Cambridge Experimental Cancer Medicine Center

Cambridge, United Kingdom

Cambridge Experimental Cancer Medicine Center

Cambridge, United Kingdom
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Dawson S.-J.,University of Cambridge | Rueda O.M.,University of Cambridge | Aparicio S.,University of British Columbia | Aparicio S.,British Columbia Cancer Research Center | And 2 more authors.
EMBO Journal | Year: 2013

Breast cancer is a group of heterogeneous diseases that show substantial variation in their molecular and clinical characteristics. This heterogeneity poses significant challenges not only in breast cancer management, but also in studying the biology of the disease. Recently, rapid progress has been made in understanding the genomic diversity of breast cancer. These advances led to the characterisation of a new genome-driven integrated classification of breast cancer, which substantially refines the existing classification systems currently used. The novel classification integrates molecular information on the genomic and transcriptomic landscapes of breast cancer to define 10 integrative clusters, each associated with distinct clinical outcomes and providing new insights into the underlying biology and potential molecular drivers. These findings have profound implications both for the individualisation of treatment approaches, bringing us a step closer to the realisation of personalised cancer management in breast cancer, but also provide a new framework for studying the underlying biology of each novel subtype. © 2013 European Molecular Biology Organization.

Ali H.R.,University of Cambridge | Glont S.-E.,University of Cambridge | Blows F.M.,University of Cambridge | Provenzano E.,University of Cambridge | And 13 more authors.
Annals of Oncology | Year: 2015

Background: Expression of programmed death ligand 1 (PD-L1) in solid tumours has been shown to predict whether patients are likely to respond to anti-PD-L1 therapies. To estimate the therapeutic potential of PD-L1 inhibition in breast cancer, we evaluated the prevalence and significance of PD-L1 protein expression in a large collection of breast tumours. Patients and methods: Correlations between CD274 (PD-L1) copy number, transcript and protein levels were evaluated in tumours from 418 patients recruited to the METABRIC genomic study. Immunohistochemistry was used to detect PD-L1 protein in breast tumours in tissue microarrays from 5763 patients recruited to the SEARCH population-based study (N = 4079) and the NEAT randomised, controlled trial (N = 1684). Results: PD-L1 protein data was available for 3916 of the possible 5763 tumours from the SEARCH and NEAT studies. PD-L1 expression by immune cells was observed in 6% (235/3916) of tumours and expression by tumour cells was observed in just 1.7% (66/3916). PD-L1 was most frequently expressed in basal-like tumours. This was observed both where tumours were subtyped by combined copy number and expression profiling [39% (17/44) of IntClust 10 i.e. basallike tumours were PD-L1 immune cell positive; P < 0.001] and where a surrogate IHC-based classifier was used [19% (56/302) of basal-like tumours were PD-L1 immune cell positive; P < 0.001]. Moreover, CD274 (PD-L1) amplification was observed in five tumours of which four were IntClust 10. Expression of PD-L1 by either tumour cells or infiltrating immune cells was positively correlated with infiltration by both cytotoxic and regulatory T cells (P < 0.001). There was a nominally significant association between PD-L1 and improved disease-specific survival (hazard ratio 0.53, 95% confidence interval 0.26-1.07; P = 0.08) in ER-negative disease. Conclusions: Expression of PD-L1 is rare in breast cancer, markedly enriched in basal-like tumours and is correlated with infiltrating lymphocytes. PD-L1 inhibition may benefit the 19% of patients with basal-like tumours in which the protein is expressed. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved.

Forshew T.,Cancer Research UK Research Institute | Murtaza M.,Cancer Research UK Research Institute | Murtaza M.,University of Cambridge | Parkinson C.,Cancer Research UK Research Institute | And 22 more authors.
Science Translational Medicine | Year: 2012

Plasma of cancer patients contains cell-free tumor DNA that carries information on tumor mutations and tumor burden. Individual mutations have been probed using allele-specific assays, but sequencing of entire genes to detect cancer mutations in circulating DNA has not been demonstrated. We developed a method for tagged-amplicon deep sequencing (TAm-Seq) and screened 5995 genomic bases for low-frequency mutations. Using this method, we identified cancer mutations present in circulating DNA at allele frequencies as low as 2%, with sensitivity and specificity of >97%. We identified mutations throughout the tumor suppressor gene TP53 in circulating DNA from 46 plasma samples of advanced ovarian cancer patients. We demonstrated use of TAm-Seq to noninvasively identify the origin of metastatic relapse in a patient with multiple primary tumors. In another case, we identified in plasma an EGFR mutation not found in an initial ovarian biopsy. We further used TAm-Seq to monitor tumor dynamics, and tracked 10 concomitant mutations in plasma of a metastatic breast cancer patient over 16 months. This low-cost, high-throughput method could facilitate analysis of circulating DNA as a noninvasive "liquid biopsy" for personalized cancer genomics.

Abraham J.E.,University of Cambridge | Abraham J.E.,Cambridge Experimental Cancer Medicine Center | Guo Q.,University of Cambridge | Dorling L.,University of Cambridge | And 16 more authors.
Clinical Cancer Research | Year: 2014

Purpose: Associations between taxane-related sensory neuropathy (TRSN) and single-nucleotide polymorphisms (SNP) have previously been reported, but few have been replicated in large, independent validation studies. This study evaluates the association between previously investigated SNPs and TRSN, using genotype data from a study of chemotherapy-related toxicity in patients with breast cancer. Experimental Design: We investigated 73 SNPs in 50 genes for their contribution to TRSN risk, using genotype data from 1,303 European patients. TRSN was assessed using National Cancer Institute common toxicity criteria for adverse events classification. Unconditional logistic regression evaluated the association between each SNP and TRSN risk (primary analysis). Cox regression analysis assessed the association between each SNP and cumulative taxane dose causing the first reported moderate/severe TRSN (secondary analysis). The admixture likelihood (AML) test, which considers all SNPs with a prior probability of association with TRSN together, tested the hypothesis that certain SNPs are truly associated. Results: The AML test provided strong evidence for the association of some SNPs with TRSN (P=0.023). The two most significantly associated SNPs were rs3213619(ABCB1) [OR = 0.47; 95% confidence interval (CI), 0.28-0.79; P=0.004] and rs9501929(TUBB2A) (OR=1.80; 95% CI, 1.20-2.72; P=0.005). A further 9 SNPs were significant at P-value ≤ 0.05. Conclusion: This is currently the largest study investigating SNPs associated with TRSN. We found strong evidence that SNPs within genes in taxane pharmacokinetic and pharmacodynamic pathways contribute to TRSN risk. However, a large proportion of the inter-individual variability in TRSN remains unexplained. Further validated results from GWAS will help to identify new pathways, genes, and SNPs involved in TRSN susceptibility. © 2014 AACR.

Dawson S.-J.,University of Cambridge | Dawson S.-J.,Peter MacCallum Cancer Center | Tsui D.W.Y.,University of Cambridge | Murtaza M.,University of Cambridge | And 16 more authors.
New England Journal of Medicine | Year: 2013

BACKGROUND: The management of metastatic breast cancer requires monitoring of the tumor burden to determine the response to treatment, and improved biomarkers are needed. Biomarkers such as cancer antigen 15-3 (CA 15-3) and circulating tumor cells have been widely studied. However, circulating cell-free DNA carrying tumor-specific alterations (circulating tumor DNA) has not been extensively investigated or compared with other circulating biomarkers in breast cancer. METHODS: We compared the radiographic imaging of tumors with the assay of circulating tumor DNA, CA 15-3, and circulating tumor cells in 30 women with metastatic breast cancer who were receiving systemic therapy. We used targeted or whole-genome sequencing to identify somatic genomic alterations and designed personalized assays to quantify circulating tumor DNA in serially collected plasma specimens. CA 15-3 levels and numbers of circulating tumor cells were measured at identical time points. RESULTS: Circulating tumor DNA was successfully detected in 29 of the 30 women (97%) in whom somatic genomic alterations were identified; CA 15-3 and circulating tumor cells were detected in 21 of 27 women (78%) and 26 of 30 women (87%), respectively. Circulating tumor DNA levels showed a greater dynamic range, and greater correlation with changes in tumor burden, than did CA 15-3 or circulating tumor cells. Among the measures tested, circulating tumor DNA provided the earliest measure of treatment response in 10 of 19 women (53%). CONCLUSIONS: This proof-of-concept analysis showed that circulating tumor DNA is an informative, inherently specific, and highly sensitive biomarker of metastatic breast cancer. (Funded by Cancer Research UK and others.). Copyright © 2013 Massachusetts Medical Society.

Vire E.,University of Cambridge | Curtis C.,Cancer Research UK Research Institute | Curtis C.,University of Southern California | Davalos V.,Bellvitge Biomedical Research Institute IDIBELL | And 10 more authors.
Molecular Cell | Year: 2014

Amplification of the EMSY gene in sporadic breast and ovarian cancers is a poor prognostic indicator. Although EMSY has been linked to transcriptional silencing, its mechanism of action is unknown. Here, we report that EMSY acts as an oncogene, causing the transformation of cells invitro and potentiating tumor formation and metastatic features invivo. Weidentify an inverse correlation between EMSY amplification and miR-31 expression, an antimetastatic microRNA, in the METABRIC cohort of human breastsamples. Re-expression of miR-31 profoundly reduced cell migration, invasion, and colony-formation abilities of cells overexpressing EMSY or haboring EMSY amplification. We show that EMSY is recruited to the miR-31 promoter by the DNA binding factor ETS-1, and it represses miR-31 transcription bydelivering the H3K4me3 demethylase JARID1b/PLU-1/KDM5B. Altogether, these results suggest a pathway underlying the role of EMSY in breast cancer and uncover potential diagnostic and therapeutic targets in sporadic breast cancer. © 2014 The Authors.

Mohammed H.,Cancer Research UK Research Institute | D'Santos C.,Cancer Research UK Research Institute | Serandour A.A.,Cancer Research UK Research Institute | Ali H.R.,Cancer Research UK Research Institute | And 21 more authors.
Cell Reports | Year: 2013

Estrogen receptor-α (ER) is the driving transcription factor in most breast cancers, and its associated proteins can influence drug response, but direct methods for identifying interacting proteins have been limited. We purified endogenous ER using an approach termed RIME (rapid immunoprecipitation mass spectrometry of endogenous proteins) and discovered the interactome under agonist- and antagonist-liganded conditions in breast cancer cells, revealing transcriptional networks in breast cancer. The most estrogen-enriched ER interactor is GREB1, a potential clinical biomarker with no known function. GREB1 is shown to be a chromatin-bound ER coactivator and is essential for ER-mediated transcription, because it stabilizes interactions between ER and additional cofactors. We show a GREB1-ER interaction in three xenograft tumors, and using a directed protein-protein approach, we find GREB1-ER interactions in half of ER+ primary breast cancers. This finding is supported by histological expression of GREB1, which shows that GREB1 is expressed in half of ER+ cancers, and predicts good clinical outcome. These findings reveal an unexpected role for GREB1 as an estrogen-specific ER cofactor that is expressed in drug-sensitive contexts.

Ali H.R.,University of Cambridge | Ali H.R.,Cancer Research UK Research Institute | Dawson S.-J.,University of Cambridge | Dawson S.-J.,Cancer Research UK Research Institute | And 11 more authors.
Journal of Pathology | Year: 2012

There is an urgent need to improve prognostic classifiers in breast cancer. Ki67 and B-cell lymphoma 2 protein (BCL2) are established prognostic markers which have traditionally been assessed separately, in a dichotomous manner. This study was conducted to test the hypothesis that combinatorial assessment of these markers would provide superior prognostic information and improve their clinical utility. Tissue microarrays were used to assess the expression of Ki67 and BCL2 in 2749 cases of invasive breast cancer. We devised a Ki67/BCL2 index representing the relative expression of each protein and assessed its association with breast cancer-specific survival (BCSS) using a Cox proportional-hazards model. Based on our findings, an independent cohort of 3992 cases was used to validate the prognostic significance of the Ki67/BCL2 index. All survival analyses were conducted on complete data as well as data where missing values were resolved using multiple imputation. This study complied with reporting recommendations for tumour marker prognostic studies (REMARK) criteria. The Ki67/BCL2 index showed a significant association with BCSS at 10 years in estrogen receptor (ER)-positive disease. In multivariate analysis, adjusting for major clinical and molecular markers, the Ki67/BCL2 index retained prognostic significance, robustly classifying cases into three risk groups [intermediate- versus low-risk hazard ratio (HR), 1.5; 95% confidence interval (95% CI), 1.0-2.0; p = 0.031; high- versus low-risk HR, 2.6; 95% CI, 1.3-5.0; p = 0.005]. This finding was validated in an independent cohort of 3992 tumours containing 2761 ER-positive tumours (intermediate- versus low-risk HR, 1.7; 95% CI, 1.3-2.1; p < 0.001; high- versus low-risk HR, 2.0; 95% CI, 1.4-2.9; p < 0.001). Ki67 and BCL2 can be effectively combined to produce an index which is an independent predictor of BCSS in ER-positive breast cancer, enhancing their potential prognostic utility. Copyright © 2011 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

De Mattos-Arruda L.,University of Cambridge | De Mattos-Arruda L.,University of Barcelona | De Mattos-Arruda L.,Autonomous University of Barcelona | Caldas C.,University of Cambridge | Caldas C.,Cambridge Experimental Cancer Medicine Center
Molecular Oncology | Year: 2016

Recent developments in massively parallel sequencing and digital genomic techniques support the clinical validity of cell-free circulating tumour DNA (ctDNA) as a 'liquid biopsy' in human cancer. In breast cancer, ctDNA detected in plasma can be used to non-invasively scan tumour genomes and quantify tumour burden. The applications for ctDNA in plasma include identifying actionable genomic alterations, monitoring treatment responses, unravelling therapeutic resistance, and potentially detecting disease progression before clinical and radiological confirmation. ctDNA may be used to characterise tumour heterogeneity and metastasis-specific mutations providing information to adapt the therapeutic management of patients. In this article, we review the current status of ctDNA as a 'liquid biopsy' in breast cancer. © 2015 Federation of European Biochemical Societies.

Ali H.R.,University of Cambridge | Ali H.R.,Cancer Research UK Research Institute | Dawson S.-J.,University of Cambridge | Dawson S.-J.,Cancer Research UK Research Institute | And 9 more authors.
British Journal of Cancer | Year: 2012

Background: Proliferation has emerged as a major prognostic factor in luminal breast cancer. The immunohistochemical (IHC) proliferation marker Ki67 has been most extensively investigated but has not gained widespread clinical acceptance. Methods: We have conducted a head-to-head comparison of a panel of proliferation markers, including Ki67. Our aim was to establish the marker of the greatest prognostic utility. Tumour samples from 3093 women with breast cancer were constructed as tissue microarrays. We used IHC to detect expression of mini-chromosome maintenance protein 2, Ki67, aurora kinase A (AURKA), polo-like kinase 1, geminin and phospho-histone H3. We used a Cox proportional-hazards model to investigate the association with 10-year breast cancer-specific survival (BCSS). Missing values were resolved using multiple imputation. Results: The prognostic significance of proliferation was limited to oestrogen receptor (ER)-positive breast cancer. Aurora kinase A emerged as the marker of the greatest prognostic significance in a multivariate model adjusted for the standard clinical and molecular covariates (hazard ratio 1.3; 95% confidence interval 1.1-1.5; P=0.005), outperforming all other markers including Ki67. Conclusion: Aurora kinase A outperforms other proliferation markers as an independent predictor of BCSS in ER-positive breast cancer. It has the potential for use in routine clinical practice. © 2012 Cancer Research UK.

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