Used Alone or an Association With antiCTLA4 in the Treatment of Advanced Melanoma : PREDIMEL
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.
n/a
Observational Model: Cohort, Time Perspective: Prospective
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