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Transcription and Chromatin, Date: 2014/08/23 - 2014/08/26, Location: Heidelberg

Publication date: 2014-08-01

Author:

Verfaillie, Annelien
Imrichova, Hana ; Kalender Atak, Zeynep ; Christiaens, Valerie ; Hulselmans, Gert ; Dewaele, Michael ; Marine, Chris ; Aerts, Stein

Keywords:

Melanoma, regulatory networks, chromatin

Abstract:

Melanoma is one of the most aggressive cancers to date and is marked by a therapy-resistant character reflecting its high heterogeneity and plasticity. Expression profiling of melanoma shows the presence of at least two distinct transcriptional programs within the tumor reflecting different cellular states: more proliferative versus invasive and migratory cells. These states are defined within a phenotype switching model, a process that is thought to be driven by the cells microenvironment rather then by mutations. Besides characterizing each state with a specifc expression program, this model attributes cells with the capacity to switch back and forth between each cellular state. However, the underlying molecular mechanisms and the origin of these states are poorly understood. Identifying the key regulatory networks behind them would mean a great advancement in comprehending melanoma. To investigate this, we combined publicly available data from TCGA, ENCODE and GEO with in-house datasets generated from patient-derived cultures. Besides gene expression data, we applied FAIRE-seq and ChIP-seq against both H3K27ac and H3K27me3 to investigate the chromatin activity. In addition, we used a large collection of transcription factor binding motifs allowing us to identify master regulators within each state. Together, this data enabled us to identify SOX10/MITF and AP1/STAT/TEAD as potential master regulators for the proliferative and invasive state. In addition, the chromatin data allowed us to pinpoint distal enhancers controlled by these factors. Finally, to support our findings, we performed a perturbation of TEAD to verify its role in the invasive state of melanoma tumor cells. All together, by collecting and mining through an extensive set of data we gained insight into the mechanisms supporting melanoma’s plasticity and heterogeneity. This itself is a step forward and can proof to be vital for the development of more effective therapies to battle melanoma.