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Sökning: WFRF:(Moatamed F)

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1.
  • Wang, M B, et al. (författare)
  • Detection of chromosome 11q13 amplification in head and neck cancer using fluorescence in situ hybridization
  • 1999
  • Ingår i: Anticancer Research. - 0250-7005 .- 1791-7530. ; 19:2A, s. 925-931
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) remains a cancer with one of the lowest five-year survival rates. Despite a better understanding of the disease and recent advances in diagnosis and treatment, survival rates for HNSCC patients have not improved. Chromosomal abnormalities are common in HNSCC, and aberrations of chromosome 11q13 have been correlated with a poor prognosis. MATERIALS AND METHODS: In this study we utilized fluorescence in situ hybridization (FISH) to determine the incidence of 11q13 amplification in twenty primary HNSCC tumors. INT-2 was used as the 11q13 probe, and 9 and 11 centromeric probes were used as controls. RESULTS: Polysomy, greater than two copies of chromosome 11, was found in 2 of 20 tumors. INT2 (11q13) amplification was found in 3 other tumors. CONCLUSIONS: These preliminary studies indicate tht analysis of a larger sample of tumors using FISH may yield important diagnostic and prognostic information about head and neck tumors.  
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2.
  • Zhou, Wei, et al. (författare)
  • Global Biobank Meta-analysis Initiative : Powering genetic discovery across human disease
  • 2022
  • Ingår i: Cell Genomics. - : Elsevier. - 2666-979X. ; 2:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
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