C Gillett
St Thomas' Hospital
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by C Gillett.
Oncogene | 2007
Nicholas C. Turner; Jorge S. Reis-Filho; Am Russell; Rj Springall; K Ryder; Dawn Steele; Kay Savage; C Gillett; Fernando Schmitt; Alan Ashworth; Andrew Tutt
Basal-like breast cancers form a distinct subtype of breast cancer characterized by the expression of markers expressed in normal basal/myoepithelial cells. Breast cancers arising in carriers of germline BRCA1 mutations are predominately of basal-like type, suggesting that BRCA1 dysfunction may play a role in the pathogenesis of sporadic basal-like cancers. We analysed 37 sporadic breast cancers expressing the basal marker cytokeratin 5/6, and age- and grade-matched controls, for downregulation of BRCA1. Although BRCA1 promoter methylation was no more common in basal-like cancers (basal 14% vs controls 11%, P=0.72), BRCA1 messenger RNA expression was twofold lower in basal-like breast cancers compared to matched controls (P=0.008). ID4, a negative regulator of BRCA1, was expressed at 9.1-fold higher levels in basal-like breast cancer (P<0.0001), suggesting a potential mechanism of BRCA1 downregulation. BRCA1 downregulation correlated with the presence of multiple basal markers, revealing heterogeneity in the basal-like phenotype. Finally, we found that 63% of metaplastic breast cancers, a rare type of basal-like cancers, had BRCA1 methylation, in comparison to 12% of controls (P<0.0001). The high prevalence of BRCA1 dysfunction identified in this study could be exploited in the development of novel approaches to targeted treatment of basal-like breast cancer.
Oncogene | 2006
Rebecca Roylance; P Gorman; T Papior; Y L Wan; M Ives; J E Watson; C Collins; N Wortham; C Langford; H Fiegler; N Carter; C Gillett; P Sasieni; Sarah Pinder; Andrew M. Hanby; Ian Tomlinson
We analysed chromosome 16q in 106 breast cancers using tiling-path array-comparative genomic hybridization (aCGH). About 80% of ductal cancers (IDCs) and all lobular cancers (ILCs) lost at least part of 16q. Grade I (GI) IDCs and ILCs often lost the whole chromosome arm. Grade II (GII) and grade III (GIII) IDCs showed less frequent whole-arm loss, but often had complex changes, typically small regions of gain together with larger regions of loss. The boundaries of gains/losses tended to cluster, common sites being 54.5–55.5 Mb and 57.4–58.8 Mb. Overall, the peak frequency of loss (83% cancers) occurred at 61.9–62.9 Mb. We also found several ‘minimal’ regions of loss/gain. However, no mutations in candidate genes (TRADD, CDH5, CDH8 and CDH11) were detected. Cluster analysis based on copy number changes identified a large group of cancers that had lost most of 16q, and two smaller groups (one with few changes, one with a tendency to show copy number gain). Although all morphological types occurred in each cluster group, IDCs (especially GII/GIII) were relatively overrepresented in the smaller groups. Cluster groups were not independently associated with survival. Use of tiling-path aCGH prompted re-evaluation of the hypothetical pathways of breast carcinogenesis. ILCs have the simplest changes on 16q and probably diverge from the IDC lineage close to the stage of 16q loss. Higher-grade IDCs probably develop from low-grade lesions in most cases, but there remains evidence that some GII/GIII IDCs arise without a GI precursor.
IEEE | 2008
Paul R. Barber; G P Pierce; Simon Ameer-Beg; Daniel R. Matthews; Leo M. Carlin; Melanie Keppler; Frederic Festy; C Gillett; R Springall; Tony Ng; Boris Vojnovic
Studying cellular protein-protein interactions in situ requires a technique such as fluorescence resonance energy transfer (FRET) which is sensitive on the nanometer scale. Observing FRET is significantly simplified if the fluorescence lifetime of the donor can be monitored. Results from live cells and tissue micro arrays are presented from an automated microscope incorporating time-domain TCSPC fluorescence lifetime imaging (FLIM). Novel hardware and software with a modular approach and scripting abilities allow us to work towards speed-optimized acquisition and ease of use to bring FLIM into the high-throughput regime.
Archive | 2017
Katherine Lawler; Efterpi Papouli; Cristina Naceur-Lombardelli; Anca Mera; Kayleigh Ougham; Andrew Tutt; Siker Kimbung; Ingrid Hedenfalk; Jun Zhan; Hongquan Zhang; Richard Buus; Mitch Dowsett; Tony Ng; Sarah Pinder; Peter Parker; Lars Holmberg; C Gillett; Anita Grigoriadis; Arnie Purushotham
Distribution of gene module scores for cases and controls in each case-control series, and estimated ORs using conditional logistic and logistic regression models. (XLSX 47 kb)
Cancer Research | 2013
Roger A'Hern; C Gillett; Sarah Pinder; E Kalaitzaki; Judith M. Bliss; Andrew Tutt; Peter Barrett-Lee; P. Ellis; S. Johnston
Background : Plausible underlying treatment effects were investigated in exploratory analysis of the translational component of TACT, a large adjuvant chemotherapy trial (Lancet 2009:373, 1681). Some breast cancer patients are cured by primary therapy and are therefore not at risk of relapse, potentially confounding treatment comparisons using Cox regression, exploratory comparison of outcomes can be undertaken using parametric cure models (PCM) which estimate the proportion of patients cured and the pattern of events in patients not cured. Methods : TACT compared sequential anthracycline-taxane (FEC-D) adjuvant chemotherapy with an anthracycline regimen of similar duration. As part of TransTACT ER Allred scores were assessed centrally on two cores per patient by two pathologists (CG and SP). PCM was implemented using the CUREREGR command in Stata (Buxton A 2007), a lognormal model for time to relapse being fitted for the category of patients who were not cured. The primary endpoint for the analyses was relapse free interval. Results : 2892 patients had Estrogen Receptor (ER) assessed centrally, 1851 tumors were ER positive and 1041 were ER negative, median follow up was 8 years. The proportion of patients cured was related to established prognostic characteristics such as nodal status. In unselected ER+ patients evidence of cure was weak but it could not be ruled out in some subgroups e.g. in node negative ER+ patients the estimate of the proportion cured was approximately 70% (p = ns). In unselected ER- patients the pattern of relapse implied by PCM was found to differ significantly between taxane treated and control patients (p Conclusions : The concept of cure is of particular interest in tumour subtypes, such as ER negative tumours, in which event rates are high in early years (1-4) but low subsequently. In ER- patients PCM suggested the model-defined cure rate was about 20% higher in docetaxel treated patients, however this was counterbalanced by worse prognosis in the patients without model defined cure. EBCTCG results examining the taxane effect on recurrence were not directly available to support this finding but breast cancer mortality curves in more than 35,000 women with follow up to 8 years (Lancet 379, 432 Webappendix, p15) showed patterns in ER- patients that were consistent with a higher cure rate in taxane treated patients, in addition there was little evidence of cure in unselected ER+ patients. In this study PCM identified differences in the treatment effect between the randomised groups despite the fact there was no evidence of an overall difference based on the hazard ratio by Cox regression, suggesting PCM may have a useful role in exploratory analysis to look for treatment effects in situations where cure is a possibility. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-06-03.
IEEE | 2008
Paul R. Barber; G P Pierce; Simon Ameer-Beg; Daniel R. Matthews; Leo M. Carlin; Melanie Keppler; Frederic Festy; C Gillett; R Springall; Tony Ng; Boris Vojnovic
Studying cellular protein-protein interactions in situ requires a technique such as fluorescence resonance energy transfer (FRET) which is sensitive on the nanometer scale. Observing FRET is significantly simplified if the fluorescence lifetime of the donor can be monitored. Results from live cells and tissue micro arrays are presented from an automated microscope incorporating time-domain TCSPC fluorescence lifetime imaging (FLIM). Novel hardware and software with a modular approach and scripting abilities allow us to work towards speed-optimized acquisition and ease of use to bring FLIM into the high-throughput regime.
BMC Cancer | 2008
Andrew Tutt; Alice Wang; Charles M. Rowland; C Gillett; Kit Lau; Karen Chew; Hongyue Dai; Shirley Kwok; K Ryder; Henry Shu; Robert Springall; Paul Cane; Blair McCallie; Lauren Kam-Morgan; Steve Anderson; Horst Buerger; Joe W. Gray; James L. Bennington; Laura Esserman; Trevor Hastie; Samuel Broder; John J. Sninsky; Burkhard Brandt; Fred Waldman
Journal of Clinical Oncology | 2009
Sherene Loi; Benjamin Haibe-Kains; Fanny Lallemand; Lajos Pusztai; Alberto Bardelli; C Gillett; P. Ellis; Martine Piccart-Gebhart; Wayne A. Phillips; Grant A. McArthur; Christos Sotiriou
Breast Cancer Research and Treatment | 2005
Christine Desmedt; Sherene Loi; Benjamin Haibe-Kains; Anne Soree; Françoise Lallemand; Durbecq; Denis Larsimont; Andrew Tutt; Paul Ellis; C Gillett; K Ryder; Adrian L. Harris; Fatima Cardoso; Philippe Martiat; Martine Piccart; Christos Sotiriou
Archive | 2017
Katherine Lawler; Efterpi Papouli; Cristina Naceur-Lombardelli; Anca Mera; Kayleigh Ougham; Andrew Tutt; Siker Kimbung; Ingrid Hedenfalk; Jun Zhan; Hongquan Zhang; Richard Buus; Mitch Dowsett; Tony Ng; Sarah Pinder; Peter Parker; Lars Holmberg; C Gillett; Anita Grigoriadis; Arnie Purushotham