Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup.

Medulloblastoma is the most common type of solid brain tumor in children. This type of embryonic tumor is highly heterogeneous and has been classified into 4 molecular subgroups based on their gene expression profiles: WNT, SHH, Group 3 (G3) and Group 4 (G4). WNT and SHH tumors exhibit the specific dysregulation of genes and pathways, whereas G3 and G4 tumors, two of the more frequent subtypes, are the least characterized. Thus, novel markers to aid in the diagnosis, prognosis and management of medulloblastoma are required. In the present study, microarray gene expression data was downloaded from the Gene Expression Omnibus database, including data from the 4 subgroups of medulloblastoma and healthy cerebellum tissue (CT). The data was utilized in an in silico analysis to characterize each subgroup at a transcriptomic level. Using Partek Genomics Suite software, the data were visualized via hierarchical clustering and principal component analysis. The differentially expressed genes were uploaded to the MetaCore portal to perform enrichment analysis using CT gene expression as baseline, with fold change thresholds of <-5 and >5 for differential expression. The data mining analysis of microarray gene expression data enabled the identification of a range of dysregulated molecules associated with each subgroup of medulloblastoma. G4 is the most heterogeneous subgroup, as no definitive pathway defines its pathogenesis; analysis of the gene expression profiles were associated with the G4α and G4ß subcategories. TOX high mobility group box family member 3, synuclein α interacting protein and, potassium voltage-gated channel interacting protein 4 were identified as three novel potential markers for distinguishing the α and ß subcategories of G4. These genes may be associated with medulloblastoma pathogenesis, and thus may provide a basis for researching novel targeted treatment strategies for G4 medulloblastoma.

Polymorphisms in STK17A gene are associated with systemic lupus erythematosus and its clinical manifestations.

Systemic lupus erythematosus (SLE) is an autoimmune disorder with several clinical manifestations. SLE etiology has a strong genetic component, which plays a key role in disease's predisposition, as well as participation of environmental factors, such and UV light exposure. In this regard, we investigated whether polymorphisms in STK17A, a DNA repair related gene, encoding for serine/threonine-protein kinase 17A, are associated with SLE susceptibility. A total of 143 SLE patients and 177 healthy controls from Southern Brazil were genotyped for five STK17A TagSNPs. Our results indicated association of rs7805969 SNP (A and G/A genotype, OR=1.40 and OR=1.73, respectively) with SLE predisposition and the following clinical manifestations: arthritis, cutaneous and immunological alterations. When analyzing haplotypes distribution, we found association between TGGTC, TAGTC and AAGAT haplotypes and risk to develop SLE. When considering clinical manifestations, the haplotypes TGGTT and TAGTC were associated with protection against cutaneous alterations and the haplotype TAGTC to hematological alterations. We also observed association between SLE clinical manifestations and ethnicity, with the European-derived patients being more susceptible to cutaneous and hematological alterations.