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Träfflista för sökning "WFRF:(Hawari M) "

Search: WFRF:(Hawari M)

  • Result 1-7 of 7
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1.
  • 2021
  • swepub:Mat__t
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2.
  • Glasbey, JC, et al. (author)
  • 2021
  • swepub:Mat__t
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3.
  • Tabiri, S, et al. (author)
  • 2021
  • swepub:Mat__t
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4.
  • Bravo, L, et al. (author)
  • 2021
  • swepub:Mat__t
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5.
  • 2021
  • swepub:Mat__t
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6.
  • Kanai, M, et al. (author)
  • 2023
  • swepub:Mat__t
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7.
  • Cornish, Alex J., et al. (author)
  • The genomic landscape of 2,023 colorectal cancers
  • 2024
  • In: Nature. - 0028-0836 .- 1476-4687. ; In Press
  • Journal article (peer-reviewed)abstract
    • Colorectal carcinoma (CRC) is a common cause of mortality1, but a comprehensive description of its genomic landscape is lacking2–9. Here we perform whole-genome sequencing of 2,023 CRC samples from participants in the UK 100,000 Genomes Project, thereby providing a highly detailed somatic mutational landscape of this cancer. Integrated analyses identify more than 250 putative CRC driver genes, many not previously implicated in CRC or other cancers, including several recurrent changes outside the coding genome. We extend the molecular pathways involved in CRC development, define four new common subgroups of microsatellite-stable CRC based on genomic features and show that these groups have independent prognostic associations. We also characterize several rare molecular CRC subgroups, some with potential clinical relevance, including cancers with both microsatellite and chromosomal instability. We demonstrate a spectrum of mutational profiles across the colorectum, which reflect aetiological differences. These include the role of Escherichiacolipks+ colibactin in rectal cancers10 and the importance of the SBS93 signature11–13, which suggests that diet or smoking is a risk factor. Immune-escape driver mutations14 are near-ubiquitous in hypermutant tumours and occur in about half of microsatellite-stable CRCs, often in the form of HLA copy number changes. Many driver mutations are actionable, including those associated with rare subgroups (for example, BRCA1 and IDH1), highlighting the role of whole-genome sequencing in optimizing patient care.
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