Massively parallel sequencing technologies in neuroblastoma research

In this thesis I describe the steps taken to harness the power of massively parallel sequencing in neuroblastoma research. With running cost being prohibitive for experimental design in the early days of this technique, our primary focus was on optimizing the use of the sequencing platforms available. DNA target enrichment is a crucial technique in this process as it allows researchers to focus their research question on the parts of the genome studied. We have developed a highly efficient massively parallel nanowell PCR based capture platform. An optimal primer design as well as multiple improvements to the cycling process has resulted in an industry leading enrichment uniformity. This platform is now being commercialized by Wafergen Biosystems (USA) as a means of gene panel resequencing both for research and diagnostic applications. As genomics is taking a more prominent role in treatment decisions for cancer, such platforms may transform routine diagnostics. The advent of massively parallel sequencing technology has shifted the challenge of genomics studies away from data generation and towards data analysis. Our efforts in the management of the huge data flows from massively parallel sequencing experiments have resulted in a cloud based platform for exome and genome resequencing data analysis. Seqplorer is scalable and flexible and delivers the power of massively parallel sequencing data analysis tools through a user-friendly web interface. Finally, I have applied exome sequencing to the study of neuroblastoma murine model systems. These model systems are of enormous value in pre-clinical drug testing. These analyses have confirmed that the murine neuroblastoma models mimic the human disease at the genomic level very well and have provided important new insights in globally deregulated miRNA processing in human neuroblastoma cells.