Delineating prognostic and treatment predictive factors ín cutaneous melanoma to improve clinical decision-making

Immune checkpoint inhibitors and targeted therapies have improved the outcome for metastatic cutaneous melanoma (CM) patients and have ushered a new era as neo-adjuvant systemic therapy (NAST).

The histopathological and molecular characterization of metastatic CM and the understanding of the microenvironment are thus critical for more effective patient management and to design biologically driven clinical trials.

The overall purpose is to identify and ultimately validate clinically impactful biomarkers and therapeutic targets to optimally inform clinical decision-making and improve the survival in metastatic CM.

Our approach consists of multi-omics-based unsupervised and clinical- outcome- and pathological-outcome-based stratified analyses including machine learning of matched and curated tissue and plasma biospecimens from CM.

This will expand the concept of liquid biopsies to include not only DNA sequences, but also proteins sequences and opens up for the possibility to study fundamental biological processes also patients with MBM giving an unique insight of the interplay between the immune system, the individual tumors and metastatic niches.The matched plasma and samples from melanoma brain metastases (MBM) and patients receiving NAST provide a unique opportunity to characterize the disease and biomarkers in a real-world setting.

In future this will improve the clinical decision-making and further advance a personalized approach to cancer therapy in metastatic CM.