TP B.1 - MelBrainSys
Integrative multi-omics data analysis and model-based therapy prediction for melanoma brain metastases
We will analyze the already acquired and newly measured multi-omics data (transcriptome, methylome, DNA copy number and small mutations) of our unique metastases pair cohort to identify driver candidates and key pathways that distinguish brain from non-brain samples to predict targets for validations and perturbations experiments by the other subprojects. To realize this, we will develop Hidden Markov Models for the analysis of omics data from individual metastases pairs and further develop a network-based approach based on public omics melanoma profiles from The Cancer Genome Atlas (TCGA) to pinpoint metastases pair and subgroup specific driver candidates. Validated molecular markers and phenotypic responses will be used to develop a model-based algorithm to predict the efficacy of therapeutic interventions for individual brain metastases. This will form the basis for in vivo validations in a mouse model system and a retrospective analysis of independent brain metastases samples in close collaboration with the other subprojects.