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      Quantification of HER family receptors in breast cancer

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      Breast Cancer Research : BCR
      BioMed Central

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          Abstract

          The clinical success of trastuzumab in breast cancer taught us that appropriate tumor evaluation is mandatory for the correct identification of patients eligible for targeted therapies. Although HER2 protein expression by immunohistochemistry (IHC) and gene amplification by fluorescence in situ hybridization (FISH) assays are routinely used to select patients to receive trastuzumab, both assays only partially predict response to the drug. In the case of epidermal growth factor receptor (EGFR), the link between the presence of the receptor or its amplification and response to anti-EGFR therapies could not be demonstrated. Even less is known for HER3 and HER4, mainly due to lack of robust and validated assays detecting these proteins. It is becoming evident that, besides FISH and IHC, we need better assays to quantify HER receptors and categorize the patients for individualized treatments. Here, we present the current available methodologies to measure HER family receptors and discuss the clinical implications of target quantification.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13058-015-0561-8) contains supplementary material, which is available to authorized users.

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          Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2.

          The HER2 gene, which encodes the growth factor receptor HER2, is amplified and HER2 is overexpressed in 25 to 30 percent of breast cancers, increasing the aggressiveness of the tumor. We evaluated the efficacy and safety of trastuzumab, a recombinant monoclonal antibody against HER2, in women with metastatic breast cancer that overexpressed HER2. We randomly assigned 234 patients to receive standard chemotherapy alone and 235 patients to receive standard chemotherapy plus trastuzumab. Patients who had not previously received adjuvant (postoperative) therapy with an anthracycline were treated with doxorubicin (or epirubicin in the case of 36 women) and cyclophosphamide alone (138 women) or with trastuzumab (143 women). Patients who had previously received adjuvant anthracycline were treated with paclitaxel alone (96 women) or paclitaxel with trastuzumab (92 women). The addition of trastuzumab to chemotherapy was associated with a longer time to disease progression (median, 7.4 vs. 4.6 months; P<0.001), a higher rate of objective response (50 percent vs. 32 percent, P<0.001), a longer duration of response (median, 9.1 vs. 6.1 months; P<0.001), a lower rate of death at 1 year (22 percent vs. 33 percent, P=0.008), longer survival (median survival, 25.1 vs. 20.3 months; P=0.01), and a 20 percent reduction in the risk of death. The most important adverse event was cardiac dysfunction of New York Heart Association class III or IV, which occurred in 27 percent of the group given an anthracycline, cyclophosphamide, and trastuzumab; 8 percent of the group given an anthracycline and cyclophosphamide alone; 13 percent of the group given paclitaxel and trastuzumab; and 1 percent of the group given paclitaxel alone. Although the cardiotoxicity was potentially severe and, in some cases, life-threatening, the symptoms generally improved with standard medical management. Trastuzumab increases the clinical benefit of first-line chemotherapy in metastatic breast cancer that overexpresses HER2.
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            Direct multiplexed measurement of gene expression with color-coded probe pairs.

            We describe a technology, the NanoString nCounter gene expression system, which captures and counts individual mRNA transcripts. Advantages over existing platforms include direct measurement of mRNA expression levels without enzymatic reactions or bias, sensitivity coupled with high multiplex capability, and digital readout. Experiments performed on 509 human genes yielded a replicate correlation coefficient of 0.999, a detection limit between 0.1 fM and 0.5 fM, and a linear dynamic range of over 500-fold. Comparison of the NanoString nCounter gene expression system with microarrays and TaqMan PCR demonstrated that the nCounter system is more sensitive than microarrays and similar in sensitivity to real-time PCR. Finally, a comparison of transcript levels for 21 genes across seven samples measured by the nCounter system and SYBR Green real-time PCR demonstrated similar patterns of gene expression at all transcript levels.
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              Supervised risk predictor of breast cancer based on intrinsic subtypes.

              PURPOSE To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression-based "intrinsic" subtypes luminal A, luminal B, HER2-enriched, and basal-like. METHODS A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen. The intrinsic subtypes as discrete entities showed prognostic significance (P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for the combined model (subtype and tumor size) was a significant improvement on either the clinicopathologic model or subtype model alone. The intrinsic subtype model predicted neoadjuvant chemotherapy efficacy with a negative predictive value for pCR of 97%. CONCLUSION Diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer. The prognostic properties of the continuous risk score will be of value for the management of node-negative breast cancers. The subtypes and risk score can also be used to assess the likelihood of efficacy from neoadjuvant chemotherapy.
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                Author and article information

                Contributors
                pnuciforo@vhio.net
                nina.radosevic.robin@gmail.com
                tony.ng@kcl.ac.uk
                scaltrim@mskcc.org
                Journal
                Breast Cancer Res
                Breast Cancer Research : BCR
                BioMed Central (London )
                1465-5411
                1465-542X
                9 April 2015
                9 April 2015
                2015
                : 17
                : 1
                : 53
                Affiliations
                [ ]Molecular Oncology Laboratory, Vall d’Hebron Institute of Oncology, Passeig Vall d’Hebron 119–129, Barcelona, 08035 Spain
                [ ]Universitat Autònoma de Barcelona, Barcelona, 08035 Spain
                [ ]ERTICa Research Group, University of Auvergne EA4677, 63000 Clermont-Ferrand, France
                [ ]Biopathology, Jean Perrin Comprehensive Cancer Center, 58 rue Montalembert, 63011 Clermont-Ferrand, France
                [ ]Richard Dimbleby Department of Cancer Research, Randall Division of Cell and Molecular Biophysics and Division of Cancer Studies, King’s College London, London, SE1 1UL UK
                [ ]UCL Cancer Institute, Paul O’Gorman Building, University College London, London, WC1E 6DD UK
                [ ]Breakthrough Breast Cancer Research Unit, Department of Research Oncology, Guy’s Hospital King’s College London School of Medicine, London, SE1 9RT UK
                [ ]Human Oncology and Pathogenesis Program (HOPP), Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 20, New York, NY 10065 USA
                Article
                561
                10.1186/s13058-015-0561-8
                4389676
                25887735
                d4ae8c24-766c-4eef-9b2b-91824c02e1aa
                © Nuciforo et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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                Oncology & Radiotherapy
                Oncology & Radiotherapy

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