Now showing items 1-5 of 5

    • Combined genetic and splicing analysis of BRCA1 c.[594-2A>C; 641A>G] highlights the relevance of naturally occurring in-frame transcripts for developing disease gene variant classification algorithms 

      de, la Hoya Miguel; Soukarieh, Omar; López-Perolio, Irene; Vega, Ana; Walker, Logan C; van, Ierland Yvette; Baralle, Diana et al. (Oxford University Press, 2016-03-23)
      A recent analysis using family history weighting and co-observation classification modeling indicated that BRCA1 c.594-2A > C (IVS9-2A > C), previously described to cause exon 10 skipping (a truncating alteration), displays ...
    • Etiology of hormone receptor positive breast cancer differs by levels of histologic grade and proliferation. 

      Abubakar, Mustapha; Chang-Claude, Jenny; Ali, H Raza; Chatterjee, Nilanjan; Coulson, Penny; Daley, Frances; Blows, Fiona et al. (Wiley-Blackwell, 2018-03)
      Limited epidemiological evidence suggests that the etiology of hormone receptor positive (HR+) breast cancer may differ by levels of histologic grade and proliferation. We pooled risk factor and pathology data on 5,905 HR+ ...
    • Familial relative risks for breast cancer by pathological subtype: a population-based cohort study 

      Mavaddat, Nasim; Pharoah, Paul David; Blows, Fiona; Driver, Kristy E; Provenzano, Elena; Thompson, Deborah Jane; MacInnis, Robert J et al. (2010-02-10)
      Abstract Introduction The risk of breast cancer to first degree relatives of breast cancer patients is approximately twice that of the general population. Breast cancer, however, is a heterogeneous disease and it is plausible ...
    • High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium 

      Abubakar, Mustapha; Howat, William J; Daley, Frances; Zabaglo, Lila; McDuffus, Leigh-Anne; Blows, Fiona; Coulson, Penny et al. (Wiley, 2016-04-06)
      Automated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated ...
    • Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium 

      Howat, William; Blows, Fiona; Provenzano, Elena; Brook, Mark; Morris, Lorna; Gazinska, Patrycja; Johnson, Nicola et al. (Wiley, 2014-12-04)
      Breast cancer risk factors and clinical outcomes vary by tumor marker expression. However, individual studies often lack the power required to assess these relationships, and large-scale analyses are limited by the need ...