From High-Throughput Microarray-Based Screening to Clinical Application: The Development of a Second Generation Multigene Test for Breast Cancer Prognosis
Several multigene tests have been developed for breast cancer patients to predict the individual risk of recurrence. Most of the first generation tests rely on proliferation-associated genes and are commonly carried out in central reference laboratories. Here, we describe the development of a second generation multigene assay, the EndoPredict test, a prognostic multigene expression test for estrogen receptor (ER) positive, human epidermal growth factor receptor (HER2) negative (ER+/HER2？) breast cancer patients. The EndoPredict gene signature was initially established in a large high-throughput microarray-based screening study. The key steps for biomarker identification are discussed in detail, in comparison to the establishment of other multigene signatures. After biomarker selection, genes and algorithms were transferred to a diagnostic platform (reverse transcription quantitative PCR (RT-qPCR)) to allow for assaying formalin-fixed, paraffin-embedded (FFPE) samples. A comprehensive analytical validation was performed and a prospective proficiency testing study with seven pathological laboratories finally proved that EndoPredict can be reliably used in the decentralized setting. Three independent large clinical validation studies (n = 2,257) demonstrated that EndoPredict offers independent prognostic information beyond current clinicopathological parameters and clinical guidelines. The review article summarizes several important steps that should be considered for the development process of a second generation multigene test and offers a means for transferring a microarray signature from the research laboratory to clinical practice.
References
[1]
Siegel, R.; Naishadham, D.; Jemal, A. Cancer statistics, 2013. CA. Cancer J. Clin. 2013, 63, 11–30, doi:10.3322/caac.21166.
[2]
Olivotto, I.A.; Bajdik, C.D.; Ravdin, P.M.; Speers, C.H.; Coldman, A.J.; Norris, B.D.; Davis, G.J.; Chia, S.K.; Gelmon, K.A. Population-based validation of the prognostic model ADJUVANT! for early breast cancer. J. Clin. Oncol. 2005, 23, 2716–2725.
[3]
Galea, M.H.; Blamey, R.W.; Elston, C.E.; Ellis, I.O. The Nottingham Prognostic Index in primary breast cancer. Breast Cancer Res. Treat. 1992, 22, 207–219, doi:10.1007/BF01840834.
[4]
D’Eredita, G.; Giardina, C.; Martellotta, M.; Natale, T.; Ferrarese, F. Prognostic factors in breast cancer: The predictive value of the Nottingham Prognostic Index in patients with a long-term follow-up that were treated in a single institution. Eur. J. Cancer 2001, 37, 591–596, doi:10.1016/S0959-8049(00)00435-4.
[5]
Goldhirsch, A.; Ingle, J.N.; Gelber, R.D.; Coates, A.S.; Thurlimann, B.; Senn, H.J. Thresholds for therapies: Highlights of the St. Gallen International Expert Consensus on the primary therapy of early breast cancer 2009. Ann. Oncol. 2009, 20, 1319–1329, doi:10.1093/annonc/mdp322.
[6]
Perou, C.M.; Sorlie, T.; Eisen, M.B.; van de Rijn, M.; Jeffrey, S.S.; Rees, C.A.; Pollack, J.R.; Ross, D.T.; Johnsen, H.; Akslen, L.A.; et al. Molecular portraits of human breast tumours. Nature 2000, 406, 747–752, doi:10.1038/35021093.
[7]
Sorlie, T.; Perou, C.M.; Tibshirani, R.; Aas, T.; Geisler, S.; Johnsen, H.; Hastie, T.; Eisen, M.B.; van de Rijn, M.; Jeffrey, S.S.; et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. USA 2001, 98, 10869–10874, doi:10.1073/pnas.191367098.
[8]
Sorlie, T.; Tibshirani, R.; Parker, J.; Hastie, T.; Marron, J.S.; Nobel, A.; Deng, S.; Johnsen, H.; Pesich, R.; Geisler, S.; et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl. Acad. Sci. USA 2003, 100, 8418–8423, doi:10.1073/pnas.0932692100.
[9]
Rouzier, R.; Perou, C.M.; Symmans, W.F.; Ibrahim, N.; Cristofanilli, M.; Anderson, K.; Hess, K.R.; Stec, J.; Ayers, M.; Wagner, P.; et al. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin. Cancer Res. 2005, 11, 5678–5685, doi:10.1158/1078-0432.CCR-04-2421.
[10]
Gluck, S.; de Snoo, F.; Peeters, J.; Stork-Sloots, L.; Somlo, G. Molecular subtyping of early-stage breast cancer identifies a group of patients who do not benefit from neoadjuvant chemotherapy. Breast Cancer Res. Treat. 2013, 139, 759–767, doi:10.1007/s10549-013-2572-4.
[11]
Van’t Veer, L.J.; Dai, H.; van de Vijver, M.J.; He, Y.D.; Hart, A.A.; Mao, M.; Peterse, H.L.; van der Kooy, K.; Marton, M.J.; Witteveen, A.T.; et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002, 415, 530–536, doi:10.1038/415530a.
[12]
Van de Vijver, M.J.; He, Y.D.; van’t Veer, L.J.; Dai, H.; Hart, A.A.; Voskuil, D.W.; Schreiber, G.J.; Peterse, J.L.; Roberts, C.; Marton, M.J.; et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 2002, 347, 1999–2009, doi:10.1056/NEJMoa021967.
[13]
Buyse, M.; Loi, S.; van’t Veer, L.; Viale, G.; Delorenzi, M.; Glas, A.M.; d’Assignies, M.S.; Bergh, J.; Lidereau, R.; Ellis, P.; et al. Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J. Natl. Cancer Inst. 2006, 98, 1183–1192, doi:10.1093/jnci/djj329.
[14]
Mook, S.; Schmidt, M.K.; Weigelt, B.; Kreike, B.; Eekhout, I.; van de Vijver, M.J.; Glas, A.M.; Floore, A.; Rutgers, E.J.; van’t Veer, L.J. The 70-gene prognosis signature predicts early metastasis in breast cancer patients between 55 and 70 years of age. Ann. Oncol. 2010, 21, 717–722, doi:10.1093/annonc/mdp388.
[15]
Wittner, B.S.; Sgroi, D.C.; Ryan, P.D.; Bruinsma, T.J.; Glas, A.M.; Male, A.; Dahiya, S.; Habin, K.; Bernards, R.; Haber, D.A.; et al. Analysis of the MammaPrint breast cancer assay in a predominantly postmenopausal cohort. Clin. Cancer Res. 2008, 14, 2988–2993, doi:10.1158/1078-0432.CCR-07-4723.
[16]
Glas, A.M.; Floore, A.; Delahaye, L.J.; Witteveen, A.T.; Pover, R.C.; Bakx, N.; Lahti-Domenici, J.S.; Bruinsma, T.J.; Warmoes, M.O.; Bernards, R.; et al. Converting a breast cancer microarray signature into a high-throughput diagnostic test. BMC Genomics 2006, 7, 278, doi:10.1186/1471-2164-7-278.
[17]
Paik, S.; Shak, S.; Tang, G.; Kim, C.; Baker, J.; Cronin, M.; Baehner, F.L.; Walker, M.G.; Watson, D.; Park, T.; et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N. Engl. J. Med. 2004, 351, 2817–2826, doi:10.1056/NEJMoa041588.
[18]
Paik, S.; Tang, G.; Shak, S.; Kim, C.; Baker, J.; Kim, W.; Cronin, M.; Baehner, F.L.; Watson, D.; Bryant, J.; et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J. Clin. Oncol. 2006, 24, 3726–3734, doi:10.1200/JCO.2005.04.7985.
[19]
Albain, K.S.; Barlow, W.E.; Shak, S.; Hortobagyi, G.N.; Livingston, R.B.; Yeh, I.T.; Ravdin, P.; Bugarini, R.; Baehner, F.L.; Davidson, N.E.; 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. 2010, 11, 55–65, doi:10.1016/S1470-2045(09)70314-6.
[20]
Dowsett, M.; Cuzick, J.; Wale, C.; Forbes, J.; Mallon, E.A.; Salter, J.; Quinn, E.; Dunbier, A.; Baum, M.; Buzdar, A.; 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. 2010, 28, 1829–1834, doi:10.1200/JCO.2009.24.4798.
[21]
Cuzick, J.; Dowsett, M.; Pineda, S.; Wale, C.; Salter, J.; Quinn, E.; Zabaglo, L.; Mallon, E.; Green, A.R.; Ellis, I.O.; et al. Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and comparison with the Genomic Health recurrence score in early breast cancer. J. Clin. Oncol. 2011, 29, 4273–4278, doi:10.1200/JCO.2010.31.2835.
[22]
Klang, S.H.; Hammerman, A.; Liebermann, N.; Efrat, N.; Doberne, J.; Hornberger, J. Economic implications of 21-gene breast cancer risk assay from the perspective of an Israeli-managed health-care organization. Value Health 2010, 13, 381–387, doi:10.1111/j.1524-4733.2010.00724.x.
[23]
Partin, J.F.; Mamounas, E.P. Impact of the 21-gene recurrence score assay compared with standard clinicopathologic guidelines in adjuvant therapy selection for node-negative, estrogen receptor-positive breast cancer. Ann. Surg. Oncol. 2011, 18, 3399–3406, doi:10.1245/s10434-011-1698-z.
[24]
Bueno-de-Mesquita, J.M.; van Harten, W.H.; Retel, V.P.; van’t Veer, L.J.; van Dam, F.S.; Karsenberg, K.; Douma, K.F.; van Tinteren, H.; Peterse, J.L.; Wesseling, J.; et al. Use of 70-gene signature to predict prognosis of patients with node-negative breast cancer: A prospective community-based feasibility study (RASTER). Lancet Oncol. 2007, 8, 1079–1087, doi:10.1016/S1470-2045(07)70346-7.
[25]
Geffen, D.B.; Amir, N.; Sion-Vardy, N.; Ariad, S.; Kachko, L.; Bayme, M.; Delgado, B.; Dyomin, V.; Argov, S.; Koretz, M. Stage I breast cancer in a regional oncology practice in Israel 2002–2006: Clinicopathologic features, risk estimation and planned therapy of 328 consecutive patients. Breast 2009, 18, 316–321, doi:10.1016/j.breast.2009.08.004.
[26]
Asad, J.; Jacobson, A.F.; Estabrook, A.; Smith, S.R.; Boolbol, S.K.; Feldman, S.M.; Osborne, M.P.; Boachie-Adjei, K.; Twardzik, W.; Tartter, P.I. Does oncotype DX recurrence score affect the management of patients with early-stage breast cancer? Am. J. Surg. 2008, 196, 527–529, doi:10.1016/j.amjsurg.2008.06.021.
[27]
Drukker, C.A.; Bueno-de-Mesquita, J.M.; Retel, V.P.; van Harten, W.H.; van Tinteren, H.; Wesseling, J.; Roumen, R.M.; Knauer, M.; van’t Veer, L.J.; Sonke, G.S.; et al. A prospective evaluation of a breast cancer prognosis signature in the observational RASTER study. Int. J. Cancer 2013, 133, 929–936, doi:10.1002/ijc.28082.
[28]
Bogaerts, J.; Cardoso, F.; Buyse, M.; Braga, S.; Loi, S.; Harrison, J.A.; Bines, J.; Mook, S.; Decker, N.; Ravdin, P.; et al. Gene signature evaluation as a prognostic tool: Challenges in the design of the MINDACT trial. Nat. Clin. Pract. Oncol. 2006, 3, 540–551.
[29]
Cardoso, F.; van’t Veer, L.; Rutgers, E.; Loi, S.; Mook, S.; Piccart-Gebhart, M.J. Clinical application of the 70-gene profile: the MINDACT trial. J. Clin. Oncol. 2008, 26, 729–735, doi:10.1200/JCO.2007.14.3222.
[30]
Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP working group: Can tumor gene expression profiling improve outcomes in patients with breast cancer? Genet. Med. 2009, 11, 66–73, doi:10.1097/GIM.0b013e3181928f56.
[31]
Fisher, B.; Dignam, J.; Bryant, J.; Wolmark, N. Five versus more than five years of tamoxifen for lymph node-negative breast cancer: Updated findings from the National Surgical Adjuvant Breast and Bowel Project B-14 randomized trial. J. Natl. Cancer Inst. 2001, 93, 684–690, doi:10.1093/jnci/93.9.684.
[32]
Fisher, B.; Jeong, J.H.; Bryant, J.; Anderson, S.; Dignam, J.; Fisher, E.R.; Wolmark, N. Treatment of lymph-node-negative, oestrogen-receptor-positive breast cancer: Long-term findings from National Surgical Adjuvant Breast and Bowel Project randomised clinical trials. Lancet 2004, 364, 858–868, doi:10.1016/S0140-6736(04)16981-X.
[33]
Peto, R.; Davies, C.; Godwin, J.; Gray, R.; Pan, H.C.; Clarke, M.; Cutter, D.; Darby, S.; McGale, P.; Taylor, C.; et al. Comparisons between different polychemotherapy regimens for early breast cancer: Meta-analyses of long-term outcome among 100,000 women in 123 randomised trials. Lancet 2012, 379, 432–444, doi:10.1016/S0140-6736(11)61625-5.
[34]
Berry, D.A.; Cirrincione, C.; Henderson, I.C.; Citron, M.L.; Budman, D.R.; Goldstein, L.J.; Martino, S.; Perez, E.A.; Muss, H.B.; Norton, L.; et al. Estrogen-receptor status and outcomes of modern chemotherapy for patients with node-positive breast cancer. JAMA 2006, 295, 1658–1667, doi:10.1001/jama.295.14.1658.
[35]
Milburn, M.; Rosman, M.; Mylander, C.; Tafra, L. Is oncotype DX recurrence score (RS) of prognostic value once HER2-positive and low-ER expression patients are removed? Breast J. 2013, 19, 357–364, doi:10.1111/tbj.12126.
[36]
Desmedt, C.; Haibe-Kains, B.; Wirapati, P.; Buyse, M.; Larsimont, D.; Bontempi, G.; Delorenzi, M.; Piccart, M.; Sotiriou, C. Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin. Cancer Res. 2008, 14, 5158–5165, doi:10.1158/1078-0432.CCR-07-4756.
[37]
Schmidt, M.; Bohm, D.; von Torne, C.; Steiner, E.; Puhl, A.; Pilch, H.; Lehr, H.A.; Hengstler, J.G.; Kolbl, H.; Gehrmann, M. The humoral immune system has a key prognostic impact in node-negative breast cancer. Cancer Res. 2008, 68, 5405–5413, doi:10.1158/0008-5472.CAN-07-5206.
[38]
Schmidt, M.; Hellwig, B.; Hammad, S.; Othman, A.; Lohr, M.; Chen, Z.; Boehm, D.; Gebhard, S.; Petry, I.; Lebrecht, A.; et al. A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin Do C as a compatible prognostic marker in human solid tumors. Clin. Cancer Res. 2012, 18, 2695–2703, doi:10.1158/1078-0432.CCR-11-2210.
[39]
Schmidt, M.; Hengstler, J.G.; von Torne, C.; Koelbl, H.; Gehrmann, M.C. Coordinates in the universe of node-negative breast cancer revisited. Cancer Res. 2009, 69, 2695–2698, doi:10.1158/0008-5472.CAN-08-4013.
[40]
Teschendorff, A.E.; Gomez, S.; Arenas, A.; El-Ashry, D.; Schmidt, M.; Gehrmann, M.; Caldas, C. Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules. BMC Cancer 2010, 10, 604, doi:10.1186/1471-2407-10-604.
[41]
Bianchini, G.; Qi, Y.; Alvarez, R.H.; Iwamoto, T.; Coutant, C.; Ibrahim, N.K.; Valero, V.; Cristofanilli, M.; Green, M.C.; Radvanyi, L.; et al. Molecular anatomy of breast cancer stroma and its prognostic value in estrogen receptor-positive and -negative cancers. J. Clin. Oncol. 2010, 28, 4316–4323, doi:10.1200/JCO.2009.27.2419.
[42]
Esserman, L.J.; Moore, D.H.; Tsing, P.J.; Chu, P.W.; Yau, C.; Ozanne, E.; Chung, R.E.; Tandon, V.J.; Park, J.W.; Baehner, F.L.; et al. Biologic markers determine both the risk and the timing of recurrence in breast cancer. Breast Cancer Res. Treat. 2011, 129, 607–616, doi:10.1007/s10549-011-1564-5.
[43]
Jatoi, I.; Anderson, W.F.; Jeong, J.H.; Redmond, C.K. Breast cancer adjuvant therapy: Time to consider its time-dependent effects. J. Clin. Oncol. 2011, 29, 2301–2304, doi:10.1200/JCO.2010.32.3550.
[44]
Davies, C.; Pan, H.; Godwin, J.; Gray, R.; Arriagada, R.; Raina, V.; Abraham, M.; Alencar, V.H.; Badran, A.; Bonfill, X.; et al. Long-term effects of continuing adjuvant tamoxifen to 10 years versus stopping at 5 years after diagnosis of oestrogen receptor-positive breast cancer: ATLAS, a randomised trial. Lancet 2013, 381, 805–816, doi:10.1016/S0140-6736(12)61963-1.
[45]
Goss, P.E. Letrozole in the extended adjuvant setting: MA.17. Breast Cancer Res. Treat. 2007, 105 Suppl 1, 45–53, doi:10.1007/s10549-007-9698-1.
[46]
Goss, P.E.; Ingle, J.N.; Martino, S.; Robert, N.J.; Muss, H.B.; Livingston, R.B.; Davidson, N.E.; Perez, E.A.; Chavarri-Guerra, Y.; Cameron, D.A.; et al. Impact of premenopausal status at breast cancer diagnosis in women entered on the placebo-controlled NCIC CTG MA17 trial of extended adjuvant letrozole. Ann. Oncol. 2013, 24, 355–361, doi:10.1093/annonc/mds330.
[47]
Goss, P.E.; Ingle, J.N.; Martino, S.; Robert, N.J.; Muss, H.B.; Piccart, M.J.; Castiglione, M.; Tu, D.; Shepherd, L.E.; Pritchard, K.I.; et al. Randomized trial of letrozole following tamoxifen as extended adjuvant therapy in receptor-positive breast cancer: Updated findings from NCIC CTG MA.17. J. Natl. Cancer Inst. 2005, 97, 1262–1271, doi:10.1093/jnci/dji250.
[48]
Goss, P.E.; Ingle, J.N.; Martino, S.; Robert, N.J.; Muss, H.B.; Piccart, M.J.; Castiglione, M.; Tu, D.; Shepherd, L.E.; Pritchard, K.I.; et al. Efficacy of letrozole extended adjuvant therapy according to estrogen receptor and progesterone receptor status of the primary tumor: National Cancer Institute of Canada Clinical Trials Group MA.17. J. Clin. Oncol. 2007, 25, 2006–2011, doi:10.1200/JCO.2006.09.4482.
[49]
Goss, P.E.; Ingle, J.N.; Martino, S.; Robert, N.J.; Muss, H.B.; Piccart, M.J.; Castiglione, M.; Tu, D.; Shepherd, L.E.; Pritchard, K.I.; et al. A randomized trial of letrozole in postmenopausal women after five years of tamoxifen therapy for early-stage breast cancer. N. Engl. J. Med. 2003, 349, 1793–1802, doi:10.1056/NEJMoa032312.
[50]
Mamounas, E.P.; Jeong, J.H.; Wickerham, D.L.; Smith, R.E.; Ganz, P.A.; Land, S.R.; Eisen, A.; Fehrenbacher, L.; Farrar, W.B.; Atkins, J.N.; et al. Benefit from exemestane as extended adjuvant therapy after 5 years of adjuvant tamoxifen: Intention-to-treat analysis of the National Surgical Adjuvant Breast And Bowel Project B-33 trial. J. Clin. Oncol. 2008, 26, 1965–1971, doi:10.1200/JCO.2007.14.0228.
[51]
Jakesz, R.; Greil, R.; Gnant, M.; Schmid, M.; Kwasny, W.; Kubista, E.; Mlineritsch, B.; Tausch, C.; Stierer, M.; Hofbauer, F.; et al. Extended adjuvant therapy with anastrozole among postmenopausal breast cancer patients: Results from the randomized Austrian Breast and Colorectal Cancer Study Group Trial 6a. J. Natl. Cancer Inst. 2007, 99, 1845–1853, doi:10.1093/jnci/djm246.
[52]
Sgroi, D.C.; Sestak, I.; Cuzick, J.; Zhang, Y.; Schnabel, C.A.; Erlander, M.G.; Goss, P.E.; Dowsett, M. Comparative performance of breast cancer Index (BCI) vs. oncotype Dx and IHC4 in the prediction of late recurrence in hormonal receptor-positive lymph node-negative breast cancer patients: A TransATAC study. Cancer Res. 2012, 72, doi:10.1158/0008-5472.SABCS12-S1-9.
[53]
Cheang, M.C.; Chia, S.K.; Voduc, D.; Gao, D.; Leung, S.; Snider, J.; Watson, M.; Davies, S.; Bernard, P.S.; Parker, J.S.; et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J. Natl. Cancer Inst. 2009, 101, 736–750, doi:10.1093/jnci/djp082.
[54]
Goldhirsch, A.; Wood, W.C.; Coates, A.S.; Gelber, R.D.; Thurlimann, B.; Senn, H.J. 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. 2011, 22, 1736–1747, doi:10.1093/annonc/mdr304.
[55]
Varga, Z.; Diebold, J.; Dommann-Scherrer, C.; Frick, H.; Kaup, D.; Noske, A.; Obermann, E.; Ohlschlegel, C.; Padberg, B.; Rakozy, C.; et al. How reliable is Ki-67 immunohistochemistry in grade 2 breast carcinomas? A QA study of the Swiss Working Group of Breast- and Gynecopathologists. PLoS One 2012, 7, e37379, doi:10.1371/journal.pone.0037379.
[56]
Filipits, M.; Rudas, M.; Jakesz, R.; Dubsky, P.; Fitzal, F.; Singer, C.F.; Dietze, O.; Greil, R.; Jelen, A.; Sevelda, P.; et al. A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors. Clin. Cancer Res. 2011, 17, 6012–6020, doi:10.1158/1078-0432.CCR-11-0926.
[57]
Patterson, T.A.; Lobenhofer, E.K.; Fulmer-Smentek, S.B.; Collins, P.J.; Chu, T.M.; Bao, W.; Fang, H.; Kawasaki, E.S.; Hager, J.; Tikhonova, I.R.; et al. Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project. Nat. Biotechnol. 2006, 24, 1140–1150, doi:10.1038/nbt1242.
[58]
Shi, L.; Reid, L.H.; Jones, W.D.; Shippy, R.; Warrington, J.A.; Baker, S.C.; Collins, P.J.; de Longueville, F.; Kawasaki, E.S.; Lee, K.Y.; et al. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat. Biotechnol. 2006, 24, 1151–1161, doi:10.1038/nbt1239.
Sotiriou, C.; Pusztai, L. Gene-expression signatures in breast cancer. N. Engl. J. Med. 2009, 360, 790–800, doi:10.1056/NEJMra0801289.
[61]
Furness, P.N.; Taub, N.; Assmann, K.J.; Banfi, G.; Cosyns, J.P.; Dorman, A.M.; Hill, C.M.; Kapper, S.K.; Waldherr, R.; Laurinavicius, A.; et al. International variation in histologic grading is large, and persistent feedback does not improve reproducibility. Am. J. Surg. Pathol. 2003, 27, 805–810, doi:10.1097/00000478-200306000-00012.
[62]
Sotiriou, C.; Wirapati, P.; Loi, S.; Harris, A.; Fox, S.; Smeds, J.; Nordgren, H.; Farmer, P.; Praz, V.; Haibe-Kains, B.; et al. Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis. J. Natl. Cancer Inst. 2006, 98, 262–272, doi:10.1093/jnci/djj052.
[63]
Desmedt, C.; Giobbie-Hurder, A.; Neven, P.; Paridaens, R.; Christiaens, M.R.; Smeets, A.; Lallemand, F.; Haibe-Kains, B.; Viale, G.; Gelber, R.D.; et al. The Gene expression Grade Index: A potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1–98 trial. BMC Med. Genom. 2009, 2, 40, doi:10.1186/1755-8794-2-40.
[64]
Loi, S.; Haibe-Kains, B.; Desmedt, C.; Lallemand, F.; Tutt, A.M.; Gillet, C.; Ellis, P.; Harris, A.; Bergh, J.; Foekens, J.A.; et al. Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade. J. Clin. Oncol. 2007, 25, 1239–1246, doi:10.1200/JCO.2006.07.1522.
[65]
Bohmann, K.; Hennig, G.; Rogel, U.; Poremba, C.; Mueller, B.M.; Fritz, P.; Stoerkel, S.; Schaefer, K.L. RNA extraction from archival formalin-fixed paraffin-embedded tissue: A comparison of manual, semiautomated, and fully automated purification methods. Clin. Chem. 2009, 55, 1719–1727, doi:10.1373/clinchem.2008.122572.
[66]
Hennig, G.; Gehrmann, M.; Stropp, U.; Brauch, H.; Fritz, P.; Eichelbaum, M.; Schwab, M.; Schroth, W. Automated extraction of DNA and RNA from a single formalin-fixed paraffin-embedded tissue section for analysis of both single-nucleotide polymorphisms and mRNA expression. Clin. Chem. 2010, 56, 1845–1853, doi:10.1373/clinchem.2010.151233.
[67]
Muller, B.M.; Kronenwett, R.; Hennig, G.; Euting, H.; Weber, K.; Bohmann, K.; Weichert, W.; Altmann, G.; Roth, C.; Winzer, K.J.; et al. Quantitative determination of estrogen receptor, progesterone receptor, and HER2 mRNA in formalin-fixed paraffin-embedded tissue—A new option for predictive biomarker assessment in breast cancer. Diagn. Mol. Pathol. 2011, 20, 1–10, doi:10.1097/PDM.0b013e3181e3630c.
[68]
Dubsky, P.; Brase, J.C.; Fisch, K.; Jakesz, R.; Singer, C.F.; Greil, R.; Dietze, O.; Weber, K.E.; Petry, C.; Kronenwett, R.; et al. The EndoPredict score identifies late distant metastases in ER+/HER2？ breast cancer patients. Cancer Res. 2012, 72, doi:10.1158/0008-5472.SABCS12-S4-3.
[69]
Ein-Dor, L.; Kela, I.; Getz, G.; Givol, D.; Domany, E. Outcome signature genes in breast cancer: Is there a unique set? Bioinformatics 2005, 21, 171–178, doi:10.1093/bioinformatics/bth469.
[70]
Dubsky, P.C.; Jakesz, R.; Mlineritsch, B.; Postlberger, S.; Samonigg, H.; Kwasny, W.; Tausch, C.; Stoger, H.; Haider, K.; Fitzal, F.; et al. Tamoxifen and anastrozole as a sequencing strategy: A randomized controlled trial in postmenopausal patients with endocrine-responsive early breast cancer from the Austrian Breast and Colorectal Cancer Study Group. J. Clin. Oncol. 2012, 30, 722–728, doi:10.1200/JCO.2011.36.8993.
[71]
Simon, R.M.; Paik, S.; Hayes, D.F. Use of archived specimens in evaluation of prognostic and predictive biomarkers. J. Natl. Cancer Inst. 2009, 101, 1446–1452, doi:10.1093/jnci/djp335.
[72]
Martin, M.; Brase, J.C.; Ruiz-Borrego, M.; Krappmann, K.; Munarriz, B.; Fisch, K.; Ruiz, A.; Weber, K.E.; Crespo, C.; Petry, C.; et al. Prognostic performance of the EndoPredict score in node-positive chemotherapy-treated ER+/HER2？ breast cancer patients: results from the GEICAM/9906 trial. Cancer Res. 2012, 72, doi:10.1158/0008-5472.SABCS12-P2-10-11.
[73]
Brase, J.C.; Gehrmann, M.C.; Petry, C.; Weber, K.E.; Schmidt, M.; K？lbl, H.; Schroth, W.; Schwab, M.; Müller, V.; J？nicke, F.; et al. The EndoPredict score is a response predictor for neoadjuvant chemotherapy in ER-positive, HER2-negative breast cancer. Cancer Res. 2011, 71, doi:10.1158/0008-5472.SABCS11-P1-06-26.
[74]
Kronenwett, R.; Bohmann, K.; Prinzler, J.; Sinn, B.V.; Haufe, F.; Roth, C.; Averdick, M.; Ropers, T.; Windbergs, C.; Brase, J.C.; et al. Decentral gene expression analysis: Analytical validation of the Endopredict genomic multianalyte breast cancer prognosis test. BMC Cancer 2012, 12, 456, doi:10.1186/1471-2407-12-456.
[75]
Denkert, C.; Kronenwett, R.; Schlake, W.; Bohmann, K.; Penzel, R.; Weber, K.E.; Hofler, H.; Lehmann, U.; Schirmacher, P.; Specht, K.; et al. Decentral gene expression analysis for ER+/HER2？ breast cancer: Results of a proficiency testing program for the EndoPredict assay. Virchows Arch. 2012, 460, 251–259, doi:10.1007/s00428-012-1204-4.
[76]
Noske, A.; Loibl, S.; Darb-Esfahani, S.; Roller, M.; Kronenwett, R.; Muller, B.M.; Steffen, J.; von Toerne, C.; Wirtz, R.; Baumann, I.; 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. 2011, 126, 109–117, doi:10.1007/s10549-010-1316-y.
[77]
Loibl, S.; Muller, B.M.; von Minckwitz, G.; Schwabe, M.; Roller, M.; Darb-Esfahani, S.; Ataseven, B.; du Bois, A.; Fissler-Eckhoff, A.; Gerber, B.; et al. Androgen receptor expression in primary breast cancer and its predictive and prognostic value in patients treated with neoadjuvant chemotherapy. Breast Cancer Res. Treat. 2011, 130, 477–487, doi:10.1007/s10549-011-1715-8.
[78]
Muller, B.M.; Brase, J.C.; Haufe, F.; Weber, K.E.; Budzies, J.; Petry, C.; Prinzler, J.; Kronenwett, R.; Dietel, M.; Denkert, C. Comparison of the RNA-based EndoPredict multigene test between core biopsies and corresponding surgical breast cancer sections. J. Clin. Pathol. 2012, 65, 660–662, doi:10.1136/jclinpath-2012-200716.
[79]
W？ckel, A.; Kreienberg, R. First revision of the German S3 guideline ‘diagnosis, Therapy, and Follow-Up of Breast Cancer’. Breast Care (Basel) 2008, 3, 82–86, doi:10.1159/000127509.
[80]
Carlson, R.W.; Brown, E.; Burstein, H.J.; Gradishar, W.J.; Hudis, C.A.; Loprinzi, C.; Mamounas, E.P.; Perez, E.A.; Pritchard, K.; Ravdin, P.; et al. NCCN task force report: Adjuvant therapy for breast cancer. J. Natl. Compr. Canc. Netw. 2006, 4 Suppl 1, S1–S26.
[81]
Dubsky, P.; Filipits, M.; Jakesz, R.; Rudas, M.; Singer, C.F.; Greil, R.; Dietze, O.; Luisser, I.; Klug, E.; Sedivy, R.; et al. EndoPredict improves the prognostic classification derived from common clinical guidelines in ER-positive, HER2-negative early breast cancer. Ann. Oncol. 2013, 24, 640–647, doi:10.1093/annonc/mds334.
[82]
Muller, B.M.; Keil, E.; Lehmann, A.; Winzer, K.J.; Richter-Ehrenstein, C.; Prinzler, J.; Bangemann, N.; Reles, A.; Stadie, S.; Schoenegg, W.; et al. The EndoPredict gene-expression assay in clinical practice—Performance and impact on clinical decisions. PLoS One 2013, 8, e68252, doi:10.1371/journal.pone.0068252.
[83]
Ettl, J.; Gro？e Lackmann, K.; Hapfelmeier, A.; Klein, E.; Paepke, S.; Petry, C.; Specht, K.; H？fler, H.; Kiechle, M. Prospective Comparison of uPA/PAI-1 and Endopredict-Clin Score in ER-Positive, HER2-Negative Breast Cancer: Impact on Risk Stratification and Treatment Decisions. In Proceeding of 2013 ASCO Annual Meeting, Chicago, IL, USA, 31 May–4 June 2013.
[84]
Blank, P.; Schwenkglenks, M.; Dubsky, P.; Filipits, M.; Gutzwiller, F.; Lux, M.P.; Brase, J.C.; Kronenwett, R.; Szucs, T.D.; Gnant, M. Health economic analysis of guideline and gene expression signature-based risk stratification of distant recurrence in early breast cancer patients. Ann. Oncol. 2013, 24, doi:10.1093/annonc/mdt084.7.
[85]
Weigelt, B.; Reis-Filho, J.S.; Swanton, C. Genomic analyses to select patients for adjuvant chemotherapy: Trials and tribulations. Ann. Oncol. 2012, 23 Suppl 10, x211–x218.
[86]
Nielsen, T.O.; Parker, J.S.; Leung, S.; Voduc, D.; Ebbert, M.; Vickery, T.; Davies, S.R.; Snider, J.; Stijleman, I.J.; Reed, J.; 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. 2010, 16, 5222–5232, doi:10.1158/1078-0432.CCR-10-1282.
[87]
Parker, J.S.; Mullins, M.; Cheang, M.C.; Leung, S.; Voduc, D.; Vickery, T.; Davies, S.; Fauron, C.; He, X.; Hu, Z.; et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 2009, 27, 1160–1167, doi:10.1200/JCO.2008.18.1370.
[88]
Jankowitz, R.C.; Cooper, K.; Erlander, M.G.; Ma, X.J.; Kesty, N.C.; Li, H.; Chivukula, M.; Brufsky, A. Prognostic utility of the breast cancer index and comparison to Adjuvant! Online in a clinical case series of early breast cancer. Breast Cancer Res. 2011, 13, R98, doi:10.1186/bcr3038.
[89]
Jerevall, P.L.; Ma, X.J.; Li, H.; Salunga, R.; Kesty, N.C.; Erlander, M.G.; Sgroi, D.C.; Holmlund, B.; Skoog, L.; Fornander, T.; et al. Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br. J. Cancer 2011, 104, 1762–1769, doi:10.1038/bjc.2011.145.
[90]
Varga, Z.; Sinn, P.; Fritzsche, F.; von Hochstetter, A.; Noske, A.; Schraml, P.; Tausch, C.; Trojan, A.; Moch, H. Comparison of EndoPredict and oncotype DX test results in hormone receptor positive invasive breast cancer. PLoS One 2013, 8, e58483, doi:10.1371/journal.pone.0058483.
[91]
Dowsett, M.; Sestak, I.; Lopez-Knowles, E.; Sidhu, K.; Dunbier, A.K.; Cowens, J.W.; Ferree, S.; Storhoff, J.; Schaper, C.; Cuzick, J. Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J. Clin. Oncol. 2013, doi:10.1200/JCO.2012.46.1558.
[92]
Mamounas, E.P.; Tang, G.; Paik, S.; Baehner, F.L.; Liu, Q.; Jeong, J.H.; Kim, S.R.; Butler, S.M.; Jamshidian, F.; Cherbavaz, D.B.; et al. Association between the 21-gene recurrence score (RS) and benefit from adjuvant paclitaxel (Pac) in node-positive (N+), ER-positive breast cancer patients (pts): Results from NSABP B-28. Cancer Res. 2012, 72, doi:10.1158/0008-5472.SABCS12-S1-10.
