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. 2025 Jan;40(1):27-42.
doi: 10.1007/s10654-024-01188-4. Epub 2025 Jan 9.

The Dutch Early-Stage Melanoma (D-ESMEL) study: a discovery set and validation cohort to predict the absolute risk of distant metastases in stage I/II cutaneous melanoma

Catherine Zhou  1 , Antien L Mooyaart  2 , Thamila Kerkour  1 , Marieke W J Louwman  3 , Marlies Wakkee  1 , Yunlei Li  4 , Quirinus J M Voorham  5 , Annette Bruggink  5 , Tamar E C Nijsten  1 , Loes M Hollestein  6   7
Affiliations

The Dutch Early-Stage Melanoma (D-ESMEL) study: a discovery set and validation cohort to predict the absolute risk of distant metastases in stage I/II cutaneous melanoma

Catherine Zhou et al. Eur J Epidemiol. 2025 Jan.

Abstract

Early-stage cutaneous melanoma patients generally have a favorable prognosis, yet a significant proportion of metastatic melanoma cases arise from this group, highlighting the need for improved risk stratification using novel prognostic biomarkers. The Dutch Early-Stage Melanoma (D-ESMEL) study introduces a robust, population-based methodology to develop an absolute risk prediction model for stage I/II melanoma, incorporating clinical, imaging, and multi-omics data to identify patients at increased risk for distant metastases. Utilizing the Netherlands Cancer Registry and Dutch Nationwide Pathology Databank, we collected primary tumor samples from early-stage melanoma patients, with and without distant metastases during follow-up. Our study design includes a discovery set of metastatic cases and matched controls to identify novel prognostic factors, followed by a validation cohort using a nested case-control design to validate these factors and to build a risk prediction model. Tissue sections underwent Hematoxylin & Eosin (H&E) staining, RNA sequencing (RNAseq), DNA sequencing (DNAseq), immunohistochemistry (IHC), and multiplex immunofluorescence (MxIF).The discovery set included 442 primary melanoma samples (221 case-control sets), with 46% stage I and 54% stage II melanomas. The median time to distant metastasis was 3.4 years, while controls had a median follow-up time of 9.8 years. The validation cohort included 154 cases and 154 controls from a random population-based selection of 5,815 patients. Our approach enabled the collection of a large number of early-stage melanoma samples from population-based databases with extensive follow-up and a sufficient number of metastatic events. This methodology in prognostic cancer research holds the potential to impact clinical decision-making through absolute risk prediction.

Keywords: Biomarkers; Melanoma; Multi-omics; Population-based; Prognostic; Risk prediction.

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Conflict of interest statement

Declarations. Conflict of interests: All authors declare no competing interests. Ethics approval: Ethical approval was obtained from the scientific committees of Erasmus MC (MEC-2018–1738), the Dutch Nationwide Pathology Databank, and the Netherlands Cancer Registry. Consent to participate: The use of leftover diagnostic tissue samples for scientific research is based on the ‘no objection’ principle, as outlined in the Code of Conduct for Health Research by the Committee on Regulation of Health Research.

Figures

Fig. 1
Fig. 1
Matched case–control design of the discovery set and nested case–control design of the validation cohort. (Abbreviations: AJCC = American Joint Committee of Cancer)
Fig. 2
Fig. 2
Clinical, imaging, RNA sequencing and DNA sequencing data derived from the discovery set will be integrated and the most prognostic features will be validated in the validation cohort
Fig. 3
Fig. 3
Selection process of the matched case–control sets in the discovery set. (Abbreviations: NCR = Netherlands Cancer Registry, EMC = Erasmus MC Cancer Institute, H&E = Hematoxylin & Eosin)
Fig. 4
Fig. 4
Selection process of the nested case–control design of the validation cohort (Abbreviations: NCR = Netherlands Cancer Registry, Palga = Dutch Nationwide Pathology Databank, H&E = Hematoxylin & Eosin)
See this image and copyright information in PMC

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