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Studies

Observational Recruiting

NCT05856565 on ClinicalTrials.gov

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

  • Sponsor: Centre Hospitalier Universitaire de Nantes
  • Enrollment: 700 (Estimated)
  • Study start: 2023-07-24 (Actual)
  • Primary completion: 2028-07-24 (Estimated)
  • Study completion: 2028-07-24 (Estimated)
  • Allocation: N/a
  • InterventionModel: N/a
  • Masking: None
  • PrimaryPurpose: Other

Brief Summary

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.

Conditions

  • Metastatic Melanoma

Intervention / Treatment

  • Other: Photo

Primary Outcome Measures

  • Predictive performance of tumor progression score (after 6 months)
    The predictive score for tumor progression at 6 months will be calculated from the photograph of the excision scar of the patient's primary tumor, as well as the clinical characteristics associated with the prognosis: patient age, sex, phototype, anatomical location and Breslow index of the primary tumour, stage of the skin cancer and WHO performance status at the initiation of the treatment, nature of the treatment administered

Countries

France

Locations and Investigators

  • Besancon University Hospital, Besançon, France (Recruiting)
  • Brest University Hospital, Brest, France (Recruiting)
    • Delphine LEGOUPIL, PH
    • Delphine LEGOUPIL (Principal Investigator)
  • Angers University Hospital, Angers, France (Recruiting)
    • Yannick LE CORRE, PH
    • Yannick LE CORRE (Principal Investigator)
  • Blois Hospital site, Blois, France (Not yet recruiting)
    • Guido BENS
    • Guido BENS (Principal Investigator)
  • Bordeaux University Hospital, Bordeaux, France (Not yet recruiting)
    • Emilie GERARD
    • Emilie GERARD (Principal Investigator)
  • Dijon University Hospital, Dijon, France (Not yet recruiting)
    • Géraldine JEUDY
    • Géraldine JEUDY (Principal Investigator)
  • Grenoble University Hospital, Grenoble, France (Not yet recruiting)
  • CHU de La Rochelle, La Rochelle, France (Not yet recruiting)
    • Cécile FRÉNARD
    • Cécile FRÉNARD (Principal Investigator)
  • CH du Mans, Le Mans, France (Not yet recruiting)
    • Nathalie BENETON-BENHARD
    • Nathalie BENETON-BENHARD (Principal Investigator)
  • Léon Site Bérard in Lyon, Lyon, France (Not yet recruiting)
    • Mona AMINI-ADLE
    • Mona AMINI-ADLE (Principal Investigator)
  • Nantes University Hospital, Nantes, France (Recruiting)
    • Lise Boussemart, PU-PH
    • Lise BOUSSEMART (Principal Investigator)
  • Ambroise Paré Hospital - APHP, Paris, France (Not yet recruiting)
    • Elisa FUNCK BRENTANO
    • Elisa FUNCK BRENTANO (Principal Investigator)
  • Avicenne Hospital - APHP, Paris, France (Not yet recruiting)
  • Bichat Hospital - APHP, Paris, France (Not yet recruiting)
    • Caroline FAUCON
    • Caroline FAUCON (Principal Investigator)
  • Saint-Louis Hospital - APHP, Paris, France (Not yet recruiting)
  • CHU de Rennes, Rennes, France (Not yet recruiting)
    • Monica DINULESCU
    • Monica DINULESCU (Principal Investigator)
  • Eugène Marquis site - Rennes, Rennes, France (Not yet recruiting)
    • Marc PRACHT
    • Marc PRACHT (Principal Investigator)
  • Rouen University Hospital, Rouen, France (Not yet recruiting)
    • Anne-Bénédicte DUVAL MODESTE
    • Anne-Bénédicte DUVAL MODESTE (Principal Investigator)
  • ICO, Saint-Herblain, France (Not yet recruiting)
    • Clément CHARPENTIER
    • Clément CHARPENTIER (Principal Investigator)
  • Valence Hospital Site, Valence, France (Not yet recruiting)