Loes Hollestein

Erasmus MC

In short, Loes Hollestein's research entails the following:

AI-Driven Exploration of the Melanoma Tumor Microenvironment in the Dutch Early Stage Melanoma (D-ESMEL) study

The development of distant metastasis after thin melanoma is very rare (e.g. 1% of all stage IA melanoma). In order to study progression of early stage melanoma, we designed the Dutch Early Stage Melanoma Study (D-ESMEL). The D-ESMEL study consists of a discovery set and a population-based validation cohort. From all cutaneous melanoma samples (>750), clinical, multi-omics (RNAseq/DNAseq) and whole slide imaging (digital H&E and multiplex immunofluorescence) is available. In this project we will characterize the interactions in the tumor microenvironment using two AI approaches. First we will apply a segmentation approach, where tumor and immune cell interactions are quantified after Deep Learning based cell segmentation. Second, we will apply a segmentation-free approach where a Deep Learning framework will be applied to learn which cell phenotypes, neighborhoods and area interactions are predictive for prognosis. Thereafter, prognostic features of the tumor microenvironment will be integrated with prognostic features from
RNAseq, DNAseq, clinical and histopathological data.