Expression signatures of DNA repair genes correlate with survival prognosis of astrocytoma patients.

Astrocytomas are the most common primary brain tumors. They are very resistant to therapies and usually progress rapidly to high-grade lesions. Here, we investigated the potential role of DNA repair genes in astrocytoma progression and resistance. To this aim, we performed a polymerase chain reaction array-based analysis focused on DNA repair genes and searched for correlations between expression patters and survival prognoses. We found 19 genes significantly altered. Combining these genes in all possible arrangements, we found 421 expression signatures strongly associated with poor survival. Importantly, five genes (DDB2, EXO1, NEIL3, BRCA2, and BRIP1) were independently correlated with worse prognoses, revealing single-gene signatures. Moreover, silencing of EXO1, which is remarkably overexpressed, promoted faster restoration of double-strand breaks, while NEIL3 knockdown, also highly overexpressed, caused an increment in DNA damage and cell death after irradiation of glioblastoma cells. These results disclose the importance of DNA repair pathways for the maintenance of genomic stability of high-grade astrocytomas and suggest that EXO1 and NEIL3 overexpression confers more efficiency for double-strand break repair and resistance to reactive oxygen species, respectively. Thereby, we highlight these two genes as potentially related with tumor aggressiveness and promising candidates as novel therapeutic targets.

Intrinsically disordered proteins (IDPs) in trypanosomatids.

BACKGROUND: Proteins are composed of one or more amino acid chains and exhibit several structure levels. IDPs (intrinsically disordered proteins) represent a class of proteins that do not fold into any particular conformation and exist as dynamic ensembles in their native state. Due to their intrinsic adaptability, IDPs participate in many regulatory biological processes, including parasite immune escape. Using the information from trypanosomatids proteomes, we developed a pipeline for the identification, characterization and analysis of IDPs. The pipeline employs six disorder prediction methodologies and integrates structural and functional annotation information, subcellular location prediction and physicochemical properties. At the core of the IDP pipeline, there is a relational database that describes the protein disorder knowledge in a logically consistent manner. RESULTS: The results obtained from the IDP pipeline showed that Leishmania and Trypanosoma species have approximately 70% and 55% IDPs, respectively. Our results indicate that IDPs in trypanosomatids contain disorder-promoting amino acids and order-promoting amino acids. The functional annotation analysis demonstrated enrichment of selected Gene Ontology terms. A relevant association was observed between the disordered residue numbers within predicted IDPs and their subcellular location, lack of transmembrane domains and lack of predicted function. We validated our computational findings with 2D electrophoresis designed for IDP identification and found that 100% of the identified protein spots were predicted in silico. CONCLUSIONS: Because there is no pipeline or database addressing IDPs in trypanosomatids, the pipeline described here represents the first attempt to establish possible correlations between protein function and structural disorder in these eukaryotes. Interestingly, all significant associations detected in the contingency analysis were observed when the protein disorder content reached approximately 40%. The exploratory data analysis allowed us to develop hypotheses regarding the IDPs' association with key biological features of these parasites, including transcription and transcriptional regulation, RNA processing and splicing, and cytoskeleton.

Contribution of genetic ancestry and polygenic risk score in meeting vitamin B12 needs in healthy Brazilian children and adolescents.

Polymorphisms in genes related to the metabolism of vitamin B12 haven't been examined in a Brazilian population. To (a) determine the correlation between the local genetic ancestry components and vitamin B12 levels using ninety B12-related genes; (b) determine associations between these genes and their SNPs with vitamin B12 levels; (c) determine a polygenic risk score (PRS) using significant variants. This cross-sectional study included 168 children and adolescents, aged 9-13 years old. Total cobalamin was measured in plasma. Genotyping arrays and whole exome data were combined to yield ~ 7000 SNPs in 90 genes related to vitamin B12. The Efficient Local Ancestry Inference was used to estimate local ancestry for African (AFR), Native American, and European (EUR). The association between the genotypes and vitamin B12 levels were determined with generalized estimating equation. Vitamin B12 levels were driven by positive (EUR) and negative (AFR, AMR) correlations with genetic ancestry. A set of 36 variants were used to create a PRS that explained 42% of vitamin level variation. Vitamin B12 levels are influenced by genetic ancestry and a PRS explained almost 50% of the variation in plasma cobalamin in Brazilian children and adolescents.

Copy Number Profiling of Brazilian Astrocytomas.

Copy number alterations (CNA) are one of the driving mechanisms of glioma tumorigenesis, and are currently used as important biomarkers in the routine setting. Therefore, we performed CNA profiling of 65 astrocytomas of distinct malignant grades (WHO grade I-IV) of Brazilian origin, using array-CGH and microsatellite instability analysis (MSI), and investigated their correlation with TERT and IDH1 mutational status and clinico-pathological features. Furthermore, in silico analysis using the Oncomine database was performed to validate our findings and extend the findings to gene expression level. We found that the number of genomic alterations increases in accordance with glioma grade. In glioblastomas (GBM), the most common alterations were gene amplifications (PDGFRA, KIT, KDR, EGFR, and MET) and deletions (CDKN2A and PTEN) Log-rank analysis correlated EGFR amplification and/or chr7 gain with better survival of the patients. MSI was observed in 11% of GBMs. A total of 69% of GBMs presented TERT mutation, whereas IDH1 mutation was most frequent in diffuse (85.7%) and anaplastic (100%) astrocytomas. The combination of 1p19q deletion and TERT and IDH1 mutational status separated tumor groups that showed distinct age of diagnosis and outcome. In silico validation pointed to less explored genes that may be worthy of future investigation, such as CDK2, DMRTA1, and MTAP Herein, using an extensive integrated analysis, we indicated potentially important genes, not extensively studied in gliomas, that could be further explored to assess their biological and clinical impact in astrocytomas.

Molecular Profiling of a Rare Rosette-Forming Glioneuronal Tumor Arising in the Spinal Cord.

Rosette-forming glioneuronal tumor (RGNT) of the IV ventricle is a rare and recently recognized brain tumor entity. It is histologically composed by two distinct features: a glial component, resembling pilocytic astrocytoma, and a component forming neurocytic rosettes and/or perivascular rosettes. Herein, we describe a 33-year-old man with RGNT arising in the spinal cord. Following an immunohistochemistry validation, we further performed an extensive genomic analysis, using array-CGH (aCGH), whole exome and cancer-related hotspot sequencing, in order to better understand its underlying biology. We observed the loss of 1p and gain of 1q, as well as gain of the whole chromosomes 7, 9 and 16. Local amplifications in 9q34.2 and 19p13.3 (encompassing the gene SBNO2) were identified. Moreover, we observed focal gains/losses in several chromosomes. Additionally, on chromosome 7, we identified the presence of the KIAA1549:BRAF gene fusion, which was further validated by RT-PCR and FISH. Across all mutational analyses, we detected and validated the somatic mutations of the genes MLL2, CNNM3, PCDHGC4 and SCN1A. Our comprehensive molecular profiling of this RGNT suggests that MAPK pathway and methylome changes, driven by KIAA1549:BRAF fusion and MLL2 mutation, respectively, could be associated with the development of this rare tumor entity.

Modulation of HJURP (Holliday Junction-Recognizing Protein) levels is correlated with glioblastoma cells survival.

BACKGROUND: Diffuse astrocytomas are the most common type of primary brain cancer in adults. They present a wide variation in differentiation and aggressiveness, being classified into three grades: low-grade diffuse astrocytoma (grade II), anaplastic astrocytoma (grade III) and glioblastoma multiforme (grade IV), the most frequent and the major lethal type. Recent studies have highlighted the molecular heterogeneity of astrocytomas and demonstrated that large-scale analysis of gene expression could help in their classification and treatment. In this context, we previously demonstrated that HJURP, a novel protein involved in the repair of DNA double-strand breaks, is highly overexpressed in glioblastoma. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that HJURP is remarkably overexpressed in a cohort composed of 40 patients with different grade astrocytomas. We also observed that tumors presenting the higher expression levels of HJURP are associated with poor survival prognosis, indicating HJURP overexpression as an independent prognostic factor of death risk for astrocytoma patients. More importantly, we found that HJURP knockdown strongly affects the maintenance of glioblastoma cells in a selective manner. Glioblastoma cells showed remarkable cell cycle arrest and premature senescence that culminated in elevated levels of cell death, differently from non-tumoral cells that were minimally affected. CONCLUSIONS: These data suggest that HJURP has an important role in the maintenance of extremely proliferative cells of high-grade gliomas and point to HJURP as a potential therapeutic target for the development of novel treatments for glioma patients.

Automatic assignment of prokaryotic genes to functional categories using literature profiling.

In the last years, there was an exponential increase in the number of publicly available genomes. Once finished, most genome projects lack financial support to review annotations. A few of these gene annotations are based on a combination of bioinformatics evidence, however, in most cases, annotations are based solely on sequence similarity to a previously known gene, which was most probably annotated in the same way. As a result, a large number of predicted genes remain unassigned to any functional category despite the fact that there is enough evidence in the literature to predict their function. We developed a classifier trained with term-frequency vectors automatically disclosed from text corpora of an ensemble of genes representative of each functional category of the J. Craig Venter Institute Comprehensive Microbial Resource (JCVI-CMR) ontology. The classifier achieved up to 84% precision with 68% recall (for confidence≥0.4), F-measure 0.76 (recall and precision equally weighted) in an independent set of 2,220 genes, from 13 bacterial species, previously classified by JCVI-CMR into unambiguous categories of its ontology. Finally, the classifier assigned (confidence≥0.7) to functional categories a total of 5,235 out of the ∼24 thousand genes previously in categories "Unknown function" or "Unclassified" for which there is literature in MEDLINE. Two biologists reviewed the literature of 100 of these genes, randomly picket, and assigned them to the same functional categories predicted by the automatic classifier. Our results confirmed the hypothesis that it is possible to confidently assign genes of a real world repository to functional categories, based exclusively on the automatic profiling of its associated literature. The LitProf--Gene Classifier web server is accessible at: www.cebio.org/litprofGC.

Novel primate-specific genes, RMEL 1, 2 and 3, with highly restricted expression in melanoma, assessed by new data mining tool.

Melanoma is a highly aggressive and therapy resistant tumor for which the identification of specific markers and therapeutic targets is highly desirable. We describe here the development and use of a bioinformatic pipeline tool, made publicly available under the name of EST2TSE, for the in silico detection of candidate genes with tissue-specific expression. Using this tool we mined the human EST (Expressed Sequence Tag) database for sequences derived exclusively from melanoma. We found 29 UniGene clusters of multiple ESTs with the potential to predict novel genes with melanoma-specific expression. Using a diverse panel of human tissues and cell lines, we validated the expression of a subset of three previously uncharacterized genes (clusters Hs.295012, Hs.518391, and Hs.559350) to be highly restricted to melanoma/melanocytes and named them RMEL1, 2 and 3, respectively. Expression analysis in nevi, primary melanomas, and metastatic melanomas revealed RMEL1 as a novel melanocytic lineage-specific gene up-regulated during melanoma development. RMEL2 expression was restricted to melanoma tissues and glioblastoma. RMEL3 showed strong up-regulation in nevi and was lost in metastatic tumors. Interestingly, we found correlations of RMEL2 and RMEL3 expression with improved patient outcome, suggesting tumor and/or metastasis suppressor functions for these genes. The three genes are composed of multiple exons and map to 2q12.2, 1q25.3, and 5q11.2, respectively. They are well conserved throughout primates, but not other genomes, and were predicted as having no coding potential, although primate-conserved and human-specific short ORFs could be found. Hairpin RNA secondary structures were also predicted. Concluding, this work offers new melanoma-specific genes for future validation as prognostic markers or as targets for the development of therapeutic strategies to treat melanoma.

Identificação e caracterização computacional de proteínas do tipo IUP no proteoma predito de Schistosoma mansoni / Caracterization and identification proteins of computational of the type IUP in predicted proteoma of the Schistosoma mansoni

A relação entre estrutura e função protéica é um dos conceitos mais bem estabelecidos da biologia molecular. O acúmulo de evidências experimentais, cujos primeiros trabalhos datam de 1890, suportam essa hipótese com grande embasamento científico. Apesar da existência de evidências de mais de um século de estudos, somente no inicio da década de 90 começaram a surgir trabalhos mostrando de forma conclusiva a existência de proteínas funcionalmente ativas, mas incapazes de manter uma conformação estável em condições fisiológicas. Tais proteínas, hoje conhecidas como IUPs (do inglês Intrinsically Unstructured Proteins) estão envolvidas em importantes processos de saúde e doenças, tais como o câncer e diversos processos de interação parasito/hospedeiro. A presente dissertação tem como proposta o estabelecimento de um pipeline computacional visando à avaliação dos diferentes algoritmos de predição de desordem estrutural, seu desempenho e a posterior aplicação dessa ferramenta no estudo in silico do conteúdo de IUPs presentes no proteoma predito de Schistosoma mansoni. Complementarmente, foi desenhado um banco de dados MySQL capaz de albergar toda a informação de desordem estrutural juntamente com diferentes dados de caracterização das IUPs para S. mansoni.

Foram analisados um total de 10.417 proteínas, 7.373 predições de desordem estrutural, mais de 24.600 predições de características estruturais e funcionais, desenvolvidos 21 scripts, e todas essas predições e scripts desenvolvidos foram integrados em um pipeline totalmente automático e inédito para. análise de desordem estrutural. Nossas análises de sensibilidade e especificidade implementadas pela análise de gráficos ROC e pela integração de resultados utilizando bancos de dados relacionais indicam que a predição integrativa (consenso de quatro diferentes metodologias de predição) de desordem estrutural apresenta um ganho de 40% na correta identificação de regiões desordenadas se comparada às predições de cada metodologia individualmente. Aproximadamente 5,5% das regiões desordenadas identificadas tiveram suas coordenadas limítrofes ajustadas após comparação com as coordenadas de domínios conservados. Nossos resultados indicam que aproximadamente 33,6% do proteoma predito de S. mansoni apresenta desordem estrutural. Destas, 2% apresentam domínios transmembrana e 7% apresentam peptídeo sinal. A comparação do perfil funcional das IUPs com as proteínas globulares de S. mansoni demonstra uma maior proporção de IUPs envolvidas em processos de regulação celular e componentes extracelulares.

Identificação e caracterização computacional de proteínas do tipo IUP no proteoma predito de Schistosoma mansoni

A relação entre estrutura e função protéica é um dos conceitos mais bem estabelecidos da biologia molecular. O acúmulo de evidências experimentais, cujos primeiros trabalhos datam de 1890, suportam essa hipótese com grande embasamento científico. Apesar da existência de evidências de mais de um século de estudos, somente no inicio da década de 90 começaram a surgir trabalhos mostrando de forma conclusiva a existência de proteínas funcionalmente ativas, mas incapazes de manter uma conformação estável em condições fisiológicas. Tais proteínas, hoje conhecidas como IUPs (do inglês Intrinsically Unstructured Proteins) estão envolvidas em importantes processos de saúde e doenças, tais como o câncer e diversos processos de interação parasito/hospedeiro. A presente dissertação tem como proposta o estabelecimento de um pipeline computacional visando à avaliação dos diferentes algoritmos de predição de desordem estrutural, seu desempenho e a posterior aplicação dessa ferramenta no estudo in silico do conteúdo de IUPs presentes no proteoma predito de Schistosoma mansoni. Complementarmente, foi desenhado um banco de dados MySQL capaz de albergar toda a informação de desordem estrutural juntamente com diferentes dados de caracterização das IUPs para S. mansoni.

Foram analisados um total de 10.417 proteínas, 7.373 predições de desordem estrutural, mais de 24.600 predições de características estruturais e funcionais, desenvolvidos 21 scripts, e todas essas predições e scripts desenvolvidos foram integrados em um pipeline totalmente automático e inédito para. análise de desordem estrutural. Nossas análises de sensibilidade e especificidade implementadas pela análise de gráficos ROC e pela integração de resultados utilizando bancos de dados relacionais indicam que a predição integrativa (consenso de quatro diferentes metodologias de predição) de desordem estrutural apresenta um ganho de 40% na correta identificação de regiões desordenadas se comparada às predições de cada metodologia individualmente. Aproximadamente 5,5% das regiões desordenadas identificadas tiveram suas coordenadas limítrofes ajustadas após comparação com as coordenadas de domínios conservados. Nossos resultados indicam que aproximadamente 33,6% do proteoma predito de S. mansoni apresenta desordem estrutural. Destas, 2% apresentam domínios transmembrana e 7% apresentam peptídeo sinal. A comparação do perfil funcional das IUPs com as proteínas globulares de S. mansoni demonstra uma maior proporção de IUPs envolvidas em processos de regulação celular e componentes extracelulares.

Identificação e caracterização computacional de proteínas do tipo IUP no proteoma predito de Schistosoma mansoni / Caracterization and identification proteins of computational of the type IUP in predicted proteoma of the Schistosoma mansoni

A relação entre estrutura e função protéica é um dos conceitos mais bem estabelecidos da biologia molecular. O acúmulo de evidências experimentais, cujos primeiros trabalhos datam de 1890, suportam essa hipótese com grande embasamento científico. Apesar da existência de evidências de mais de um século de estudos, somente no inicio da década de 90 começaram a surgir trabalhos mostrando de forma conclusiva a existência de proteínas funcionalmente ativas, mas incapazes de manter uma conformação estável em condições fisiológicas. Tais proteínas, hoje conhecidas como IUPs (do inglês Intrinsically Unstructured Proteins) estão envolvidas em importantes processos de saúde e doenças, tais como o câncer e diversos processos de interação parasito/hospedeiro. A presente dissertação tem como proposta o estabelecimento de um pipeline computacional visando à avaliação dos diferentes algoritmos de predição de desordem estrutural, seu desempenho e a posterior aplicação dessa ferramenta no estudo in silico do conteúdo de IUPs presentes no proteoma predito de Schistosoma mansoni. Complementarmente, foi desenhado um banco de dados MySQL capaz de albergar toda a informação de desordem estrutural juntamente com diferentes dados de caracterização das IUPs para S. mansoni. Foram analisados um total de 10.417 proteínas, 7.373 predições de desordem estrutural, mais de 24.600 predições de características estruturais e funcionais, desenvolvidos 21 scripts, e todas essas predições e scripts desenvolvidos foram integrados em um pipeline totalmente automático e inédito para análise de desordem estrutural. Nossas análises de sensibilidade e especificidade implementadas pela análise de gráficos ROC e pela integração de resultados utilizando bancos de dados relacionais indicam que a predição integrativa (consenso de quatro diferentes metodologias de predição) de desordem estrutural apresenta um ganho de 40% na correta identificação de regiões desordenadas se comparada às predições de cada metodologia individualmente. Aproximadamente 5,5% das regiões desordenadas identificadas tiveram suas coordenadas limítrofes ajustadas após comparação com as coordenadas de domínios conservados. Nossos resultados indicam que aproximadamente 33,6% do proteoma predito de S. mansoni apresenta desordem estrutural. Destas, 2% apresentam domínios transmembrana e 7% apresentam peptídeo sinal. A comparação do perfil funcional das IUPs com as proteínas globulares de S. mansoni demonstra uma maior proporção de IUPs envolvidas em processos de regulação celular e componentes extracelulares.