Cancer Computational Biology Center ErasmusMC

Erasmus MC Cancer Computational Biology Center (CCBC)

The Erasmus MC Cancer Computational Biology Center (CCBC) part of the Cancer Institute and funded by the Daniel den Hoed Foundation, facilitates ICT and bioinformatics both for research as well as clinic. CCBC develops new computational algorithms, analysis methods and visualization tools in the field of computational biology. The CCBC aims to support, stimulate and innovate mostly omics-based cancer research, including genomics, transcriptomics and proteomics. With dedicated employees and well-structured robust infrastructure the CCBC is able to manage big data sources and combine activities of multiple cancer research groups. Involvement of the CCBC is preferentially before the start of a project, but can also be implemented later. Our main goals are four fold.

First, understand the origin and progression of cancer. Cancer (epi)genomes and transcriptomes are considerably different than the normal diploid genomes. We study large data sets of normal and cancer (epi)genomes to gain insights into genome stability, regulation of gene expression, protein function and cellular networks.

Second, identification of cancer biomarkers and therapy targets. Mutations and dysregulation of gene expression can change the quality and quantity of macromolecules, such as DNA, RNA and proteins. The identification of these aberrations and further characterization can provide diagnostic, prognostic and predictive biomarkers, being clinically extremely relevant and, if functionally important, these macromolecules are great candidates as therapy targets. Computational derived hypotheses and predictions are being generated and can be validated in close collaboration with the Erasmus MC Cancer Treatment Screening Facility (CTSF; https://ctcf.erasmusmc.nl/)

Third, implementation of Next Generation Sequencing (NGS)-based molecular diagnostics and personalized oncology. Individualized medicine and molecular diagnostics improve and will improve medical care at the Erasmus MC. We analyze large clinical NGS datasets and develop, build and implement novel computational tools to assess disease-specific DNA molecules, used in a clinical setting.

Fourth, data integration, tool development, data storage and computational biology.We maintain a local high compute and storage system to perform heavy computational analyses. Moreover, we provide storage, develop bioinformatics tools and design new computational algorithms. Therefore the CCBC is able to analyze, locally, normal and cancer-related DNA-seq, RNA-seq, ChIP-seq, 4C-seq, microarray, high-throughput qPCR and proteomics data. Using our implemented work flows, we analyze high-throughput data from alignments to data integration and from mutational calling to pathway analysis and carry out tailor-made cluster and network analysis. In addition, we perform uni- and multivariant statistical analysis, power calculations, survival analysis and advise research groups with their experimental design Understanding cancer and computational biology starts with a good education of BSc-,MSc- and PhD-students. Therefore, the CCBC is sharing its knowledge on cancer computational biology with national and international students.