Single Cell EPigenomic Transcriptomic and structural Rearrangement profiling t...
Single Cell EPigenomic Transcriptomic and structural Rearrangement profiling to investigate Evolution in prostate cancer
Prostate cancer (PrCa) is the most frequently diagnosed cancer in men in the European Union (EU), and is a molecularly and clinically heterogeneous disease. Although the genomic and transcriptomic landscapes of PrCa have been char...
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Información proyecto SCEPTRE
Duración del proyecto: 36 meses
Fecha Inicio: 2020-03-23
Fecha Fin: 2023-04-09
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
Prostate cancer (PrCa) is the most frequently diagnosed cancer in men in the European Union (EU), and is a molecularly and clinically heterogeneous disease. Although the genomic and transcriptomic landscapes of PrCa have been characterized deeply, the genome-wide epigenetic landscape and its contribution to tumor heterogeneity has received less attention. The lack of single-cell methylation (with parallel single-cell transcriptomic) datasets in solid tumors (and none in PrCA) has stunted inference on clonal evolution. Consequently, the understanding of the coordinated relationship between methylation and transcriptome remains tenuous at best. Structural variants have also not been able to be accurately resolved in cancer due to the reliance on short-read sequencing, and their interplay with DNA methylation is still poorly understood. I present the project, SCEPTRE which is tightly connected to and builds upon ample expertise in the laboratories of Prof. Christoph Plass, Division Chair of Cancer Epigenomics, DKFZ, and Dr. Oliver Stegle, Division Chair of Computational Genomics, DKFZ. Within this project, I will drive the generation of novel ‘single-cell’ and ‘single-molecule long-read’ PrCa datasets, and exploit existing data resources to comprehensively assess the epigenetic and joint transcriptomic and genomic dimensions of human PrCa with the aim to examine cancer evolution. To realize this aim, I will also derive a comprehensive computational toolbox for the analysis of single-cell (and single-molecule) DNA methylation and joint multi-omic profiles. This project will deliver novel innovative ways to identify epigenetic drivers; as well as link DNA methylation for lineage tracing as a biomarker for disease progression. Moreover, the project will uncover putative relationships between the DNA methylome and transcriptome as well as between structural genetic aberrations and epigenetic changes.