Building a Community to Advance Research for Patients with Acral Melanoma

Abstract

Acral melanoma (AM) is a rare subtype of melanoma accounting for approximately 2-3% of melanoma cases in the US, with a higher proportion of cases in populations with darker skin. AM is generally diagnosed at more advanced stages of the disease and typically is not as responsive to the treatments that have been approved for melanoma over the past decade. Therefore, more research and data are needed to comprehensively address the complexity and distinct characteristics of this disease. To address this, the Melanoma Research Alliance launched RARE, the first direct-to-patient registry for those with AM and mucosal melanoma (MM), as well as non-acral cutaneous melanoma as a comparator arm. Participants complete surveys on topics including demographics, disease and treatment history, genetics and biomarker testing, health and lifestyle, and quality of life and upload medical reports. The aims of this study are to: 1) Populate the RARE registry with datasets that accurately represent the racial and ethnic distribution of AM patients in the US; 2) Build a clinically annotated biospecimen repository of samples from AM RARE participants and distribute tissues to researchers; and 3) Create RARE data portals that allow the dissemination of integrated patient-reported, clinical, and omics analyses to the research community in a reasonable timeframe. At this point the RARE registry has 137 patients enrolled including 35 AM participants. Our current efforts are focused on building the diverse AM community of RARE participants and opening the associated biorepository for collection of samples.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2023
Accession Number
AD1216881

Entities

People

  • Cody Barnett
  • Isabel Ryan
  • Joan Levy
  • Marc Hurlbert
  • Nicholas Starink
  • Rachel Fischer
  • Viren Sehgal

Organizations

  • Melanoma Research Alliance

Tags

DTIC Thesaurus Topics

  • Platforms

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Molecular and Cellular Biology
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • Biotechnology