Transcriptional regulation in eukaryotes occurs within a chromatin setting, and is strongly influenced by the post-translational modification of histones, the building blocks of chromatin, such as methylation, phosphorylation and acetylation. Acetylation is probably the best understood of these modifications: hyperacetylation leads to an increase in the expression of particular genes, and hypoacetylation has the opposite effect. Many studies have identified several large, multisubunit enzyme complexes that are responsible for the targeted deacetylation of histones. The aim of this review is to give a comprehensive overview of the structure, function and tissue distribution of members of the classical histone deacetylase (HDAC) family, in order to gain insight into the regulation of gene expression through HDAC activity. SAGE (serial analysis of gene expression) data show that HDACs are generally expressed in almost all tissues investigated. Surprisingly, no major differences were observed between the expression pattern in normal and malignant tissues. However, significant variation in HDAC expression was observed within tissue types. HDAC inhibitors have been shown to induce specific changes in gene expression and to influence a variety of other processes, including growth arrest, differentiation, cytotoxicity and induction of apoptosis. This challenging field has generated many fascinating results which will ultimately lead to a better understanding of the mechanism of gene transcription as a whole.

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BackgroundMedulloblastoma is the most common malignant brain tumor in children. Despite recent improvements in cure rates, prediction of disease outcome remains a major challenge and survivors suffer from serious therapy-related side-effects. Recent data showed that patients with WNT-activated tumors have a favorable prognosis, suggesting that these patients could be treated less intensively, thereby reducing the side-effects. This illustrates the potential benefits of a robust classification of medulloblastoma patients and a detailed knowledge of associated biological mechanisms.Methods and FindingsTo get a better insight into the molecular biology of medulloblastoma we established mRNA expression profiles of 62 medulloblastomas and analyzed 52 of them also by comparative genomic hybridization (CGH) arrays. Five molecular subtypes were identified, characterized by WNT signaling (A; 9 cases), SHH signaling (B; 15 cases), expression of neuronal differentiation genes (C and D; 16 and 11 cases, respectively) or photoreceptor genes (D and E; both 11 cases). Mutations in β-catenin were identified in all 9 type A tumors, but not in any other tumor. PTCH1 mutations were exclusively identified in type B tumors. CGH analysis identified several fully or partly subtype-specific chromosomal aberrations. Monosomy of chromosome 6 occurred only in type A tumors, loss of 9q mostly occurred in type B tumors, whereas chromosome 17 aberrations, most common in medulloblastoma, were strongly associated with type C or D tumors. Loss of the inactivated X-chromosome was highly specific for female cases of type C, D and E tumors. Gene expression levels faithfully reflected the chromosomal copy number changes. Clinicopathological features significantly different between the 5 subtypes included metastatic disease and age at diagnosis and histology. Metastatic disease at diagnosis was significantly associated with subtypes C and D and most strongly with subtype E. Patients below 3 yrs of age had type B, D, or E tumors. Type B included most desmoplastic cases. We validated and confirmed the molecular subtypes and their associated clinicopathological features with expression data from a second independent series of 46 medulloblastomas.ConclusionsThe new medulloblastoma classification presented in this study will greatly enhance the understanding of this heterogeneous disease. It will enable a better selection and evaluation of patients in clinical trials, and it will support the development of new molecular targeted therapies. Ultimately, our results may lead to more individualized therapies with improved cure rates and a better quality of life.