Annals of Oncology Advance Access published online on October 25, 2009
Annals of Oncology, doi:10.1093/annonc/mdp427
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Quantitative analysis of changes in ER, PR and HER2 expression in primary breast cancer and paired nodal metastases
Edinburgh Breakthrough Research Unit and Division of Pathology, University of Edinburgh, Edinburgh, UK
* Correspondence to: Dr D. Faratian, Edinburgh Breakthrough Research Unit and Division of Pathology, Crewe Road South, Edinburgh EH4 2XU, UK. Tel: +44-131-537-1763; Fax: +44-131-537-3159; E-mail: d.faratian{at}ed.ac.uk
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abstract |
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Background: Assessment of receptors [estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2)] is routinely carried out on primary tumour in order to select appropriate adjuvant therapy; the same analysis is not carried out on nodal metastases. Since de novo resistance to therapy is common, we quantified differences in receptor expression between primary and nodal disease in order to assess whether this might contribute to therapeutic resistance.
Patients and methods: A total of 385 patients with invasive primary breast carcinomas and paired lymph nodes (n = 211) were assessed for ER, PR and HER2 expression using quantitative immunofluorescence. Cut-points were defined by comparison with tumours scored by immunohistochemistry (IHC) and FISH. Differences in expression for each of the markers and molecular phenotype were analysed.
Results: Quantitative receptor expression shows a wide dynamic range compared with IHC. Overall, 46.9% cases had disparate breast/node receptor status of at least one receptor. Many of the differences in expression between primary tumour and node are large magnitude (greater than fivefold) changes. Triple-negative phenotype changes in 23.1% of cases.
Conclusions: A significant number of patients show discordant quantitative expression of molecular markers between primary and nodal disease. Appropriately measured, lymph node receptor status could be a more accurate measurement for guiding adjuvant therapy, which requires testing in a clinical trial.
breast cancer, ER, HER2, image analysis, molecular phenotype, nodal metastases, PR
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introduction |
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Breast cancer is the most common cancer in the UK (excluding nonmelanoma skin cancer), with
46 000 new cases and 12 000 deaths per year [1]. In addition to pathological grade and stage, breast cancers are routinely assessed for hormone receptor status [estrogen receptor (ER) 
] by immunohistochemistry (IHC) and human epidermal growth factor receptor 2 (HER2) expression by IHC or amplification by FISH [2] in order to guide the choice of the appropriate adjuvant therapy. Patients with ER-positive primary tumours are offered adjuvant hormone therapy, routinely tamoxifen for 5 years, while postmenopausal women may receive an aromatase inhibitor [3]. Patients with overexpression of HER2 are eligible for trastuzumab, a mAb that targets the Her2/neu receptor. However, 60% of patients derive no benefit from endocrine therapies, and only 30%–40% of trastuzumab patients benefit [4, 5]. Therefore, either de novo or acquired resistance is common. New tissue biomarkers are being actively sought in order to predict response based on underlying molecular biology [6], but few of these, if any, are used in routine clinical practice [7, 8]. Decisions regarding adjuvant therapy are based on the molecular pathology of the diagnostic core biopsy or resection specimen from the primary tumour. Receptor expression is assumed to be identical in corresponding nodal disease. If receptor expression levels in metastatic disease differ from the primary tumour (e.g. ER-positive breast to ER-negative node), this might be an important reason for treatment failure. Cancer is a complex disease which displays considerable heterogeneity at tumour and molecular level [9], and a comprehensive analysis of the differences in receptor expression between primary and nodal disease is required.
Analysis of ER and HER2 expression levels is conventionally carried out using subjective human assessment of staining using the histoscore or simplified scoring systems (e.g. Allred), and despite evidence that such approaches can be robust [10], novel high-throughput image analysis technologies offer the opportunity to produce accurate and reproducible results removing human error [10–13]. In addition, analysis of progesterone receptor (PR) allows identification of ‘triple-negative phenotype’ (TNP) (ER–, PR– and HER2–), a surrogate for the basal-like molecular phenotype, which may be an important prognostic group amenable to novel targeted therapy and currently the subject of intensive study [14]. We therefore decided to quantitatively measure expression of therapeutically relevant proteins (ER, PR and HER2) in matched primary and nodal breast cancers on tissue microarrays (TMAs) constructed from a large series of 385 patients with primary breast cancer, 211 of which had paired nodal metastases. Using immunofluorescence on intact tissue sections allows quantitative measurement of proteins while maintaining spatial information provided by traditional IHC [15].
The aims of this study were to (i) validate the quantitative expression of ER, PR and HER2 against traditional scoring methods, (ii) compare quantitative changes in ER, PR and HER2 expression between primary and nodal disease and (iii) compare changes in TNP between primary and nodal breast cancer.
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patients and methods |
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study population and TMA construction
The study population originally consisted of 521 patients with primary breast carcinomas treated in the Edinburgh Breast Unit from 1999 to 2002 as previously described (Table 1 and [16]). All received axillary lymph node dissection as part of surgery for a large or high-grade invasive breast carcinoma, in the absence of a known history of distant metastasis [16]. This study was approved by the Lothian Research Ethics Committee (08/S1101/41) and MREC (04/S0709/16). All 521 surgical breast resections were matched with corresponding lymph nodes from axillary lymph node dissection, of which 334 contained metastases. After TMA construction, immunostaining, AQUAsition and AQUAnalysis, there were 385 primary and 211 nodal cancers remaining for statistical analysis. Six TMAs were constructed in biological triplicates using established techniques [17].
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immunofluorescence
A detailed description of the AQUA HistoRx methodology is available elsewhere [15, 18]. Briefly, antigen retrieval was carried out using heat treatment under pressure in a microwave oven for 5 min in citrate buffer pH 6.0, slides were incubated with primary antibodies: AE1/AE3 mouse monoclonal cytokeratin, ER
[Vector (VP_E613)], PR [Dako (M3569)] and HER2 [Dako (K5207)] diluted 1 : 50 in 0.025% phosphate-buffered saline Tween 20 for 60 min at room temperature. Pan-cytokeratin antibody was used to identify infiltrating tumour cells and normal epithelial cells, DAPI (4',6-diamidino-2-phenylindole) counterstain to identify nuclei and Cy-5–tyramide detection for target (ER, PR and HER2) for compartmentalised (tissue and subcellular) analysis of tissue sections (Figure 1).
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immunohistochemistry
IHC was carried out according to standard protocols. Briefly, TMA sections were dewaxed in xylene and rehydrated, antigen retrieval was carried out as above, sections were blocked for endogenous peroxidase, followed by antibody incubation (see above). Staining was developed using EnVision and diamino benzidine before slides were counterstained in haematoxylin, dehydrated and mounted in neutral disterene dibutyl phthalate xylene.
manual evaluation of IHC
One breast TMA containing 156 cores of primary breast tumours and paired node TMA (92 cores) were scored for ER (Allred 0–8), PR (Allred 0–8) and HER2 (HerceptTest 0, 1+, 2+, 3+) by two independent observers (SJA and DF), one of whom is a pathologist, following training in IHC as described previously [10].
FISH
FISH was carried out in order to identify HER2-amplified tumours, according to the manufacturer's instructions (DAKO PharmDx). One breast TMA (156 cores) and matched node TMA (92 cores) were studied. Twenty nuclei in each core were scored, and a ratio calculated: <1.8 (gene = red : centromere = green) scored negative, 1.8–2.2 scored borderline and >2.2 scored positive, according to current guidelines [19].
AQUA image analysis
AQUA HistoRx image analysis was used to visualise and quantify protein expression, as described previously [15]. Using AQUAsition software, monochromatic images of each TMA core were acquired at x20 objective through DAPI, CY3 and CY5 channels using an Olympus AX-51 epifluorescence microscope. These high-resolution digital images were then analysed using AQUAnalysis software.
protein expression analysis
AQUAnalysis software was used to calculate the quantity (AQUA units = Au) of target protein within the nuclei/cytoplasm for each protein. Images were manually quality checked (SJA and DF) to crop aberrant imaging artefacts and exclude them from analysis. Additionally, all normal mammary ducts and ductal carcinoma in situ (DCIS) were cropped to ensure that only invasive cancer was included in the analysis. If the epithelium comprised <5% of total core area, the core was excluded to ensure that a sufficient area of representative tumour was available for analysis, as previously described [15].
statistical analysis
AQUAsition data were matched to anonymised TMA maps, and mean AQUA scores were calculated for corresponding triplicate cores. The interobserver variation between the scoring of nuclear ER and PR and membrane HER2 by manual and automated methods was assessed by measuring Pearson regression coefficients (PRC). All P values were calculated using two-tailed Student's t-tests. Thresholds for negative ER, PR and HER2 were calculated using a stringent method of mean + 2 SD of the AQUA scores for all IHC and FISH-negative cores (IHC: Allred 0–2, HercepTest 
2+, FISH: <1.8).
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receptor expression measured by quantitative analysis shows a wide dynamic range of expression compared with traditional scoring methods
After TMA construction, staining, scanning and analysis, 385 patients were included in the full analysis (of the original 521). The primary tumour size, grade and node status are shown in Table 1.
In order to establish whether quantitative image analysis showed advantages over traditional scoring methods and to define cut-points (negative versus positive), we compared AQUA scores with IHC (Allred and HerceptTest) and FISH. Cut-points were ER = 58Au, PR = 43Au and HER2 = 433Au (HER2 IHC = 392Au, HER2 FISH = 475Au), defined as described in the ‘Materials and methods’ section. Representative immunofluorescence for ER, PR and HER2 are shown in Figure 1. One breast TMA (156 cores) and matched node TMA (92 cores) were scored; all cores that were scored HER2 positive on IHC were also FISH positive (n = 29), and all but two IHC-negative cores (n = 219, 99%) were also FISH negative. AQUA scores for ER, PR and HER2 show a good correlation with IHC (PRC: r = 0.66, 0.68 and 0.50, respectively). There is a continuous distribution of AQUA scores, with a particularly wide distribution at higher IHC scores (Figure 2); ER Allred 8 shows scores from 275–1200Au. This demonstrates the value of quantitative analysis, especially at higher intensity staining. This led us to investigate whether accurate quantitative measurement of receptor expression could detect significant differences between primary tumours and nodal disease.
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quantitative changes in receptor expression occur between primary and nodal disease
Since changes in receptor expression in nodal disease could alter therapeutic response to endocrine therapy or trastuzumab, we initially investigated whether there were binary differences in receptor expression (i.e. positive breast with negative lymph node or vice versa) using cut-points described above and subsequently the magnitude of change between primary and nodal disease.
Most primary tumours retained their original status in nodal metastases for all three markers. Of the 84 ER-negative and 110 ER-positive tumours, 139 (71.6%) had the same node status, but 35 ER-positive and 20 ER-negative tumours showed binary changes in expression as measured by AQUA (i.e. positive to negative or vice versa). PR expression followed a similar trend, with 147 (76.5%) remaining PR negative or PR positive, 28 switching from PR positive to PR negative and a further 17 cases from PR negative to PR positive. A higher proportion of HER2 retained their original status (n = 173, 91.1%) (Table 2). In order to establish whether these binary changes in receptor expression were of low magnitude, and therefore unlikely to be of clinical significance, we investigated the magnitude of change between primary and nodal receptor expression.
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Although the average change in AQUA score was not significantly different between primary and nodal disease (Student's t-test, P = 0.66, 0.84 for ER and PR, respectively), many cases had both binary and large quantitative changes in expression of molecular markers; 17.5% and 13.0% of tumours showed twofold or greater decrease in ER or PR expression, with 8.2% and 7.8% showing twofold or greater increase in expression. Furthermore 11.3% and 10.4% of tumours showed fivefold or greater decrease in ER and PR expression, with 4.1% and 4.2% showing fivefold or greater increase in expression (Figure 3).
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Overall, HER2 expression in nodal disease was significantly higher (461Au, n = 195) than primary disease (235Au, n = 379) (Student's t-test, P = 0.00001). Of the 14 HER2-positive primary tumours with HER2-negative nodes, all showed a twofold or greater decrease, and 12 had a fivefold decrease or greater; of the three HER2-negative breast tumours with HER2-positive nodes, all had twofold or greater increase, and two had fivefold or greater increase. Within the subset of tumours scored using AQUA, IHC and FISH, there were several examples displaying disparity between breast and node HER2 status, which was confirmed by all three methodologies.
changes in TNP between primary and nodal breast cancer
A three-marker molecular phenotype was defined for each primary and secondary tumour (ER, PR and HER2); tumours with incomplete profiles were not classified.
In this series, 39 primary tumours (18.6%) were TNP, in line with previous data [14]. Of this group of poor prognosis cancers, 30 (76.9%) also had corresponding TNP nodes (Table 3). Of those with a different nodal phenotype, five (12.8%) and three (7.7%) changed to ER/PR-positive or HER2-positive, respectively, with a mean change of 165Au for ER (n = 5), 214Au for PR (n = 2) and 1372Au for HER2 (n = 3).
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discussion |
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It is well established that there is heterogeneous expression of molecular markers between different breast cancer patients. However, there is relatively little information on how expression differs within the same patient i.e. between primary and metastatic disease. For the purposes of therapy and clinical trial design, the assumption is made that any remaining locoregional, distant or micro metastatic disease is identical in molecular phenotype to the primary lesion, although molecular analysis in primary tumour is also dictated by availability of material. However, this may be not appropriate since secondary disease has acquired new biological characteristics in order to gain access to blood vessels/lymphatics, travel through circulating blood/lymph and colonise a remote site [20]. Some of these molecular alterations may be associated with changes in receptor status since endocrine and growth signalling pathways have been shown to be involved in invasion and metastasis [21, 22]. This heterogeneity might account for a significant proportion of treatment failure since distant disease is more likely to be the target for adjuvant systemic therapy after initial surgery and radiotherapy. Indeed, local relapse rates for breast cancer are very low (3.1%) [23]. Translational studies of predictive tissue biomarkers within phase III clinical trials all measure primary tumour receptor expression; heterogeneity between primary and metastatic disease is consequently a neglected area of study which might impact on trial analysis. We therefore sought to investigate quantitative differences in receptor expression levels between primary and nodal disease, which may be an alternative explanation for therapeutic resistance to targeted therapy in breast cancer. Using a combination of TMA and AQUA technology, we examined large numbers (n = 385) of primary tumours and paired lymph node metastases (n = 211), in triplicate, for three molecular markers, which is the largest study of its kind to scrutinise all three markers.
Manual scoring of ER, PR and HER2 relies on human observers estimating the percentage and/or intensity of reactive cells, resulting in semi-quantitative and categorical variables (Allred 0–8 for ER/PR, 0–3 for HER2). These are then reported as ER ‘positive’ (Allred 3–8) or ‘negative’ (Allred 0–2), according to clinical practice and inclusion in endocrine therapy trials [24]. Previous attempts have been made at manual quantification of staining, but we have used more accurate quantitative immunofluorescence to measure protein expression [15]. We have shown that there is a continuous spectrum of ER expression, with ER-negative tumours (Allred 0–2) scoring <58Au, Allred 3–7 corresponding to 58–274Au and Allred 8 showing a wide range from 275 to 1200Au. This wide dynamic range of staining is missed by conventional IHC scoring because visually they all appear the same (Allred 8). Understanding and quantifying heterogeneity of expression is especially critical since it is emerging that response to therapy is often a quantitative phenomenon dependent on the concentration of protein within the tissue, indicating that robust quantitative methodologies are important in molecular analyses [15, 25, 26].
Analysing ER, PR and HER2 expression showed that approximately one-third (n = 82, 39.0%) of cases have a different molecular phenotype between primary and secondary tumours. Thirty-five cases (18.0%) changed from ER-positive breast to ER-negative node (comparable to [27, 28]), of which 31 had twofold or greater decrease and 23 had fivefold or greater decrease. A further 20 cases (10.3%) changed from ER-negative breast to ER-positive node, of which 18 had more than twofold increase and 10 had more than fivefold increase in expression. This is in keeping with previous studies, where it has been shown that discordant cases more commonly shift from positive breast to negative node than vice versa [29, 30]. Since a proportion of ER-positive patients fail to respond to tamoxifen and have a poor outcome, it is possible that patients with ER-positive primary tumour but ER-negative nodes are inappropriately treated with endocrine therapy and might therefore be spared unnecessary therapy and unpleasant side-effects. Also, the wide range of expression of ER at Allred 8 scores might predict a range of responsiveness. Overall, HER2 expression is twice as high in nodal metastases compared with primary disease, and 9.9% of patients display disparity in HER2 status. In this instance, a majority of these are from HER2-negative breast to HER2-positive nodes; these patients with ‘HER2-negative’ disease are denied trastuzumab despite the potential to manage their systemic disease. In all, 79.9% of patients with changed receptor status had not received any neoadjuvant therapy, so while this may have an effect, most changes are independent of therapy.
More recently, new molecular subgroups of breast cancers have been defined by gene expression profiles [14, 31]. TNP and basal-like breast cancers tend to be higher grade and have a poorer prognosis than other molecular subtypes [14, 31]. By definition, they are not amenable to traditional endocrine therapies or trastuzumab, although they may be more sensitive to platinum-based therapy [14]. We have shown that TNP primary tumours are only associated with TNP nodal disease in 76.9% (n = 39) cases, indicating that following surgical resection and identification of ER-positive or HER-positive nodes, these patients might respond to hormone/biological therapy for which they are not currently considered. Therefore, not only do changes occur, as previously described, but also the magnitude of change in expression is frequently very large, which might influence treatment response.
In the current study, a higher proportion of cases show disparate receptor status between primary and nodal disease compared with some previous studies [32–39] (for a full comparison with published literature, see Table 4 [27–30, 32–46]), for which there are several possible explanations. First, we have used a different means of measurement which is more sensitive than traditional methods (AQUA versus manual IHC), which might explain some changes in nodal expression which would not be detected by IHC. Secondly, we have used TMAs rather than whole sections, and although this methodology has been validated as representative of whole sections [47], we cannot exclude that some differences may be due to core selection bias. Finally, our study population is biased towards patients with large or high-grade invasive breast carcinomas, while other studies include a broader population of patients. It was shown in [40, 44–46] that patients with distant metastases showed lower concordance between breast and metastases than those where only local lymph nodes were included. This indicates that in more advanced disease there is more likely to be a receptor status/phenotype change, which may be reflected in our high-grade tumour population.
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Given that nodes are excised in standard surgical practice, as sentinel node biopsy, axillary node sample, or node clearance, and assessed by a pathologist for routine staging, our data show that there may be added benefit to molecular testing on nodal metastases as well as the primary tumour in order to guide adjuvant therapy. While this might incur additional financial costs for specimen processing and molecular analysis, savings could be made by avoiding overtreatment. This would reduce morbidity for patients and ultimately has to potential to produce more favourable clinical outcomes.
While a majority of patients have the same receptor status in both primary and nodal disease, some do vary, whose postoperative management might be different if this information was available. Using new high-throughput technology, we have highlighted the quantitative changes that occur in receptor expression within a patient, which may confer increase therapeutic sensitivity or resistance to targeted therapy. Unfortunately, the current study is underpowered to demonstrate the effect of differing node expression on clinical outcome. Ultimately, the effect of stratifying patients on the basis of nodal receptor expression will need to be tested in the context of a prospective phase III clinical trial.
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Breakthrough Breast Cancer; Scottish Funding Council (Strategic Research Development Grant) (HR07005); molecular pathology on tissue was supported by the Edinburgh CRUK Experimental Cancer Medicine Centre.
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The authors would like to thank InHwa Um and Dawn Lyster for technical help with TMA construction and John Bartlett for helpful advice during the early phase of this work.
Received for publication June 6, 2009. Revision received July 29, 2009. Accepted for publication July 30, 2009.
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1. Office for National Statistics. Cancer Statistics Registrations: Registrations of Cancer Diagnosed in 2006 (2009) London: Office for National Statistics. (Report No.: MB1 no. 37).
2. Payne SJ, Bowen RL, Jones JL, Wells CA. Predictive markers in breast cancer—the present. Histopathology (2008) 52(1):82–90.[Web of Science][Medline]
3. Carlson RW, Hudis CA, Pritchard KI. Adjuvant endocrine therapy in hormone receptor-positive postmenopausal breast cancer: evolution of NCCN, ASCO, and St Gallen recommendations. J Natl Compr Cancer Netw (2006) 4(10):971–979.
4. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet (2005) 365(9472):1687–1717.[CrossRef][Web of Science][Medline]
5. Smith I, Procter M, Gelber RD, et al. 2-Year follow-up of trastuzumab after adjuvant chemotherapy in HER2-positive breast cancer: a randomised controlled trial. Lancet (2007) 369(9555):29–36.[CrossRef][Medline]
6. Faratian D, Bartlett J. Predictive markers in breast cancer—the future. Histopathology (2008) 52(1):91–98.[Web of Science][Medline]
7. Faratian D, Clyde R, Crawford J, Harrison D. Systems pathology—taking molecular pathology into a new dimension. Nat Rev Clin Oncol (2009) 6(8):455–464.[CrossRef][Web of Science][Medline]
8. Faratian D, Moodie SL, Harrison DJ, Goryanin I. Dynamic computational modeling in the search for better breast cancer drug therapy. Pharmacogenomics (2007) 8(12):1757–1761.[CrossRef][Web of Science][Medline]
9. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell (2000) 100(1):57–70.[CrossRef][Web of Science][Medline]
10. Kirkegaard T, Edwards J, Tovey S, et al. Observer variation in immunohistochemical analysis of protein expression, time for a change? Histopathology (2006) 48(7):787–794.[CrossRef][Web of Science][Medline]
11. Adams EJ, Green JA, Clark AH, Youngson JH. Comparison of different scoring systems for immunohistochemical staining. J Clin Pathol (1999) 52(1):75–77.[Abstract]
12. van Diest PJ, Weger DR, Lindholm J. Reproducibility of subjective immunoscoring of steroid receptors in breast cancer. Anal Quant Cytol Histol (1996) 18(5):351–354.[Web of Science][Medline]
13. Faratian D, Kay C, Robson T, et al. Automated image analysis for high-throughput quantitative detection of ER and PR expression levels in large-scale clinical studies: the TEAM Trial Experience. Histopathology (2009) in press.
14. Reis-Filho JS, Tutt AN. Triple negative tumours: a critical review. Histopathology (2008) 52(1):108–118.[Web of Science][Medline]
15. Camp RL, Chung GG, Rimm DL. Automated subcellular localization and quantification of protein expression in tissue microarrays. Nat Med (2002) 8(11):1323–1327.[CrossRef][Web of Science][Medline]
16. Somner JE, Dixon JM, Thomas JS. Node retrieval in axillary lymph node dissections: recommendations for minimum numbers to be confident about node negative status. J Clin Pathol (2004) 57(8):845–848.
17. Kononen J, Bubendorf L, Kallioniemi A, et al. Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat Med (1998) 4(7):844–847.[CrossRef][Web of Science][Medline]
18. Giltnane JM, Molinaro A, Cheng H, et al. Comparison of quantitative immunofluorescence with conventional methods for HER2/neu testing with respect to response to trastuzumab therapy in metastatic breast cancer. Arch Pathol Lab Med (2008) 132(10):1635–1647.[Web of Science][Medline]
19. Wolff AC, Hammond ME, Schwartz JN, et al. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol (2007) 25(1):118–145.
20. Chambers AF, Naumov GN, Vantyghem SA, Tuck AB. Molecular biology of breast cancer metastasis. Clinical implications of experimental studies on metastatic inefficiency. Breast Cancer Res (2000) 2(6):400–407.[CrossRef][Web of Science][Medline]
21. Huang TH, Wu F, Loeb GB, et al. Upregulation of miR-21 by HER2/neu signaling promotes cell invasion. J Biol Chem (2009) 284(27):18515–18524.
22. Maynadier M, Nirde P, Ramirez JM, et al. Role of estrogens and their receptors in adhesion and invasiveness of breast cancer cells. Adv Exp Med Biol (2008) 617:485–491.[CrossRef][Web of Science][Medline]
23. Mannino M, Yarnold JR. Local relapse rates are falling after breast conserving surgery and systemic therapy for early breast cancer: can radiotherapy ever be safely withheld? Radiother Oncol (2009) 90(1):14–22.[CrossRef][Web of Science][Medline]
24. Harvey JM, Clark GM, Osborne CK, Allred DC. Estrogen receptor status by immunohistochemistry is superior to the ligand-binding assay for predicting response to adjuvant endocrine therapy in breast cancer. J Clin Oncol (1999) 17(5):1474–1481.
25. Psyrri A, Yu Z, Weinberger PM, et al. Quantitative determination of nuclear and cytoplasmic epidermal growth factor receptor expression in oropharyngeal squamous cell cancer by using automated quantitative analysis. Clin Cancer Res (2005) 11(16):5856–5862.
26. Zafirellis K, Agrogiannis G, Zachaki A, et al. Prognostic significance of VEGF expression evaluated by quantitative immunohistochemical analysis in colorectal cancer. J Surg Res (2008) 147(1):99–107.[CrossRef][Web of Science][Medline]
27. Iguchi C, Nio Y, Itakura M. Heterogeneic expression of estrogen receptor between the primary tumor and the corresponding involved lymph nodes in patients with node-positive breast cancer and its implications in patient outcome. J Surg Oncol (2003) 83(2):85–93.[CrossRef][Web of Science][Medline]
28. Xu R, Perle MA, Inghirami G, et al. Amplification of Her-2/neu gene in Her-2/neu-overexpressing and -nonexpressing breast carcinomas and their synchronous benign, premalignant, and metastatic lesions detected by FISH in archival material. Mod Pathol (2002) 15(2):116–124.[CrossRef][Web of Science][Medline]
29. Coradini D, Cappelletti V, Miodini P, et al. Distribution of estrogen and progesterone receptors in primary tumor and lymph nodes in individual patients with breast cancer. Tumori (1984) 70(2):165–168.[Web of Science][Medline]
30. Dikicioglu E, Barutca S, Meydan N, Meteoglu I. Biological characteristics of breast cancer at the primary tumour and the involved lymph nodes. Int J Clin Pract (2005) 59(9):1039–1044.[CrossRef][Web of Science][Medline]
31. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature (2000) 406(6797):747–752.[CrossRef][Medline]
32. D'Andrea MR, Limiti MR, Bari M, et al. Correlation between genetic and biological aspects in primary non-metastatic breast cancers and corresponding synchronous axillary lymph node metastasis. Breast Cancer Res Treat (2007) 101(3):279–284.[CrossRef][Web of Science][Medline]
33. Simon R, Nocito A, Hubscher T, et al. Patterns of HER-2/neu amplification and overexpression in primary and metastatic breast cancer. J Natl Cancer Inst (2001) 93(15):1141–1146.
34. Gomez-Fernandez C, Daneshbod Y, Nassiri M, et al. Immunohistochemically determined estrogen receptor phenotype remains stable in recurrent and metastatic breast cancer. Am J Clin Pathol (2008) 130(6):879–882.
35. Tsutsui S, Ohno S, Murakami S, et al. EGFR, c-erbB2 and p53 protein in the primary lesions and paired metastatic regional lymph nodes in breast cancer. Eur J Surg Oncol (2002) 28(4):383–387.[CrossRef][Web of Science][Medline]
36. Carlsson J, Nordgren H, Sjostrom J, et al. HER2 expression in breast cancer primary tumours and corresponding metastases. Original data and literature review. Br J Cancer (2004) 90(12):2344–2348.[Web of Science][Medline]
37. Masood S, Bui MM. Assessment of Her-2/neu overexpression in primary breast cancers and their metastatic lesions: an immunohistochemical study. Ann Clin Lab Sci (2000) 30(3):259–265.[Abstract]
38. Tanner M, Jarvinen P, Isola J. Amplification of HER-2/neu and topoisomerase IIalpha in primary and metastatic breast cancer. Cancer Res (2001) 61(14):5345–5348.
39. Gancberg D, Di Leo A, Cardoso F, et al. Comparison of HER-2 status between primary breast cancer and corresponding distant metastatic sites. Ann Oncol (2002) 13(7):1036–1043.
40. Simmons C, Miller N, Geddie W, et al. Does confirmatory tumor biopsy alter the management of breast cancer patients with distant metastases? Ann Oncol (2009).
41. van Agthoven T, Timmermans M, Dorssers LC, Henzen-Logmans SC. Expression of estrogen, progesterone and epidermal growth factor receptors in primary and metastatic breast cancer. Int J Cancer (1995) 63(6):790–793.[Web of Science][Medline]
42. Niehans GA, Singleton TP, Dykoski D, Kiang DT. Stability of HER-2/neu expression over time and at multiple metastatic sites. J Natl Cancer Inst (1993) 85(15):1230–1235.
43. Mori T, Morimoto T, Komaki K, Monden Y. Comparison of estrogen receptor and epidermal growth factor receptor content of primary and involved nodes in human breast cancer. Cancer (1991) 68(3):532–537.[CrossRef][Web of Science][Medline]
44. Brunn RB, Kamby C. Immunohistochemical detection of estrogen receptors in paraffin sections from primary and metastatic breast cancer. Pathol Res Pract (1989) 185(6):856–859.[Web of Science][Medline]
45. Kamby C, Rasmussen BB, Kristensen B. Oestrogen receptor status of primary breast carcinomas and their metastases. Relation to pattern of spread and survival after recurrence. Br J Cancer (1989) 60(2):252–257.[Web of Science][Medline]
46. Hahnel R, Twaddle E. The relationship between estrogen receptors in primary and secondary breast carcinomas and in sequential primary breast carcinomas. Breast Cancer Res Treat (1985) 5(2):155–163.[CrossRef][Web of Science][Medline]
47. Kyndi M, Sorensen FB, Knudsen H, et al. Tissue microarrays compared with whole sections and biochemical analyses. A subgroup analysis of DBCG 82 b&c. Acta Oncol (2008) 47(4):591–599.[CrossRef][Web of Science][Medline]
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