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

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

Which patient and tumor characteristics predict distant metastasis among stage I/II melanoma?

Periode
-
Looptijd
48 months
Deel van call / Programma
/
Projectpartners
Erasmus
Iknl
Skyline Dx

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 >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.

We 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. We will focus on a transcriptomic 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.

The project has led to The Dutch Early Stage Melanoma (D-ESMEL) study: an unique sample collection, including clinical, multi-omics and imaging data of a discovery and validation cohort. We showed that gene expression adds information on top of the clinicopathological variables. A prognostic model will be further  developed and will help to target early interventions, (e.g. surveillance or adjuvant therapy), towards patients at high risk of developing metastasis in order to reduce melanoma mortality.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.