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1.
Genome Med ; 11(1): 79, 2019 12 04.
Artigo em Inglês | MEDLINE | ID: mdl-31801603

RESUMO

BACKGROUND: Genomic structural variants (SVs) can affect many genes and regulatory elements. Therefore, the molecular mechanisms driving the phenotypes of patients carrying de novo SVs are frequently unknown. METHODS: We applied a combination of systematic experimental and bioinformatic methods to improve the molecular diagnosis of 39 patients with multiple congenital abnormalities and/or intellectual disability harboring apparent de novo SVs, most with an inconclusive diagnosis after regular genetic testing. RESULTS: In 7 of these cases (18%), whole-genome sequencing analysis revealed disease-relevant complexities of the SVs missed in routine microarray-based analyses. We developed a computational tool to predict the effects on genes directly affected by SVs and on genes indirectly affected likely due to the changes in chromatin organization and impact on regulatory mechanisms. By combining these functional predictions with extensive phenotype information, candidate driver genes were identified in 16/39 (41%) patients. In 8 cases, evidence was found for the involvement of multiple candidate drivers contributing to different parts of the phenotypes. Subsequently, we applied this computational method to two cohorts containing a total of 379 patients with previously detected and classified de novo SVs and identified candidate driver genes in 189 cases (50%), including 40 cases whose SVs were previously not classified as pathogenic. Pathogenic position effects were predicted in 28% of all studied cases with balanced SVs and in 11% of the cases with copy number variants. CONCLUSIONS: These results demonstrate an integrated computational and experimental approach to predict driver genes based on analyses of WGS data with phenotype association and chromatin organization datasets. These analyses nominate new pathogenic loci and have strong potential to improve the molecular diagnosis of patients with de novo SVs.


Assuntos
Estudos de Associação Genética , Doenças Genéticas Inatas/diagnóstico , Doenças Genéticas Inatas/genética , Predisposição Genética para Doença , Variação Genética , Fenótipo , Biologia Computacional/métodos , Variações do Número de Cópias de DNA , Genoma Humano , Variação Estrutural do Genoma , Humanos , Anotação de Sequência Molecular , Sequenciamento Completo do Genoma
2.
Cell Rep ; 25(9): 2308-2316.e4, 2018 11 27.
Artigo em Inglês | MEDLINE | ID: mdl-30485801

RESUMO

Mutation accumulation during life can contribute to hematopoietic dysfunction; however, the underlying dynamics are unknown. Somatic mutations in blood progenitors can provide insight into the rate and processes underlying this accumulation, as well as the developmental lineage tree and stem cell division numbers. Here, we catalog mutations in the genomes of human-bone-marrow-derived and umbilical-cord-blood-derived hematopoietic stem and progenitor cells (HSPCs). We find that mutations accumulate gradually during life with approximately 14 base substitutions per year. The majority of mutations were acquired after birth and could be explained by the constant activity of various endogenous mutagenic processes, which also explains the mutation load in acute myeloid leukemia (AML). Using these mutations, we construct a developmental lineage tree of human hematopoiesis, revealing a polyclonal architecture and providing evidence that developmental clones exhibit multipotency. Our approach highlights features of human native hematopoiesis and its implications for leukemogenesis.


Assuntos
Linhagem da Célula/genética , Senescência Celular/genética , Hematopoese/genética , Mutagênese/genética , Mutação/genética , Adulto , Embrião de Mamíferos/citologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Células-Tronco Multipotentes/citologia , Células-Tronco Multipotentes/metabolismo , Especificidade de Órgãos
3.
Mol Cell Proteomics ; 17(10): 1892-1908, 2018 10.
Artigo em Inglês | MEDLINE | ID: mdl-29970458

RESUMO

Intrinsic and/or acquired resistance represents one of the great challenges in targeted cancer therapy. A deeper understanding of the molecular biology of cancer has resulted in more efficient strategies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has also been observed in colorectal cancer patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block intrinsic resistance to BRAF inhibitors. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant colorectal cancer cells as a model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both known and novel responses. We primarily observe widespread up-regulation of receptor tyrosine kinases and metabolic pathways upon BRAF inhibition. These findings point to mechanisms by which the drug-treated cells switch energy sources and enter a quiescent-like state as a defensive response, while additionally compensating for the MAPK pathway inhibition.


Assuntos
Neoplasias Colorretais/patologia , Receptores ErbB/antagonistas & inibidores , Inibidores de Proteínas Quinases/farmacologia , Proteínas Proto-Oncogênicas B-raf/antagonistas & inibidores , Biologia de Sistemas/métodos , Ciclo Celular/efeitos dos fármacos , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Neoplasias Colorretais/genética , Regulação para Baixo/efeitos dos fármacos , Sinergismo Farmacológico , Receptores ErbB/metabolismo , Retroalimentação Fisiológica , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Técnicas de Inativação de Genes , Humanos , Sistema de Sinalização das MAP Quinases/efeitos dos fármacos , Modelos Biológicos , Mutação/genética , Fosfatidilinositol 3-Quinases/metabolismo , Proteína Tirosina Fosfatase não Receptora Tipo 11/metabolismo , Proteínas Proto-Oncogênicas B-raf/metabolismo , Proteínas Proto-Oncogênicas c-akt/metabolismo
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