Single Cell EPigenomic, Transcriptomic, and structural Rearrangement profiling to investigate Evolution in prostate cancer

Descripción del proyecto

Evolución del cáncer de próstata

El cáncer de próstata se caracteriza por una extensa heterogeneidad molecular y clínica. El objetivo del proyecto SCEPTRE, financiado con fondos europeos, es comprender la función de la epigenética en la heterogeneidad de los tumores y la evolución clonal. Para ello, los científicos utilizarán tecnologías de secuenciación punta para identificar las variaciones epigenéticas, transcriptómicas y genómicas en las células cancerosas. Los factores impulsores epigenéticos y la metilación del ADN pueden servir como biomarcadores y proporcionar información sobre la evolución de diferentes clones de cáncer. Teniendo en cuenta que el cáncer de próstata es el cáncer más diagnosticado en hombres en Europa, los resultados del proyecto tendrán una gran importancia clínica y terapéutica.

Objetivo

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.