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1.
MedicalExpress (São Paulo, Online) ; 4(5)Sept.-Oct. 2017. tab, graf
Article in English | LILACS | ID: biblio-894366

ABSTRACT

OBJECTIVE: Glioblastoma, the most common and lethal brain tumor, is also one of the most defying forms of malignancies in terms of treatment. Integrated genomic analysis has searched deeper into the molecular architecture of GBM, revealing a new sub-classification and promising precision in the care for patients with specific alterations. METHOD: Here, we present the classification of a Brazilian glioblastoma cohort into its main molecular subtypes. Using a high-throughput DNA sequencing procedure, we have classified this cohort into proneural, classical and mesenchymal sub-types. Next, we tested the possible use of the overexpression of the EGFR and CHI3L1 genes, detected through immunohistochemistry, for the identification of the classical and mesenchymal subtypes, respectively. RESULTS: Our results demonstrate that genetic identification of the glioblastoma subtypes is not possible using single targeted mutations alone, particularly in the case of the Mesenchymal subtype. We also show that it is not possible to single out the mesenchymal cases through CHI3L1 expression. CONCLUSION: Our data indicate that the Mesenchymal subtype, the most malignant of the glioblastomas, needs further and more thorough research to be ensure adequate identification.


OBJETIVO: O glioblastoma (GBM), o tumor cerebral mais comum e mais letal, é também um dos tipos de tumores de mais difícil tratamento. Análises genômicas integradas têm contribuído para um melhor entendimento da arquitetura molecular dos GBMs, revelando uma nova subclassificação com a promessa de precisão no tratamento de pacientes com alterações específicas. Neste estudo, nós apresentamos a classificação de uma casuística brasileira de GBMs dentro dos principais subtipos do tumor. MÉTODO: Usando sequenciamento de DNA em larga escala, foi possível classificar os tumores em proneural, clássico e mesenquimal. Em seguida, testamos o possível uso da hiperexpressão de EGFR e CHI3L1 para a identificação dos subtipos clássico e mesenquimal, respectivamente. RESULTADOS: Nossos resultados deixam claro que a identificação genética dos subtipos moleculares de GBM não é possível utilizando-se apenas um único tipo de mutação, em particular nos casos de GBMs mesenquimais. Da mesma forma, não é possível distinguir os casos mesenquimais apenas com a expressão de CHI3L1. CONCLUSÃO: Nossos dados indicam que o subtipo mesenquimal, o mais maligno dos GBMs, necessita de uma análise mais aprofundada para sua identificação.


Subject(s)
Animals , Sequence Analysis, DNA/methods , Glioblastoma/classification , Genes, erbB-1 , Chitinase-3-Like Protein 1/analysis
2.
Clinics ; 68(2): 167-172, 2013. ilus, tab
Article in English | LILACS | ID: lil-668802

ABSTRACT

OBJECTIVES: We investigated four components of the Wnt signaling pathway in medulloblastomas. Medulloblastoma is the most common type of malignant pediatric brain tumor, and the Wnt signaling pathway has been shown to be activated in this type of tumor. METHODS: Sixty-one medulloblastoma cases were analyzed for β-catenin gene (CTNNB1) mutations, β-catenin protein expression via immunostaining and Wnt signaling pathway-related gene expression. All data were correlated with histological subtypes and patient clinical information. RESULTS: CTNNB1 sequencing analysis revealed that 11 out of 61 medulloblastomas harbored missense mutations in residues 32, 33, 34 and 37, which are located in exon 3. These mutations alter the glycogen synthase kinase-3β phosphorylation sites, which participate in β-catenin degradation. No significant differences were observed between mutation status and histological medulloblastoma type, patient age and overall or progression-free survival times. Nuclear β-catenin accumulation, which was observed in 27.9% of the cases, was not associated with the histological type, CTNNB1 mutation status or tumor cell dissemination. The relative expression levels of genes that code for proteins involved in the Wnt signaling pathway (CTNNB1, APC, AXIN1 and WNT1) were also analyzed, but no significant correlations were found. In addition, large-cell variant medulloblastomas presented lower relative CTNNB1 expression as compared to the other tumor variants. CONCLUSIONS: A small subset of medulloblastomas carry CTNNB1 mutations with consequent nuclear accumulation of β-catenin. The Wnt signaling pathway plays a role in classic, desmoplastic and extensive nodularity medulloblastoma variants but not in large-cell medulloblastomas.


Subject(s)
Adult , Child , Female , Humans , Male , Adenomatous Polyposis Coli Protein/analysis , Axin Protein/analysis , Cerebellar Neoplasms/pathology , Medulloblastoma/pathology , beta Catenin/analysis , Adenomatous Polyposis Coli Protein/metabolism , Axin Protein/metabolism , Chi-Square Distribution , Cerebellar Neoplasms/genetics , Cerebellar Neoplasms/metabolism , Disease-Free Survival , Gene Expression , Medulloblastoma/genetics , Medulloblastoma/metabolism , Real-Time Polymerase Chain Reaction , Statistics, Nonparametric , Wnt Signaling Pathway , beta Catenin/metabolism
3.
Arq. neuropsiquiatr ; 66(2a): 238-241, jun. 2008. ilus
Article in English | LILACS | ID: lil-484133

ABSTRACT

Malignant brain tumor experimental models tend to employ cells that are immunologically compatible with the receptor animal. In this study, we have proposed an experimental model of encephalic tumor development by injecting C6 cells into athymic Rowett rats, aiming at reaching a model which more closely resembles to the human glioma tumor. In our model, we observed micro-infiltration of tumor cell clusters in the vicinity of the main tumor mass, and of more distal isolated tumor cells immersed in normal encephalic parenchyma. This degree of infiltration is superior to that usually observed in other C6 models.


Modelos experimentais de tumores cerebrais malignos geralmente utilizam células imunologicamente compatíveis com o animal receptor. Neste estudo apresentamos um modelo experimental baseado na inoculação de células C6 em ratos atímicos Rowett, visando obter um tumor que se assemelhe mais àqueles observados nos seres humanos. Neste modelo observamos microinfiltração de ilhotas de células na periferia da massa tumoral principal e nas áreas mais distantes, células tumorais isoladas no tecido cerebral normal. Este grau de infiltração é superior àquele observado em outros modelos utilizando as células C6.


Subject(s)
Animals , Female , Rats , Brain Neoplasms/pathology , Glioma/pathology , Disease Models, Animal , Neoplasm Invasiveness , Rats, Nude
4.
Genet. mol. res. (Online) ; 3(4): 493-511, 2004. tab, graf
Article in English | LILACS | ID: lil-410894

ABSTRACT

The correct identification of all human genes, and their derived transcripts, has not yet been achieved, and it remains one of the major aims of the worldwide genomics community. Computational programs suggest the existence of 30,000 to 40,000 human genes. However, definitive gene identification can only be achieved by experimental approaches. We used two distinct methodologies, one based on the alignment of mouse orthologous sequences to the human genome, and another based on the construction of a high-quality human testis cDNA library, in an attempt to identify new human transcripts within the human genome sequence. We generated 47 complete human transcript sequences, comprising 27 unannotated and 20 annotated sequences. Eight of these transcripts are variants of previously known genes. These transcripts were characterized according to size, number of exons, and chromosomal localization, and a search for protein domains was undertaken based on their putative open reading frames. In silico expression analysis suggests that some of these transcripts are expressed at low levels and in a restricted set of tissues.


Subject(s)
Humans , Animals , Male , Mice , DNA, Complementary/genetics , Genome, Human , Sequence Analysis, DNA/methods , Testis/chemistry , Transcription, Genetic/genetics , Amino Acid Sequence , Chromosome Mapping , Gene Library , Molecular Sequence Data
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