Generation of an Artificial Intelligence Algorithm Based on the Analysis of Melanoma Peri-scar Dermatoheliosis, as a Predictive Factor of Response to Anti-PD-1

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorNantes University Hospital

About this trial

In the last decade, the advent of immunotherapies with inhibitors of immune checkpoints, such as anti-PD-1 and anti-CTLA-4, has revolutionized the treatment of advanced or metastatic melanoma. However, the clinical benefit remains limited to a subset of patients. Identifying the patients most likely to benefit from these novel therapies (and avoiding unnecessary toxicity in non-responding patients) is therefore critical. Previous studies found a significant link between the high mutational load of a tumor (TMB) and its response to anti-PD-1 monotherapy, regardless of the histological type of cancer. Unfortunately, TMB measurement is expensive, and requires extensive sequencing approaches difficult to implement in clinical practice. I have shown that melanomas known to be secondary to mutagenic ultraviolet rays (UVR) often carry a high TMB. The cumulative UVR damage translates into visible stigmas termed "dermatoheliosis" on patients' skin, easy to recognize with the naked eye of the clinician around the scar of the primary melanoma. My project proposes to establish, for the first time, dermatoheliosis as a novel predictive factor of response to anti-PD-1 immunotherapy, to be used within multidisciplinary tumor boards as a powerful decision-support tool to select the best treatment option. Specifically, I will 1) develop, validate and test in a prospective manner, an artificial intelligence (AI)-based algorithm, to assess features of pericicatricial dermatoheliosis based on a collection of photographs obtained from patients with unresectable locally advanced or metastatic melanoma 2) demonstrate the link between dermatoheliosis, TMB, immune and treatment response by characterizing pericicatricial skin single cell transcriptomics, as well as tumor DNA, RNA and host immunological profiles of the patients. This directly accessible, non-invasive, surrogate marker for TMB will be a game changer in clinical practice and will subsequently be translated to other skin cancers.

Eligibility criteria

Qualifiers

None

Disqualifiers

Retrospective cohort: Patients who have received curative treatment with anti-PD-1, +/- anti-CTLA-4 or anti-LAG-3 for skin cancer for less than 90 days

Patients who received adjuvant immunotherapy within 6 months prior to curative treatment

Patients who received chemotherapy prior to curative treatment

Patients whose primary skin cancer site cannot be photographed (e.g. choroidal melanomas, mucosal melanomas, with the exception of vulvar or penile melanomas, etc.).

Trial design

Treatments tested in this trial

  • Photo

Treatment groups

700 Participants
are divided into 2 treatment groups

Sponsors and collaborators