Type 1 Receptor Tyrosine Kinase Profiles Identify Patients With Enhanced Benefit From Anthracyclines in the BR9601 Adjuvant Breast Cancer Chemotherapy Trial

Bartlett, John M.S.; Munro, Alison F.; Cameron, David; Thomas, Jeremy; Prescott, R. J.; Twelves, Chris

doi:10.1200/jco.2007.14.6597

Cited by 91 publications

(84 citation statements)

References 33 publications

(4 reference statements)

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“…Analysis of Chr17CEP duplication in BR9601, NEAT and MA.5 suggests chromosome 17 to be an independent predictive marker of anthracycline sensitivity. Therefore, Chr17CEP duplication provides the first unifying hypothesis of anthracycline response within three trials for which the HER2 data are opposing (Di Leo et al, 2004Leo et al, , 2009Knoop et al, 2005;Pritchard et al, 2006;Reinholz et al, 2007;Bartlett et al, 2008Bartlett et al, , 2009aBartlett et al, , b, 2010. Analysis of Chr17CEP in tumours recruited into the Belgian trial is near completion, which would allow a meta-analysis of chromosome 17 in 2975 patients.…”

Section: Chromosome 17 Centromere Duplicationmentioning

confidence: 99%

Targeting anthracyclines in early breast cancer: new candidate predictive biomarkers emerge

2010

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The search for a predictive marker of sensitivity to anthracycline-based chemotherapy has proven challenging. Despite human epidermal growth factor receptor 2 (HER2) being a strong prognostic marker in breast cancer, the only therapies with which there is a recognized functional link to the HER2 oncogene are those directly targeting the molecule itself. Despite this, HER2 has been extensively assessed as a predictive marker in a variety of chemotherapy regimens including anthracyclines. Analysis of anthracycline response in patients with HER2 amplification has given conflicting results. This led to the suggestion that HER2 amplification was acting as a surrogate for the gene encoding topoisomerase IIa (TOP2A), a direct cellular target of anthracyclines. Despite an attractive functional link between TOP2A and anthracyclines, published studies have failed to show strong evidence of an interaction between TOP2A genetic aberrations and anthracycline response. A number of other biomarkers have also been assessed for their role in predicting anthracycline response, including TP53 (tumour protein 53) and BRCA1 (breast cancer 1, early onset), together with an increasing emergence of gene expression profiling to produce predictive signatures of response. Moreover, recent evidence has emerged from presentations suggesting new candidate markers of response that warrant further investigation: Chr17CEP duplication and tissue inhibitor of metalloproteases 1. This review will discuss research into HER2 and TOP2A as predictive markers of anthracycline response and will focus on current research into other possible candidate predictive markers.

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Section: Chromosome 17 Centromere Duplicationmentioning

confidence: 99%

Targeting anthracyclines in early breast cancer: new candidate predictive biomarkers emerge

2010

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“…14 Trials have shown that the overexpression, amplification and deletion of topo-IIa does indeed appear to be predictive of anthracycline response 33,34 while others have suggested that the normal expression of Her1 to 3 may be predictive, 35 but whether the true relationship is with HER2 or topo-IIa remains unclear. At this point in time, it appears that the topo-IIa story is not definitive enough to change clinical practice.…”

Section: Predicting Anthracycline Efficacy: Topoisomerase II Alpha (Tmentioning

confidence: 99%

Use of non‐anthracycline regimens in early stage breast cancer in Australia

Boer

Chan

Wilcken

2010

Asia-Pac J Clncl Oncology

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Various factors have recently prompted a re-evaluation of the role of non-anthracycline regimens in early stage breast cancer (ESBC). Since 1990 anthracyclines have been a key component of chemotherapy regimens. However, there is increased understanding of the long-term, irreversible toxicities associated with these therapies, including cardiac failure and secondary leukemia. The development of the taxanes in the 1990s led to new adjuvant chemotherapy regimens and trials of various combinations in an effort to further increase survival and reduce toxicity. Concerns about cardiac toxicity were reinforced with the emergence of trastuzumab for the treatment of HER2-positive breast cancer. Trastuzumab alone causes cardiac toxicity and increases the risk of cardiac toxicity when combined with anthracyclines. These data, combined with recent results demonstrating the efficacy of non-anthracycline regimens in various disease settings, have generated interest in utilizing these therapies in patients with both HER2-positive and -negative tumors. This review outlines the evidence for the use of non-anthracycline adjuvant regimens in ESBC, including cyclophosphamide, methotrexate and 5-fluoruoracil, docetaxel, carboplatin and trastuzumab and docetaxel and cyclophosphamide, which have demonstrated equivalent efficacy and reduced toxicity compared to anthracycline-based regimens in various trials. The review also examines evidence for the use of nonanthracycline regimens in patients who previously had restricted access to these therapies due to their negative lymph node status. The wider availability of these regimens increases options when deciding upon adjuvant chemotherapy for patients with ESBC, especially in patients with a high risk of cardiac toxicity.

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“…First, the molecular differences that exist between breast cancers (Perou et al, 2000;Pollack et al, 2002;Desmedt et al, 2004) support treating different molecular subtypes on the basis of their biology and pathology rather than on pathology alone. Second, clear evidence that molecular subtypes of cancer respond differently to different therapeutic options challenges the 'one size fits all' approach to chemotherapy in cancer (Hayes et al, 2007;Bartlett et al, 2008Bartlett et al, , 2009aBartlett et al, , b, 2010Pritchard et al, 2008;Ellis et al, 2009).…”

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confidence: 99%

Tamoxifen resistance in early breast cancer: statistical modelling of tissue markers to improve risk prediction

et al. 2010

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BACKGROUND: For over two decades, the Nottingham Prognostic Index (NPI) has been used in the United Kingdom to calculate risk scores and inform management about breast cancer patients. It is derived using just three clinical variables -nodal involvement, tumour size and grade. New scientific methods now make cost-effective measurement of many biological characteristics of tumour tissue from breast cancer biopsy samples possible. However, the number of potential explanatory variables to be considered presents a statistical challenge. The aim of this study was to investigate whether in ER þ tamoxifen-treated breast cancer patients, biological variables can add value to NPI predictors, to provide improved prognostic stratification in terms of overall recurrence-free survival (RFS) and also in terms of remaining recurrence free while on tamoxifen treatment (RFoT). A particular goal was to enable the discrimination of patients with a very low risk of recurrence. METHODS: Tissue samples of 401 cases were analysed by microarray technology, providing biomarker data for 72 variables in total, from AKT, BAD, HER, MTOR, PgR, MAPK and RAS families. Only biomarkers screened as potentially informative (i.e., exhibiting univariate association with recurrence) were offered to the multivariate model. The multiple imputation method was used to deal with missing values, and bootstrap sampling was used to assess internal validity and refine the model. RESULTS: Neither the RFS nor RFoT models derived included Grade, but both had better predictive and discrimination ability than NPI. A slight difference was observed between models in terms of biomarkers included, and, in particular, the RFoT model alone included HER2. The estimated 7-year RFS rates in the lowest-risk groups by RFS and RFoT models were 95 and 97%, respectively, whereas the corresponding rate for the lowest-risk group of NPI was 89%.CONCLUSION: The findings demonstrate considerable potential for improved prognostic modelling by incorporation of biological variables into risk prediction. In particular, the ability to identify a low-risk group with minimal risk of recurrence is likely to have clinical appeal. With larger data sets and longer follow-up, this modelling approach has the potential to enhance an understanding of the interplay of biological characteristics, treatment and cancer recurrence.

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Type 1 Receptor Tyrosine Kinase Profiles Identify Patients With Enhanced Benefit From Anthracyclines in the BR9601 Adjuvant Breast Cancer Chemotherapy Trial

Cited by 91 publications

References 33 publications

Targeting anthracyclines in early breast cancer: new candidate predictive biomarkers emerge

Targeting anthracyclines in early breast cancer: new candidate predictive biomarkers emerge

Use of non‐anthracycline regimens in early stage breast cancer in Australia

Tamoxifen resistance in early breast cancer: statistical modelling of tissue markers to improve risk prediction

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