Early stage melanoma: who is at risk of distant metastasis?

THe Risk among Early stage melanomA of distant meTastasis (THREAT)

Erasmus MC, SkylineDx and the Netherlands Comprehensive Cancer Organisation (IKNL), will develop a risk prediction model to identify patients with an early stage melanoma (i.e. without any metastasis), who are at high risk of developing distant metastasis (e.g. metastasis in the lungs, liver or brains).

Each year more than 6,500 patients are diagnosed with melanoma in the Netherlands. Most patients (90%) are diagnosed with an early stage melanoma. Although it seems controversial to the good prognosis of most early stage melanomas, death due to melanoma after diagnosis of an early stage melanoma concerns 41% of all melanoma deaths (i.e. >300 of 800 melanoma deaths in the Netherlands). Current staging of locally invasive melanoma includes only thickness and ulceration of the melanoma and is clearly not sufficient to identify patients at risk of dying.

This project will make use of routinely collected health care data, which will be enriched with molecular diagnostics in order to include all patient and (molecular) tumor characteristics in a risk prediction model. The excellent Dutch health care data allows to combine molecular data with long term clinical follow-up and compare primary melanomas with and without metastasis during follow-up. This project will focus on a genetic signature of the primary melanoma and the tumor microenvironment combined with patient characteristics. The risk prediction model will include prognostic factors which are of added value to known predictive factors (thickness and ulceration).

The final risk prediction model can be applied in any pathology laboratory with standard equipment. The identification of melanoma patients at high risk of developing metastasis leads to identifying a target population for an early clinical intervention (e.g. increased surveillance and/or adjuvant therapy), which will decrease melanoma mortality.

Erasmus MC, SkylineDx and the Netherlands Comprehensive Cancer Organisation (IKNL) will develop a prediction model based on both patient and (molecular) tumor characteristics to identify patients with early stage melanoma who are at high risk for disease progression. Those patients are the target population for surveillance/treatment to decrease melanoma mortality.
Technology Readiness Level (TRL)
1 - 6
Time period
48 months