Melanoma Multi-level risk profiling by DNA sequencing
This project develops a new molecular approach to more accurately predict how melanoma will behave. By combining three types of DNA changes—methylation, mutations, and copy number variations—the goal is to build a more complete picture of each tumour, helping doctors identify high-risk patients earlier and improve treatment decisions. The project builds on a long-standing collaboration between MLA Diagnostics and Maastricht University, which began with the discovery of the LY75 DNA methylation biomarker. Together, the partners will now investigate how to best combine various molecular signals into a more powerful prognostic model using state-of-the-art sequencing technologies.
Melanoma is one of the most dangerous forms of skin cancer, with around 8,300 new cases diagnosed annually in the Netherlands. Despite improvements in early detection, existing diagnostic tools—such as histopathological analysis and sentinel lymph node biopsy—still fall short in predicting whether early-stage tumours will recur or spread. Studies show that nearly 28% of patients with a negative sentinel node result still develop metastases within five years. This uncertainty leads to both over- and under-treatment, making it essential to develop more reliable methods for risk assessment.
In this project, tumour samples from melanoma patients will be analysed using two advanced DNA sequencing techniques: next-generation sequencing (NGS) and Oxford Nanopore sequencing. These technologies will be used to examine a broad set of DNA markers, including methylation patterns, known mutations, and large-scale DNA changes. By comparing the performance of both methods, the team aims to identify the most suitable technology for combining these markers into a single, clinically useful workflow.
The main deliverable of this project will be a validated sequencing protocol and technology choice for integrated, multi-marker melanoma risk assessment. This will lay the foundation for future clinical validation and eventual integration into routine diagnostic care.
