Abstract
Gene-expression profiling has had a considerable impact on our understanding of breast cancer biology, and more recently on clinical care. Two statistical approaches underlie these advancements. Supervised analyses have led to the development of gene-expression signatures designed to predict survival and/or treatment response, which has resulted in the development of new clinical assays. Unsupervised analyses have identified numerous biological signatures including signatures of cell type of origin, signaling pathways, and of cellular proliferation. Included within these biological signatures are the molecular subtypes known as the 'intrinsic' subtypes of breast cancer. This classification has expanded our appreciation of the heterogeneity of breast cancer and has provided a way to sub-classify the disease in a manner that might have clinical utility. In this Review, we discuss the clinical utility of gene-expression-based assays and their technical potential as clinical tools vis-a-vis the performance of breast cancer biomarkers that are the current standard of care.
Key Points
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Gene-expression-based assays provide independent prognostic information beyond standard clinical-pathological variables; however, tumor and nodal stage remain important and must be taken into account in the final prognostic assessment
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Gene-expression-based assays identify patients with ER-positive node-negative disease at low risk of relapse after treatment with hormonal therapy and who might be spared from chemotherapy
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Clinical use of gene-expression-based assays for the prediction of chemotherapy benefit in node-positive disease, and in ER-negative disease, is currently experimental
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Current methodologies for ER, PR and HER2 testing might benefit from additional protocol standardizations, but may still be less reproducible than standardized gene-expression-based assays
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Non-standardized research-based identification of the intrinsic subtypes shows concordance values equivalent to current clinical testing for histological grade, ER, PR and HER2
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For daily clinical use, we recommend the highest level of reproducibility/concordance (Level 1), which will only be achieved for pathology and gene-expression-based tests by using a single platform and standardized protocol
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References
Jemal, A., Siegel, R., Xu, J. & Ward, E. Cancer Statistics, 2010. CA Cancer J. Clin. 60, 277–300 (2010).
NCCM Clinical Practicce Guidelines in Oncology™. Breast Cancer [online], (2011).
Harris, L. et al. American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J. Clin. Oncol. 25, 5287–5312 (2007).
Goldhirsch, A. et al. Strategies for subtypes—dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann. Oncol. 22, 1736–1747 (2011).
Wirapati, P. et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 10, R65 (2008).
Fan, C. et al. Concordance among gene-expression-based predictors for breast cancer. N. Engl. J. Med. 355, 560–569 (2006).
Prat, A. et al. Concordance among gene-expression-based predictors for ER-positive breast cancer treated with adjuvant tamoxifen [abstract]. J. Clin. Oncol. 29 (Suppl.), a502 (2011).
Kim, C. & Paik, S. Gene-expression-based prognostic assays for breast cancer. Nat. Rev. Clin. Oncol. 7, 340–347 (2010).
Sparano, J. A. & Paik, S. Development of the 21-gene assay and its application in clinical practice and clinical trials. J. Clin. Oncol. 26, 721–728 (2008).
Fisher, B. et al. Tamoxifen and chemotherapy for lymph node-negative, estrogen receptor-positive breast cancer. J. Natl Cancer Inst. 89, 1673–1682 (1997).
Paik, S. et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N. Engl. J. Med. 351, 2817–2826 (2004).
Habel, L. A. et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res. 8, R25 (2006).
van't Veer, L. J. et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 415, 530–536 (2002).
Buyse, M. et al. Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J. Natl Cancer Inst. 98, 1183–1192 (2006).
van de Vijver, M. J. et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009 (2002).
Cardoso, F. et al. Clinical application of the 70-gene profile: the MINDACT trial. J. Clin. Oncol. 26, 729–735 (2008).
Sotiriou, C. et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J. Natl Cancer Inst. 98, 262–272 (2006).
Loi, S. et al. Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade. J. Clin. Oncol. 25, 1239–1246 (2007).
Ma, X. J. et al. A five-gene molecular grade index and HOXB13:IL17BR are complementary prognostic factors in early stage breast cancer. Clin. Cancer Res. 14, 2601–2608 (2008).
Jerevall, P. L. et al. Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br. J. Cancer 104, 1762–1769 (2011).
Ma, X. J. et al. A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell 5, 607–616 (2004).
Perou, C. M. et al. Molecular portraits of human breast tumours. Nature 406, 747–752 (2000).
Sorlie, T. et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl Acad. Sci. USA 100, 8418–8423 (2003).
Sørlie, T. et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl Acad. Sci. USA 98, 10869–10874 (2001).
Perou, C. M. et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc. Natl Acad. Sci. USA 96, 9212–9217 (1999).
Millikan, R. C. et al. Epidemiology of basal-like breast cancer. Breast Cancer Res. Treat. 109, 123–139 (2008).
Fan, C. et al. Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures. BMC Med. Genomics 4, 3 (2011).
Parker, J. S. et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 27, 1160–1167 (2009).
Martin, M. et al. Genomic predictors of response to doxorubicin versus docetaxel in primary breast cancer. Breast Cancer Res. Treat. 128, 127–136 (2011).
Glück, S. et al. TP53 genomics predict higher clinical and pathologic tumor response in operable early-stage breast cancer treated with docetaxel-capecitabine ± trastuzumab. Breast Cancer Res. Treat. doi:10.1007/s10549-011-1412-7.
Carey, L. A. et al. The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin. Cancer Res. 13, 2329–2334 (2007).
Rouzier, R. et al. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin. Cancer Res. 11, 5678–5678 (2005).
Nielsen, T. O. et al. A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor positive breast cancer. Clin. Cancer Res. 16, 5222–5232 (2010).
Geiss, G. K. et al. Direct multiplexed measurement of gene expression with color-coded probe pairs. Nat. Biotechnol. 26, 317–325 (2008).
Prat, A. & Perou, C. M. Deconstructing the molecular portraits of breast cancer. Mol. Oncol. 5, 5–23 (2011).
Cheang, M. C. et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J. Natl Cancer Inst. 101, 736–750 (2009).
Nielsen, T. O. et al. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin. Cancer Res. 10, 5367–3574 (2004).
Cheang, M. C. et al. Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype. Clin. Cancer Res. 14, 1368–1368 (2008).
Alexe, G. et al. High expression of lymphocyte-associated genes in node-negative HER2+ breast cancers correlates with lower recurrence rates. Cancer Res. 67, 10669–10669 (2007).
Teschendorff, A. E. et al.: An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol. 8, R157 (2007).
Lo, S. S. et al. Prospective multicenter study of the impact of the 21-gene recurrence score assay on medical oncologist and patient adjuvant breast cancer treatment selection. J. Clin. Oncol. 28, 1671–1676 (2010).
Geffen, D. B. et al. The impact of the 21-gene recurrence score assay on decision making about adjuvant chemotherapy in early-stage estrogen-receptor-positive breast cancer in an oncology practice with a unified treatment policy. Ann. Oncol. 22, 2381–2386 (2011).
Tsoi, D. T., Inoue, M., Kelly, C. M., Verma, S. & Pritchard, K. I. Cost-effectiveness analysis of recurrence score-guided treatment using a 21-gene assay in early breast cancer. Oncologist 15, 457–465 (2010).
Hornberger, J., Cosler, L. & Lyman, G. Economic analysis of targeting chemotherapy using a 21-gene RT-PCR assay in lymph-node-negative, estrogen-receptor-positive, early-stage breast cancer. Am. J. Manag. Care 11, 313–324 (2005).
Albain, K. S. et al. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial. Lancet Oncol. 11, 55–65 (2010).
Dowsett, M. et al. Prediction of risk of distant recurrence using the 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study. J. Clin. Oncol. 28, 1829–1834 (2010).
Mook, S. et al. The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1–3 positive lymph nodes in an independent validation study. Breast Cancer Res. Treat. 116, 295–302 (2009).
Parker, J. et al. Breast cancer molecular subtypes predict response to anthracycline/taxane-based chemotherapy [abstract]. Cancer Res. 69 (Suppl. 3), a2019 (2009).
Liedtke, C. et al. Genomic grade index is associated with response to chemotherapy in patients with breast cancer. J. Clin. Oncol. 27, 3185–3191 (2009).
Straver, M. E. et al. The 70-gene signature as a response predictor for neoadjuvant chemotherapy in breast cancer. Breast Cancer Res. Treat. 119, 551–558 (2010).
Gianni, L. et al. Gene expression profiles in paraffin-embedded core biopsy tissue predict response to chemotherapy in women with locally advanced breast cancer. J. Clin. Oncol. 23, 7265–7277 (2005).
Ellis, M. J. et al. Outcome prediction for estrogen receptor-positive breast cancer based on postneoadjuvant endocrine therapy tumor characteristics. J. Natl Cancer Inst. 100, 1380–1388 (2008).
Ellis, M. J. et al. Letrozole is more effective neoadjuvant endocrine therapy than tamoxifen for ErbB-1- and/or ErbB-2-positive, estrogen receptor-positive primary breast cancer: evidence from a phase III randomized trial. J. Clin. Oncol. 19, 3808–3816 (2001).
Ellis, M. J. et al. Randomized phase II neoadjuvant comparison between letrozole, anastrozole, and exemestane for postmenopausal women with estrogen receptor-rich stage 2 to 3 breast cancer: clinical and biomarker outcomes and predictive value of the baseline PAM50-based intrinsic subtype--ACOSOG Z1031. J. Clin. Oncol. 29, 2342–2349 (2011).
Paik, S. et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J. Clin. Oncol. 24, 3726–3734 (2006).
Cronin, M. et al. Analytical validation of the Oncotype DX genomic diagnostic test for recurrence prognosis and therapeutic response prediction in node-negative, estrogen receptor-positive breast cancer. Clin. Chem. 53, 1084–1091 (2007).
Glas, A. M. et al. Converting a microarray breast cancer signature into a high throughput diagnostic test. BMC Genomics 7, 278 (2006).
Wolff, A. C. 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. 25, 118–145 (2007).
Hammond, M. E., Hayes, D. F., Wolff, A. C., Mangu, P. B. & Temin, S. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J. Clin. Oncol. 28, 2784–2795 (2010).
Cohen, J. A coefficient of agreement for nominal scales. Educ. Psychol. Meas. 20, 37–46 (1960).
Randolph, J. Free-marginal multirater kappa: an alternative to Fleiss' fixed-marginal multirater kappa. Joensuu University Learning and Instruction Symp. October 14–15 (2005).
Mackay, A. et al. Microarray-based class discovery for molecular classification of breast cancer: analysis of interobserver agreement. J. Natl Cancer Inst. 103, 662–673 (2011).
Weigelt, B. et al. Breast cancer molecular profiling with single sample predictors: a retrospective analysis. Lancet Oncol. 11, 339–349 (2010).
Turbin, D. A. et al. Automated quantitative analysis of estrogen receptor expression in breast carcinoma does not differ from expert pathologist scoring: a tissue microarray study of 3,484 cases. Breast Cancer Res. Treat. 110, 417–426 (2008).
Bueno-de-Mesquita, J. M. et al. The impact of inter-observer variation in pathological assessment of node-negative breast cancer on clinical risk assessment and patient selection for adjuvant systemic treatment. Ann. Oncol. 21, 40–47 (2010).
Mudduwa, L. & Liyanage, T. Immunohistochemical assessment of hormone receptor status of breast carcinoma: interobserver variation of the quick score. Indian J. Med. Sci. 63, 21–27 (2009).
Wells, C. A. et al. Consistency of staining and reporting of oestrogen receptor immunocytochemistry within the European Union—an inter-laboratory study. Virchows Arch. 445, 119–128 (2004).
Badve, S. S. et al. Estrogen- and progesterone-receptor status in ECOG 2197: comparison of immunohistochemistry by local and central laboratories and quantitative reverse transcription polymerase chain reaction by central laboratory. J. Clin. Oncol. 26, 2473–2481 (2008).
Collins, L. C., Marotti, J. D., Baer, H. J. & Tamimi, R. M. Comparison of estrogen receptor results from pathology reports with results from central laboratory testing. J. Natl Cancer Inst. 100, 218–221 (2008).
Parker, R. L. et al. Assessment of interlaboratory variation in the immunohistochemical determination of estrogen receptor status using a breast cancer tissue microarray. Am. J. Clin. Pathol. 117, 723–728 (2002).
Rydén, L. et al. Reproducibility of human epidermal growth factor receptor 2 analysis in primary breast cancer: a national survey performed at pathology departments in Sweden. Acta Oncol. 48, 860–866 (2009).
Press, M. F. et al. Diagnostic evaluation of HER-2 as a molecular target: an assessment of accuracy and reproducibility of laboratory testing in large, prospective, randomized clinical trials. Clin. Cancer Res. 11, 6598–6607 (2005).
Umemura, S. et al. What causes discrepancies in HER2 testing for breast cancer? Am. J. Clin. Pathol. 130, 883–891 (2008).
Diaz, L. K., Gupta, R., Kidwai, N., Sneige, N. & Wiley, E. L. The use of TMA for interlaboratory validation of FISH testing for detection of HER2 gene amplification in breast cancer. J. Histochem. Cytochem. 52, 501–507 (2004).
Di Palma, S. et al. A quality assurance exercise to evaluate the accuracy and reproducibility of chromogenic in situ hybridisation for HER2 analysis in breast cancer. J. Clin. Pathol. 61, 757–760 (2008).
Bartlett, J. M. et al. Evaluating HER2 amplification and overexpression in breast cancer. J. Pathol. 195, 422–428 (2001).
Turashvili, G. et al. Inter-observer reproducibility of HER2 immunohistochemical assessment and concordance with fluorescent in situ hybridization (FISH): pathologist assessment compared to quantitative image analysis. BMC Cancer 9, 165 (2009).
van der Vegt, B., de Bock, G. H., Bart, J., Zwartjes, N. G. & Wesseling, J. Validation of the 4B5 rabbit monoclonal antibody in determining Her2/neu status in breast cancer. Mod. Pathol. 22, 879–886 (2009).
Tsuda, H. et al. HER2 testing on core needle biopsy specimens from primary breast cancers: interobserver reproducibility and concordance with surgically resected specimens. BMC Cancer 10, 534 (2010).
Arena, V., Pennacchia, I., Monego, G., Carbone, A. & Capelli, A. Fluorescent in situ hybridization as a primary test for HER2 status in breast cancer: controversies. J. Clin. Oncol. 28, e83–e84 (2009).
Sauter, G., Lee, J., Bartlett, J. M., Slamon, D. J. & Presse, M. J. Guidelines for human epidermal growth factor receptor 2 testing: biologic and methodologic considerations. J. Clin. Oncol. 27, 1323–1333 (2009).
Perez, E. A. et al. HER2 testing by local, central, and reference laboratories in specimens from the North Central Cancer Treatment Group N9831 intergroup adjuvant trial. J. Clin. Oncol. 24, 3032–3038 (2006).
Paik, S. et al. Real-world performance of HER2 testing--National Surgical Adjuvant Breast and Bowel Project experience. J. Natl Cancer Inst. 94, 852–854 (2002).
Regan, M. M. et al. Re-evaluating adjuvant breast cancer trials: assessing hormone receptor status by immunohistochemical versus extraction assays. J. Natl Cancer Inst. 98, 1571–1581 (2006).
Cheang, M. C. et al. Immunohistochemical detection using the new rabbit monoclonal antibody SP1 of estrogen receptor in breast cancer is superior to mouse monoclonal antibody 1D5 in predicting survival. J. Clin. Oncol. 24, 5637–5644 (2006).
Harvey, J. M., Clark, G. M., Osborne, C. K. & Allred, D. C. 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. 17, 1474–1481 (1999).
Nassar, A., Cohen, C. & Siddiqui, M. Estimation of hormone receptor status and HER2 in cytologic cell blocks from breast cancer using the novel rabbit monoclonal antibodies (SP1, SP2, and SP3). Diagn. Cytopathol. 37, 865–870 (2009).
Rhodes, A., Jasani, B., Barnes, D. M., Bobrow, L. G. & Miller, K. D. Reliability of immunohistochemical demonstration of oestrogen receptors in routine practice: interlaboratory variance in the sensitivity of detection and evaluation of scoring systems. J. Clin. Pathol. 53, 125–130 (2000).
Viale, G. et al. Prognostic and predictive value of centrally reviewed expression of estrogen and progesterone receptors in a randomized trial comparing letrozole and tamoxifen adjuvant therapy for postmenopausal early breast cancer: BIG 1–98. J. Clin. Oncol. 25, 3846–3852 (2007).
Regitnig, P. et al. Quality assurance for detection of estrogen and progesterone receptors by immunohistochemistry in Austrian pathology laboratories. Virchows Arch. 441, 328–334 (2002).
Anderson, T. J., Alexander, F. E., Lamb, J., Smith, A. & Forrest, A. P. Pathology characteristics that optimize outcome prediction of a breast screening trial. Br. J. Cancer 83, 487–492 (2000).
Frierson, H. F. Jr et al. Interobserver reproducibility of the Nottingham modification of the Bloom and Richardson histologic grading scheme for infiltrating ductal carcinoma. Am. J. Clin. Pathol. 103, 195–198 (1995).
Ellis, I. O. et al. Impact of a national external quality assessment scheme for breast pathology in the UK. J. Clin. Pathol. 59, 138–145 (2006).
Longacre, T. A. et al. Interobserver agreement and reproducibility in classification of invasive breast carcinoma: an NCI breast cancer family registry study. Mod. Pathol. 19, 195–207 (2005).
Boiesen, P. et al. Histologic grading in breast cancer--reproducibility between seven pathologic departments. South Sweden Breast Cancer Group. Acta Oncol. 39, 41–45 (2000).
Sloane, J. P. et al. Consistency achieved by 23 European pathologists from 12 countries in diagnosing breast disease and reporting prognostic features of carcinomas. Virchows Arch. 434, 3–10 (1999).
Adams, A. L., Chhieng, D. C., Bell, W. C., Winokur, T. & Hameed, O. Histologic grading of invasive lobular carcinoma: does use of a 2-tiered nuclear grading system improve interobserver variability? Ann. Diagn. Pathol. 13, 223–225 (2009).
Tsuda, H. et al. Evaluation of the interobserver agreement in the number of mitotic figures of breast carcinoma as simulation of quality monitoring in the Japan National Surgical Adjuvant Study of Breast Cancer (NSAS-BC) protocol. Jpn J. Cancer Res. 91, 451–457 (2000).
Reed, W. et al. The prognostic value of p53 and c-erb B-2 immunostaining is overrated for patients with lymph node negative breast carcinoma. Cancer 88, 804–813 (2000).
Rakha, E. et al. Breast cancer prognostic classification in the molecular era: the role of histological grade. Breast Cancer Res. 12, 207 (2010).
Dybdal, N. et al. Determination of HER2 gene amplification by fluorescence in situ hybridization and concordance with the clinical trials immunohistochemical assay in women with metastatic breast cancer evaluated for treatment with trastuzumab. Breast Cancer Res. Treat. 93, 3–11 (2005).
Press, M. F. et al. HER-2 gene amplification, HER-2 and epidermal growth factor receptor mRNA and protein expression, and lapatinib efficacy in women with metastatic breast cancer. Clin. Cancer Res. 14, 7861–7870 (2008).
Dressler, L. G. et al. Comparison of HER2 status by fluorescence in situ hybridization and immunohistochemistry to predict benefit from dose escalation of adjuvant doxorubicin-based therapy in node-positive breast cancer patients. J. Clin. Oncol. 23, 4287–4297 (2005).
Powell, W. C. et al. A new rabbit monoclonal antibody (4B5) for the immunohistochemical (IHC) determination of the HER2 status in breast cancer: comparison with CB11, fluorescence in situ hybridization (FISH), and interlaboratory reproducibility. Appl. Immunohistochem. Mol. Morphol. 15, 94–102 (2007).
Noske, A. et al. Comparison of different approaches for assessment of HER2 expression on protein and mRNA level: prediction of chemotherapy response in the neoadjuvant GeparTrio trial (NCT00544765). Breast Cancer Res. Treat. 126, 109–117 (2011).
Baehner, F. L. et al. Human epidermal growth factor receptor 2 assessment in a case-control study: comparison of fluorescence in situ hybridization and quantitative reverse transcription polymerase chain reaction performed by central laboratories. J. Clin. Oncol. 28, 4300–4306 (2010).
Perou, C. M., Parker, J. S., Prat, A., Ellis, M. J. & Bernard, P. S. Clinical implementation of the intrinsic subtypes of breast cancer. Lancet Oncol. 11, 718–719 (2010).
Sørlie, T. et al. The importance of gene-centring microarray data. Lancet Oncol. 11, 719–720 (2010).
Dunning, M. J. et al. The importance of platform annotation in interpreting microarray data. Lancet Oncol. 11, 717–717 (2010).
Pillai, R. et al. Validation and reproducibility of a microarray-based gene expression test for tumor identification in formalin-fixed, paraffin-embedded specimens. J. Mol. Diagn. 13, 48–56 (2011).
Hu, Z. et al. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics 7, 96 (2006).
Harrell, J. C. et al. Genomic analysis identifies unique signatures predictive of brain, lung, and liver relapse. Breast Cancer Res. Treat. doi:10.1007/s10549-011-1619-7.
Ding, L. et al. Genome remodelling in a basal-like breast cancer metastasis and xenograft. Nature 464, 999–1005 (2010).
Shah, S. P. et al. Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature 461, 809–813 (2009).
Nunes, C. B. et al. Comparative analysis of six different antibodies against Her2 including the novel rabbit monoclonal antibody (SP3) and chromogenic in situ hybridisation in breast carcinomas. J. Clin. Pathol. 61, 934–938 (2008).
Moelans, C. B. et al. Validation of a fully automated HER2 staining kit in breast cancer. Cell Oncol. 32, 149–155 (2010).
Tubbs, R. R. et al. Discrepancies in clinical laboratory testing of eligibility for trastuzumab therapy: apparent immunohistochemical false-positives do not get the message. J. Clin. Oncol. 19, 2714–2721 (2001).
Arihiro, K. et al. Comparison of evaluations for hormone receptors in breast carcinoma using two manual and three automated immunohistochemical assays. Am. J. Clin. Pathol. 127, 356–365 (2007).
Acknowledgements
We thank Cynthia Ma for reviewing this manuscript. This work was supported by funds from the NCI Breast SPORE program (P50-CA58223-09A1), by RO1-CA138255, by the Breast Cancer Research Foundation and the V Foundation for Cancer Research. A. Prat is affiliated to the Medicine PhD program of the Autonomous University of Barcelona (UAB), Spain.
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M. J. Ellis and C. M. Perou are stockholders of BioClassifier LLC. which has licensed the PAM50 assay. CMP and MJE are inventors on a pending patent application for the PAM50 assay. A. Prat declares no competing interests.
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Prat, A., Ellis, M. & Perou, C. Practical implications of gene-expression-based assays for breast oncologists. Nat Rev Clin Oncol 9, 48–57 (2012). https://doi.org/10.1038/nrclinonc.2011.178
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DOI: https://doi.org/10.1038/nrclinonc.2011.178
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