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      Biomarkers for Basal-like Breast Cancer

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          Abstract

          Initially recognized through microarray-based gene expression profiling, basal-like breast cancer, for which we lack effective targeted therapies, is an aggressive form of carcinoma with a predilection for younger women. With some success, immunohistochemical studies have attempted to reproduce the expression profile classification of breast cancer through identification of subtype-specific biomarkers. This review aims to present an in depth summary and analysis of the current status of basal-like breast cancer biomarker research. While a number of biomarkers show promise for future clinical application, the next logical step is a comprehensive investigation of all biomarkers against a gene expression profile gold standard for breast cancer subtype assignment.

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          Direct multiplexed measurement of gene expression with color-coded probe pairs.

          Gary K Geiss, Roger Bumgarner, Brian Birditt … (2008)
          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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            Gene-expression signatures in breast cancer.

            Christos Sotiriou, Lajos Pusztai (2009)
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              Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype.

              Maggie C. U. Cheang, David Voduc, Chris Bajdik … (2008)
              Basal-like breast cancer is associated with high grade, poor prognosis, and younger patient age. Clinically, a triple-negative phenotype definition [estrogen receptor, progesterone receptor, and human epidermal growth factor receptor (HER)-2, all negative] is commonly used to identify such cases. EGFR and cytokeratin 5/6 are readily available positive markers of basal-like breast cancer applicable to standard pathology specimens. This study directly compares the prognostic significance between three- and five-biomarker surrogate panels to define intrinsic breast cancer subtypes, using a large clinically annotated series of breast tumors. Four thousand forty-six invasive breast cancers were assembled into tissue microarrays. All had staging, pathology, treatment, and outcome information; median follow-up was 12.5 years. Cox regression analyses and likelihood ratio tests compared the prognostic significance for breast cancer death-specific survival (BCSS) of the two immunohistochemical panels. Among 3,744 interpretable cases, 17% were basal using the triple-negative definition (10-year BCSS, 6 7%) and 9% were basal using the five-marker method (10-year BCSS, 62%). Likelihood ratio tests of multivariable Cox models including standard clinical variables show that the five-marker panel is significantly more prognostic than the three-marker panel. The poor prognosis of triple-negative phenotype is conferred almost entirely by those tumors positive for basal markers. Among triple-negative patients treated with adjuvant anthracycline-based chemotherapy, the additional positive basal markers identified a cohort of patients with significantly worse outcome. The expanded surrogate immunopanel of estrogen receptor, progesterone receptor, human HER-2, EGFR, and cytokeratin 5/6 provides a more specific definition of basal-like breast cancer that better predicts breast cancer survival.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Cancers (Basel)
                Journal ID (iso-abbrev): Cancers (Basel)
                Journal ID (publisher-id): cancers
                Title: Cancers
                Publisher: MDPI
                ISSN (Electronic): 2072-6694
                Publication date (Electronic): 28 May 2010
                Publication date Collection: June 2010
                Volume: 2
                Issue: 2
                Pages: 1040-1065
                Affiliations
                Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada; E-Mail: jennchoo@ 123456interchange.ubc.ca
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: torsten@ 123456interchange.ubc.ca ; Tel.: +1-604-875-4111 ext. 66768; Fax: +1-604-875-4497.
                Article
                Publisher ID: cancers-02-01040
                DOI: 10.3390/cancers2021040
                PMC ID: 3835118
                PubMed ID: 24281106
                SO-VID: 166b3d54-e755-42e5-b8ef-e265827106c3
                Copyright © © 2010 by the authors; licensee MDPI, Basel, Switzerland.
                License:

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                Date received : 19 March 2010
                Date revision received : 11 May 2010
                Date accepted : 19 May 2010
                Categories
                Subject: Review

                Keywords: breast cancer,basal-like,biomarkers,intrinsic subtype,immunohistochemistry,triple-negative,basaloid,expression profile
                Data availability:
                Keywords: breast cancer, basal-like, biomarkers, intrinsic subtype, immunohistochemistry, triple-negative, basaloid, expression profile

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