Neuroblastoma as a pediatric tumor develops in the sympathetic nervous system. DLG2 is a gene that encodes a member of the membrane-associated guanylate kinase (MAGUK) family and it resides in the chromosome region 11q. SK-N-AS is a neuroblastoma cell line with 11q deletion and consequently only one copy of the potential tumor suppressor gene DLG2. This study investigated synergistic effect by a combination treatment with 1,25(OH)2D3 and the vitamin A metabolite, retinoic acid.  Separately, SK-N-AS cells was transfected with expression vector pcDNA3.1+‐DYK that contained the DLG2-gene, followed by monitoring cell proliferation and qPCR, investigating the expression of the genes DLG2, DLG3, DLG4, VDR and PDIA3. Simultaneously, effects of knocked-down of DLG2, by siRNA transfection was monitored.  Transfection of expression plasmid with the DLG2 gene increased significantly gene expression in SK-N-AS cells with significant inhibition of the proliferation rate. Furthermore, silencing of DLG2 gene had no effect on the cell growth as well. Slower cell growth showed in combination treatment with 1,25(OH)2D3 (1nM) and 9-cis RA after 48 hours of treatment. Down-regulated VDR and possible missing RARRES3 could be the reason why SK-N-AS cell line showed resistance to the combination treatment with vitamin metabolites. All these results raised the question if another vitamin D synthetic analog could be a better choice for the future study of SK-N-AS cells. Moreover, overexpression of NAIP, large amounts of IGF-II, or not responsive RXR-VDR heterodimer to 1,25(OH)2D3 could be a potential explanation for the SK-N-AS cell unresponsiveness to the treatment.

An important quest in genomics since the publication of the first complete human genome in 2003 has been its functional annotation. DNA holds the instructions to the production of the components necessary for the life of cells and organisms. A complete functional catalog of genomic regions will help the understanding of the cell body and its dynamics, thus creating links between genotype and phenotypic traits. The need for annotations prompted the development of several bioinformatic methods. In the context of promoter and first exon predictors, the majority of models relies principally on structural and chemical properties of the DNA sequence. Some of them integrate information from epigenomic and transcriptomic data as secondary features. Current genomic research asserts that reference genome annotations are far from being fully annotated (human organism included).Physicians rely on reference genome annotations and functional databases to understand disorders with genetic basis, and missing annotations may lead to unresolved cases. Because of their complexity, neurodevelopmental disorders are under study to figure out all genetic regions that are involved. Besides functional validation on model organisms, the search for genotype-phenotype association is supported by statistical analysis, which is typically biased towards known functional regions.This thesis addresses the use of an in-silico integrative analysis to improve reference genome annotations and discover novel functional regions associated with neurodevelopemental disorders. The contributions outlined in this document have practical applications in clinical settings. The presented bioinformatic method is based on epigenomic and transcriptomic data, thus excluding features from DNA sequence. Such integrative approach applied on brain data allowed the discovery of two novel promoters and coding first exons in the human DLG2 gene, which were also found to be statistically associated with neurodevelopmental disorders and intellectual disability in particular. The application of the same methodology to the whole genome resulted in the discovery of other novel exons expressed in brain. Concerning the in-silico method itself, the research demanded a high number of functional and clinical datasets to properly support and validate our discoveries.This work describes a bioinformatic method for genome annotation, in the specific area of promoter and first exons. So far the method has been applied on brain data, and the extension to the whole body data would be a logical by-product. We will leverage distributed frameworks to tackle the even higher amount of data to analyse, a task that has already begun. Another interesting research direction that came up from this work is the temporal enrichment analysis of epigenomics data across different developmental stages, in which changes of epigenomic enrichment suggest time-specific and tissue-specific functional gene and gene isoforms regulation. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished