Editorial Open Access
Copyright ©2014 Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Dec 10, 2014; 5(5): 795-799
Published online Dec 10, 2014. doi: 10.5306/wjco.v5.i5.795
Emerging gene-based prognostic tools in early breast cancer: First steps to personalised medicine
Umar Wazir, Kefah Mokbel, The London Breast Institute, Princess Grace Hospital, London W1U 5NY, United Kingdom
Author contributions: Wazir U and Mokbel K contributed equally to this work.
Supported by Grants from the Breast Cancer Hope Foundation (London, United Kingdom)
Correspondence to: Kefah Mokbel, Professor, The London Breast Institute, Princess Grace Hospital, 45 Nottingham Place, London W1U 5NY, United Kingdom. kefahmokbel@hotmail.com
Telephone: +44-207-9082040 Fax: +44-207-9082275
Received: June 23, 2014
Revised: August 19, 2014
Accepted: September 16, 2014
Published online: December 10, 2014

Abstract

Breast cancer remains a major cause of neoplastic disease in much of the developed world. The majority of cases are diagnosed with oestrogen receptor (ER)-positive and human epidermal growth factor receptor-2 negative invasive ductal carcinoma and are treated predominantly by surgery which includes sentinel node biopsy and adjuvant endocrine therapy ± adjuvant radiotherapy. It is believed that an indeterminate subset of the patient population is needlessly incurring chemotherapy related morbidity without attaining any increase in survival due to therapy. Furthermore in the era of extended adjuvant endocrine therapy it is important to identify those patients who can be safely treated with 5 years rather than 10 years of endocrine therapy thus optimising the benefit-risk balance. This perception has propelled the development of more personalised prognostic tools for newly diagnosed cases of ER-positive breast cancer. In this article, we shall review the evidence regarding the currently available gene assays for human breast cancer.

Key Words: Personalised medicine, Breast cancer, Prognosis, Polymerase chain reaction

Core tip: Recurrence score, Prosigna and EndoPredict (EP) currently have the most convincing evidence available, of which Prosigna and EP have a significant degree of external validation. In terms of cost and turnover, EP has an advantage over its competitors, being designed to be performed at a local laboratory rather than at a central facility. The results of the MINDACT and TailoRx trials are awaited.



INTRODUCTION

Breast cancer is remains a major cause of neoplastic disease in much of the developed world, comprising of 30.7% of cancers diagnosed in 2011. The 41523 cases were registered during that year[1]. The majority of cases are diagnosed with oestrogen receptor (ER) positive and human epidermal growth factor receptor-2 (HER2) negative invasive ductal carcinoma, which predominantly undergo surgery and staging, including sentinel node biopsy (SNB)[2]. Subsequent decisions by the multi-disciplinary team regarding the use of chemotherapy, radiotherapy and endocrine therapy are determined by the perceived risk of recurrence. Conventionally, the risk of recurrence is estimated based on histology, receptor status and the result of the SNB, or by composite prognostic tools, such as the Nottingham Prognostic Index[3], and Adjuvant! Online (Adjuvant, Inc., San Antonio, TX)[4].

However, it is believed that an indeterminate subset of the patient population is needlessly incurring chemotherapy related morbidity without attaining any increase in survival due to therapy. This perception has propelled the development of more personalised prognostic tools for newly diagnosed cases of breast cancer[3]. Furthermore, the results of the ATLAS randomised trial suggests that the survival benefit of continuing adjuvant tamoxifen for 10 years may be superior to stopping at 5 years after diagnosis of ER positive breast cancer. This finding has necessitated the development of new tools that could identify the subset of women who would not benefit from extended adjuvant endocrine therapy beyond 5 years[5].

Central to these developments was the identification of sub-types of breast cancer based on so-called “molecular patterns” or “ignatures”. These classifications are now referred to as intrinsic sub-types, and have a broad if imperfect concordance with breast cancer classifications based on histology and receptor status. Initially, breast cancers were typed as luminal, HER2 enriched and basal. Luminal are further sub-typed into luminal-A and -B[6]. The intrinsic typing of breast cancers continues to be an area of continuous research. As of the time of writing, 7 intrinsic types have been identified thus far. Luminal-A is characterised as strongly ER positive, while luminal-B is less so, with a greater preponderance of proliferative genes. Broadly speaking, luminal-A corresponds with ER positive and HER2 negative tumours, which are characterised as relatively low risk for recurrence[7].

With a suitable prognostic test, it may be possible to treat a portion of luminal-A patient with post-resection endocrine therapy rather than chemotherapy with endocrine therapy. This subset of patient has been the target of the majority of the extant prognostic and predictive assays.

The major gene-based prognostic assays for breast cancer have been discussed below (Table 1).

Table 1 Comparison of gene-based prognostic assays for early oestrogen receptor + breast cancer.
Prognostic assayManufacturerUnderlying technologyNo. of genesTest inductionOutput/scoreComments
MammaPrintAgendia BV, The NetherlandDNA microarrays70Reference labRisk category for recurrence (low risk vs high risk)Prospective validation is awaited with the results of the ongoing MINDACT trial
Oncotype-DXGenomic Health Inc., CA, United StatesqRT-PCR21Reference labRS scores (1-100) stratified into low, intermediate and high-risk groups for recurrenceOncotype-DX has been included in several guidelines, and has been validated by internal industrial studies (NSABB trial B14). The characterisation of intermediate risk group awaits the results of the TAILORx trial
PAM50/ProsignaNanoString Technologies, Inc., WA, United StatesDNA microarrays and qRT-PCR using nCounter technology50Reference labROR scores (1-100) stratified into low, intermediate and high risk groupsThe assay was been validated in studies based on the ATAC and ABCSG-8 trials
EndoPredictSividon Diagnostics GmbH, Köln, GermanyqRT-PCR8Local labLow or high risk groups on the basis of EP or EPClin scoresEndoPredict has been validated in ABCSG-6 and ABCSG-8 trials, and has been included in German guidelines. Potentially shorter turnover at lower cost, as there is no need for dispatching samples to a reference laboratory
MAMMAPRINT

This the oldest test available, developed by Agendia BV (Netherland). This is a 70 gene DNA microarray test performed on frozen or formalin-fixed tissue by a central reference laboratory, which returns a score which stratify patients into a high and low risk categories[8].

The assay was developed in a non-randomised cohort of 78 patients treated at the Netherland Cancer Institute, in which the median age was 55[9]. Subsequent internal studies characterised this assay to be an independent prognostic assay in the primary target group, outperforming clinical parameters[10].

However, it is yet to be validated externally. The studies pertaining to this assay were performed in only one market. Furthermore, owing to the lack of randomisation, the cited studies do not qualify as level 1 evidence. In addition, the population in which it was used is considerably younger than that seen in many countries where this assay may potentially be utilised[11]. Furthermore, the test seems to be a reliable predictor of recurrence occurring in the early follow up period. In meta-analysis of published studies, a high MammaPrint score was found to predict a 12% distant disease-free survival benefit from the addition of chemotherapy[12]. Prospective validation is awaited with the results of the ongoing MINDACT (Microarray In Node negative and 1-3 positive lymph node Disease may Avoid ChemoTherapy) trial[13].

ONCOTYPE-DX

Oncotype-DX (Genomic Health Inc., CA, United States) is currently the most widely available prognostic assay for breast cancer. It is a 21-gene assay in which quantitative real-time polymerase chain reaction (qRT-PCR) is performed on formalin-fixed breast cancer tissue samples taken during initial surgical resection and processed in a central laboratory, which returns a recurrence score (RS) out of a maximum score of 100. It is quoted to have a turnaround time of 7-10 d. It is primarily advised in early ER positive and HER2 negative disease with negative SLN[14]. In addition, it is also recommended in ER positive and HER2 negative disease in elderly patients with positive SNB[15].

The RS score was formulated and validated in patients enrolled in the National Surgical Adjuvant Breast and Bowel Project (NSABB) trials. Specifically, the predictive value of the score was initially validated by the NSABB trial B14, in which patients were randomly allocated into placebo and tamoxifen groups[16]. This was followed up by the NSABB trial B20, in which patients on tamoxifen alone were compared with patients receiving tamoxifen with chemotherapy[17]. A subsequent retrospective study is cited for validation of Oncotype-DX for predicting prognosis in relatively elderly patients treated with tamoxifen with SNB positive disease[18].

These initial studies stratified RS scores into low, intermediate and high risk groups, with RS score below 18 being labelled as low risk of recurrence (< 5% risk), and 31 and above as high risk (39.5%)[16]. Since the beginning, the clinical implications of an intermediate score has been ambiguous. Furthermore, the thresholds have been revised downwards to 11 and 25. Validation for the new thresholds is less clear[8]. The results of the Trial Assigning Individualized Options for Treatment (TAILORx) are awaited to help clarify the recommendations for the intermediate group[19].

There have been several studies suggesting that Oncotype-DX is cost effective as a prognostic test[20]. Furthermore, this assay has been recommended by a number of regulatory bodies[11,21]. However, the cost and turnover time of the test are not insignificant primarily due to test centralization. Although the Oncotype-DX was validated by randomised controlled trials, it must be emphasised that these studies were supported by funding from industry, and are regarded as internal trials by regulatory bodies[11]. It should be also highlighted that only 26% and 29% of patients (some of whom had HER2 positive tumours) in the B-14 and B-20 trials respectively were available for analysis thus reducing the effect of randomisation. This significantly weakens the evidence regarding the predictive role of Oncotype-DX in adjuvant chemotherapy, so much so that the evidence does not reach level 1 as per the Marker Utility Grading System[22]. Moreover, the Oncotype-DX is not specific to HER2 negative disease and does not incorporate any clinicopathological features which could improve its prognostic ability of longer term clinical outcome. Although the test has not been validated externally for reproducibility and reliability due to industrial centralization, the internal industry reports suggest that the test is reliable.

PAM50

Parker et al[23] developed a risk of recurrence (ROR) score (also called Prosigna) which is applicable to all tumour types including those that are ER positive. The score is derived by analysing of the expression levels of a set of 50 genes using qRT-PCR and DNA microarrays. The ROR score was developed as a prognostic tool in a cohort of 761 patients[23]. The DNA microarray cluster partitioning and analysis was done using the partitioning around medoid or microarray (PAM) methodology[24]. In addition, a related test was developed primarily as an intrinsic sub-type classifier for breast cancer. This test was termed PAM50 (NanoString Technologies, Inc., WA, United States)[25].

Currently, the ROR score and PAM50 test are performed on formalin fixed samples by a central laboratory utilising proprietary nCounter technology[26,27]. Like Oncotype-DX, ROR scores (1-100) are stratified into low, intermediate and high risk groups. The ROR score has predictive value in the neoadjuvant setting, as well as in the case of newly diagnosed patients with node negative disease[23]. The assay was validated in studies based on the ATAC[28] and ABCSG-8 trials[29]. In addition, a recent study validated the Prosigna assay for use at local laboratories[26]. Dowsett et al[28] found Prosigna to be superior to immunohistochemistry and RS in ER positive node negative patients receiving endocrine therapy.

ENDOPREDICT

EndoPredict (EP) is a relatively new assay developed by Sividon Diagnostics GmbH (Köln, Germany), which until recently was largely limited to German-speaking markets. It is an 8-gene qRT-PCR assay performed on formalin fixed breast tissue, design in the first instance to be performed at a local laboratory. Remarkably, whilst these genes are related to proliferation and hormone receptor activity, the assay does not include ER, PR, or HER2 status[30]. It was validated on 1702 samples taken from two randomised control trials, ABCSG-6 and ABCSG-8[31].

There is a level Ib evidence showing that EP is an independent prognostic parameter in patients with ER-positive, HER2 negative breast cancer. Patients with a low EP score can be safely treated with endocrine therapy as the only adjuvant systemic treatment, therefore, they can be spared chemotherapy[32]. The level of evidence regarding its independent prognostic role is similar to that of Oncotype-DX[33]. Furthermore, a hybrid score incorporating clinical parameters (EpClin) has been shown to be superior to purely clinical assessment tools[32]. In addition, Muller et al[34] found that use of EP resulted in change in clinical decision in 37.7% of patients when applied to a cohort of 167 patients. The effects of the change in therapy are to be assessed.

A further consideration is the inherent costs and logistics such a test may incur. In this regard, EP has an advantage over other similar test, being designed to be performed at a local laboratory rather than at a central facility. Proponents of this assay cite the fact that EndoPredict can be performed on-site resulting in a faster result at a lower cost. In addition, it also has the advantage of dividing tumours into two categories: low and high thus avoiding the immediate group or grey zone of characterisation, which can create anxiety and dilemma to both the oncologist and the patient. EP has achieved CE certification, and has been included in German guidelines[35]. In addition to reliably identifying patients who can be safely treated with adjuvant endocrine therapy only, EP has other potential applications including further stratification of tumours with intermediate RS (18-31) in order to make final recommendations regarding the need for chemothery and selection of patients for 5 years vs 10 of adjuvant endocrine therapy. Finally, the hybrid score EpClin is applicable to patients with node positive ER-positive breast cancer.

However, owing to its relative novelty, other regulatory bodies are yet to consider EP in their recommendations.

CONCLUSION

The recent developments in our understanding of intrinsic sub-types within breast cancer, and the explosion in the use of PCR and DNA microarrays have resulted in a growing number of promising prognostic tools for human breast cancer. OncoType-DX, Prosigna and EP currently have the most convincing evidence available, of which Prosigna and EP have a significant degree of external validation. EpClin is the only tool available that combines molecular signature with important clinicopathological parameters with the potential advantage of superior prognostication regarding the longer term clinical outcome. The RS is the only assay that has been investigated in a randomised trial population as a predictive tool of chemotherapy benefit. However the evidence in this context is considered to be of low quality[22].

Whilst some products are more mature than others, the results of several ongoing trials, such as MINDACT and TailoRx, can be expected to have profound implications for the selection of the optimal test.

Footnotes

P- Reviewer: Petmitr S, Rameshwar P, Ye QN S- Editor: Ji FF L- Editor: A E- Editor: Lu YJ

References
1.  ; ONS.  Cancer registration statistics, england, 2011. London: Office of National Statistics 2013;  Available from: http: //www.ons.gov.uk/ons/rel/vsob1/cancer-statistics-registrations--england--series-mb1-/no--42--2011/stb-cancer-statistics-registrations-2011.html.  [PubMed]  [DOI]  [Cited in This Article: ]
2.  Early and locally advanced breast cancer - diagnosis and treatment. London, UK: National Collaborating Centre for Cancer, 2009.  Available from: http: //www.nice.org.uk/guidance/cg80.  [PubMed]  [DOI]  [Cited in This Article: ]
3.  Haybittle JL, Blamey RW, Elston CW, Johnson J, Doyle PJ, Campbell FC, Nicholson RI, Griffiths K. A prognostic index in primary breast cancer. Br J Cancer. 1982;45:361-366.  [PubMed]  [DOI]  [Cited in This Article: ]
4.  Olivotto IA, Bajdik CD, Ravdin PM, Speers CH, Coldman AJ, Norris BD, Davis GJ, Chia SK, Gelmon KA. Population-based validation of the prognostic model ADJUVANT! for early breast cancer. J Clin Oncol. 2005;23:2716-2725.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 406]  [Cited by in F6Publishing: 370]  [Article Influence: 19.5]  [Reference Citation Analysis (0)]
5.  Davies C, Pan H, Godwin J, Gray R, Arriagada R, Raina V, Abraham M, Medeiros Alencar VH, Badran A, Bonfill X. 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.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1348]  [Cited by in F6Publishing: 1289]  [Article Influence: 117.2]  [Reference Citation Analysis (0)]
6.  Perou CM, Sørlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA. Molecular portraits of human breast tumours. Nature. 2000;406:747-752.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 10665]  [Cited by in F6Publishing: 10386]  [Article Influence: 432.8]  [Reference Citation Analysis (0)]
7.  Kittaneh M, Montero AJ, Glück S. Molecular profiling for breast cancer: a comprehensive review. Biomark Cancer. 2013;5:61-70.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 106]  [Cited by in F6Publishing: 115]  [Article Influence: 10.5]  [Reference Citation Analysis (0)]
8.  Sinn P, Aulmann S, Wirtz R, Schott S, Marme F, Varga Z, Lebeau A, Kreipe H, Schneeweiss A. Multigene Assays for Classification, Prognosis, and Prediction in Breast Cancer: a Critical Review on the Background and Clinical Utility. Geburtshilfe Frauenheilkd. 2013;73:932-940.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 43]  [Cited by in F6Publishing: 43]  [Article Influence: 3.9]  [Reference Citation Analysis (0)]
9.  van 't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415:530-536.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6904]  [Cited by in F6Publishing: 6222]  [Article Influence: 282.8]  [Reference Citation Analysis (0)]
10.  Bueno-de-Mesquita JM, Linn SC, Keijzer R, Wesseling J, Nuyten DS, van Krimpen C, Meijers C, de Graaf PW, Bos MM, Hart AA. Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat. 2009;117:483-495.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 122]  [Cited by in F6Publishing: 129]  [Article Influence: 8.1]  [Reference Citation Analysis (0)]
11.  Gene expression profiling and expanded immunohistochemistry tests for guiding adjuvant chemotherapy decisions in early breast cancer management: Mammaprint, oncotype dx, ihc4 and mammostrat. London, UK: National Institute for Health and Care Excellence (NICE), 2013.  Available from: http: //www.nice.org.uk/guidance/dg10.  [PubMed]  [DOI]  [Cited in This Article: ]
12.  Knauer M, Mook S, Rutgers EJ, Bender RA, Hauptmann M, van de Vijver MJ, Koornstra RH, Bueno-de-Mesquita JM, Linn SC, van ‘t Veer LJ. The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat. 2010;120:655-661.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 196]  [Cited by in F6Publishing: 206]  [Article Influence: 14.7]  [Reference Citation Analysis (0)]
13.  Cardoso F, Van’t Veer L, Rutgers E, Loi S, Mook S, Piccart-Gebhart MJ. Clinical application of the 70-gene profile: the MINDACT trial. J Clin Oncol. 2008;26:729-735.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 363]  [Cited by in F6Publishing: 322]  [Article Influence: 20.1]  [Reference Citation Analysis (0)]
14.  Lo SS, Mumby PB, Norton J, Rychlik K, Smerage J, Kash J, Chew HK, Gaynor ER, Hayes DF, Epstein A. 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. 2010;28:1671-1676.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 217]  [Cited by in F6Publishing: 220]  [Article Influence: 15.7]  [Reference Citation Analysis (0)]
15.  Oratz R, Kim B, Chao C, Skrzypczak S, Ory C, Bugarini R, Broder M. Physician survey of the effect of the 21-gene recurrence score assay results on treatment recommendations for patients with lymph node-positive, estrogen receptor-positive breast cancer. J Oncol Pract. 2011;7:94-99.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 41]  [Cited by in F6Publishing: 44]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
16.  Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, Baehner FL, Walker MG, Watson D, Park T. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351:2817-2826.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4524]  [Cited by in F6Publishing: 4259]  [Article Influence: 213.0]  [Reference Citation Analysis (0)]
17.  Paik S, Tang G, Shak S, Kim C, Baker J, Kim W, Cronin M, Baehner FL, Watson D, Bryant J. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol. 2006;24:3726-3734.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1899]  [Cited by in F6Publishing: 1855]  [Article Influence: 103.1]  [Reference Citation Analysis (0)]
18.  Albain KS, Barlow WE, Shak S, Hortobagyi GN, Livingston RB, Yeh IT, Ravdin P, Bugarini R, Baehner FL, Davidson NE. 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.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1068]  [Cited by in F6Publishing: 1003]  [Article Influence: 71.6]  [Reference Citation Analysis (0)]
19.  Sparano JA. TAILORx: trial assigning individualized options for treatment (Rx). Clin Breast Cancer. 2006;7:347-350.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 200]  [Cited by in F6Publishing: 190]  [Article Influence: 11.2]  [Reference Citation Analysis (0)]
20.  Holt S, Bertelli G, Humphreys I, Valentine W, Durrani S, Pudney D, Rolles M, Moe M, Khawaja S, Sharaiha Y. A decision impact, decision conflict and economic assessment of routine Oncotype DX testing of 146 women with node-negative or pNImi, ER-positive breast cancer in the U.K. Br J Cancer. 2013;108:2250-2258.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 75]  [Cited by in F6Publishing: 79]  [Article Influence: 7.2]  [Reference Citation Analysis (0)]
21.  OHTAC recommendation: Multi-gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer. Toronto: Ontario Health Technology Advisory Committee, October 2010.  Available from: http: //www.hqontario.ca/evidence/publications-and-ohtac-recommendations/ontario-health-technology-assessment-series/gene-expression-profiling-for-guiding-adjuvant-chemotherapy-decisions-in-women-with-early-breast-cancer.  [PubMed]  [DOI]  [Cited in This Article: ]
22.  Gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer: an evidence-based and economic analysis Ont Health Technol Assess Ser. 2010;10:1-57.  [PubMed]  [DOI]  [Cited in This Article: ]
23.  Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, Davies S, Fauron C, He X, Hu Z. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27:1160-1167.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3209]  [Cited by in F6Publishing: 3012]  [Article Influence: 200.8]  [Reference Citation Analysis (0)]
24.  Dudoit S, Fridlyand J. A prediction-based resampling method for estimating the number of clusters in a dataset. Genome Biol. 2002;3:RESEARCH0036.  [PubMed]  [DOI]  [Cited in This Article: ]
25.  Nielsen TO, Parker JS, Leung S, Voduc D, Ebbert M, Vickery T, Davies SR, Snider J, Stijleman IJ, Reed J. 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.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 544]  [Cited by in F6Publishing: 541]  [Article Influence: 38.6]  [Reference Citation Analysis (0)]
26.  Nielsen T, Wallden B, Schaper C, Ferree S, Liu S, Gao D, Barry G, Dowidar N, Maysuria M, Storhoff J. Analytical validation of the PAM50-based Prosigna Breast Cancer Prognostic Gene Signature Assay and nCounter Analysis System using formalin-fixed paraffin-embedded breast tumor specimens. BMC Cancer. 2014;14:177.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 214]  [Cited by in F6Publishing: 211]  [Article Influence: 21.1]  [Reference Citation Analysis (0)]
27.  Kulkarni MM. Digital multiplexed gene expression analysis using the NanoString nCounter system. Curr Protoc Mol Biol. 2011;Chapter 25:Unit25B.10.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 155]  [Cited by in F6Publishing: 190]  [Article Influence: 14.6]  [Reference Citation Analysis (0)]
28.  Dowsett M, Sestak I, Lopez-Knowles E, Sidhu K, Dunbier AK, Cowens JW, 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;31:2783-2790.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 485]  [Cited by in F6Publishing: 435]  [Article Influence: 39.5]  [Reference Citation Analysis (0)]
29.  Gnant M, Filipits M, Greil R, Stoeger H, Rudas M, Bago-Horvath Z, Mlineritsch B, Kwasny W, Knauer M, Singer C. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 Risk of Recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol. 2014;25:339-345.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 244]  [Cited by in F6Publishing: 256]  [Article Influence: 23.3]  [Reference Citation Analysis (0)]
30.  Denkert C, Kronenwett R, Schlake W, Bohmann K, Penzel R, Weber KE, Höfler H, Lehmann U, Schirmacher P, Specht K. 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.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 70]  [Cited by in F6Publishing: 74]  [Article Influence: 6.2]  [Reference Citation Analysis (0)]
31.  Dubsky P, Brase JC, Jakesz R, Rudas M, Singer CF, Greil R, Dietze O, Luisser I, Klug E, Sedivy R. The EndoPredict score provides prognostic information on late distant metastases in ER+/HER2- breast cancer patients. Br J Cancer. 2013;109:2959-2964.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 220]  [Cited by in F6Publishing: 234]  [Article Influence: 21.3]  [Reference Citation Analysis (0)]
32.  Dubsky P, Filipits M, Jakesz R, Rudas M, Singer CF, Greil R, Dietze O, Luisser I, Klug E, Sedivy R. EndoPredict improves the prognostic classification derived from common clinical guidelines in ER-positive, HER2-negative early breast cancer. Ann Oncol. 2013;24:640-647.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 144]  [Cited by in F6Publishing: 132]  [Article Influence: 11.0]  [Reference Citation Analysis (0)]
33.  Filipits M, Rudas M, Jakesz R, Dubsky P, Fitzal F, Singer CF, Dietze O, Greil R, Jelen A, Sevelda P. 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.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 466]  [Cited by in F6Publishing: 465]  [Article Influence: 35.8]  [Reference Citation Analysis (0)]
34.  Muller BM, Keil E, Lehmann A, Winzer KJ, Richter-Ehrenstein C, Prinzler J, Bangemann N, Reles A, Stadie S, Schoenegg W. The EndoPredict Gene-Expression Assay in Clinical Practice - Performance and Impact on Clinical Decisions. PLoS One. 2013;8:e68252.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 55]  [Cited by in F6Publishing: 58]  [Article Influence: 5.3]  [Reference Citation Analysis (0)]
35.  Blank PR, Schwenkglenks M, Dubsky P, Filipits M, Gutzwiller F, Lux MP, Brase J, Kronenwett R, Szucs TD, 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;2013:iii31-iii31 Available from: http: //annonc.oxfordjournals.org/content/24/suppl_3/iii31.1.extract.  [PubMed]  [DOI]  [Cited in This Article: ]