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1.  A 50-Gene Intrinsic Subtype Classifier for Prognosis and Prediction of Benefit from Adjuvant Tamoxifen 
Purpose
Gene expression profiling classifies breast cancer into intrinsic subtypes based on the biology of the underlying disease pathways. We have used material from a prospective randomized trial of tamoxifen versus placebo in premenopausal women with primary breast cancer (NCIC CTG MA.12) to evaluate the prognostic and predictive significance of intrinsic subtypes identified by both the PAM50 gene set and by immunohistochemistry.
Experimental Design
Total RNA from 398 of 672 (59%) patients was available for intrinsic subtyping with a quantitative reverse transcriptase PCR (qRT-PCR) 50-gene predictor (PAM50) for luminal A, luminal B, HER-2–enriched, and basal-like subtypes. A tissue microarray was also constructed from 492 of 672 (73%) of the study population to assess a panel of six immunohistochemical IHC antibodies to define the same intrinsic subtypes.
Results
Classification into intrinsic subtypes by the PAM50 assay was prognostic for both disease-free survival (DFS; P = 0.0003) and overall survival (OS; P = 0.0002), whereas classification by the IHC panel was not. Luminal subtype by PAM50 was predictive of tamoxifen benefit [DFS: HR, 0.52; 95% confidence interval (CI), 0.32–0.86 vs. HR, 0.80; 95% CI, 0.50–1.29 for nonluminal subtypes], although the interaction test was not significant (P = 0.24), whereas neither subtyping by central immunohistochemistry nor by local estrogen receptor (ER) or progesterone receptor (PR) status were predictive. Risk of relapse (ROR) modeling with the PAM50 assay produced a continuous risk score in both node-negative and node-positive disease.
Conclusions
In the MA.12 study, intrinsic subtype classification by qRT-PCR with the PAM50 assay was superior to IHC profiling for both prognosis and prediction of benefit from adjuvant tamoxifen.
doi:10.1158/1078-0432.CCR-12-0286
PMCID: PMC3743663  PMID: 22711706
2.  Development and verification of the PAM50-based Prosigna breast cancer gene signature assay 
BMC Medical Genomics  2015;8:54.
Background
The four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories.
Methods
514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies.
Results
The gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online.
Conclusions
The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.
Electronic supplementary material
The online version of this article (doi:10.1186/s12920-015-0129-6) contains supplementary material, which is available to authorized users.
doi:10.1186/s12920-015-0129-6
PMCID: PMC4546262  PMID: 26297356
3.  PAM50 Breast Cancer Subtyping by RT-qPCR and Concordance with Standard Clinical Molecular Markers 
BMC Medical Genomics  2012;5:44.
Background
Many methodologies have been used in research to identify the “intrinsic” subtypes of breast cancer commonly known as Luminal A, Luminal B, HER2-Enriched (HER2-E) and Basal-like. The PAM50 gene set is often used for gene expression-based subtyping; however, surrogate subtyping using panels of immunohistochemical (IHC) markers are still widely used clinically. Discrepancies between these methods may lead to different treatment decisions.
Methods
We used the PAM50 RT-qPCR assay to expression profile 814 tumors from the GEICAM/9906 phase III clinical trial that enrolled women with locally advanced primary invasive breast cancer. All samples were scored at a single site by IHC for estrogen receptor (ER), progesterone receptor (PR), and Her2/neu (HER2) protein expression. Equivocal HER2 cases were confirmed by chromogenic in situ hybridization (CISH). Single gene scores by IHC/CISH were compared with RT-qPCR continuous gene expression values and “intrinsic” subtype assignment by the PAM50. High, medium, and low expression for ESR1, PGR, ERBB2, and proliferation were selected using quartile cut-points from the continuous RT-qPCR data across the PAM50 subtype assignments.
Results
ESR1, PGR, and ERBB2 gene expression had high agreement with established binary IHC cut-points (area under the curve (AUC) ≥ 0.9). Estrogen receptor positivity by IHC was strongly associated with Luminal (A and B) subtypes (92%), but only 75% of ER negative tumors were classified into the HER2-E and Basal-like subtypes. Luminal A tumors more frequently expressed PR than Luminal B (94% vs 74%) and Luminal A tumors were less likely to have high proliferation (11% vs 77%). Seventy-seven percent (30/39) of ER-/HER2+ tumors by IHC were classified as the HER2-E subtype. Triple negative tumors were mainly comprised of Basal-like (57%) and HER2-E (30%) subtypes. Single gene scoring for ESR1, PGR, and ERBB2 was more prognostic than the corresponding IHC markers as shown in a multivariate analysis.
Conclusions
The standard immunohistochemical panel for breast cancer (ER, PR, and HER2) does not adequately identify the PAM50 gene expression subtypes. Although there is high agreement between biomarker scoring by protein immunohistochemistry and gene expression, the gene expression determinations for ESR1 and ERBB2 status was more prognostic.
doi:10.1186/1755-8794-5-44
PMCID: PMC3487945  PMID: 23035882
4.  Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay 
Breast Cancer Research  2006;8(2):R23.
Introduction
Predicting the clinical course of breast cancer is often difficult because it is a diverse disease comprised of many biological subtypes. Gene expression profiling by microarray analysis has identified breast cancer signatures that are important for prognosis and treatment. In the current article, we use microarray analysis and a real-time quantitative reverse-transcription (qRT)-PCR assay to risk-stratify breast cancers based on biological 'intrinsic' subtypes and proliferation.
Methods
Gene sets were selected from microarray data to assess proliferation and to classify breast cancers into four different molecular subtypes, designated Luminal, Normal-like, HER2+/ER-, and Basal-like. One-hundred and twenty-three breast samples (117 invasive carcinomas, one fibroadenoma and five normal tissues) and three breast cancer cell lines were prospectively analyzed using a microarray (Agilent) and a qRT-PCR assay comprised of 53 genes. Biological subtypes were assigned from the microarray and qRT-PCR data by hierarchical clustering. A proliferation signature was used as a single meta-gene (log2 average of 14 genes) to predict outcome within the context of estrogen receptor status and biological 'intrinsic' subtype.
Results
We found that the qRT-PCR assay could determine the intrinsic subtype (93% concordance with microarray-based assignments) and that the intrinsic subtypes were predictive of outcome. The proliferation meta-gene provided additional prognostic information for patients with the Luminal subtype (P = 0.0012), and for patients with estrogen receptor-positive tumors (P = 3.4 × 10-6). High proliferation in the Luminal subtype conferred a 19-fold relative risk of relapse (confidence interval = 95%) compared with Luminal tumors with low proliferation.
Conclusion
A real-time qRT-PCR assay can recapitulate microarray classifications of breast cancer and can risk-stratify patients using the intrinsic subtype and proliferation. The proliferation meta-gene offers an objective and quantitative measurement for grade and adds significant prognostic information to the biological subtypes.
doi:10.1186/bcr1399
PMCID: PMC1557722  PMID: 16626501
5.  Concordance among gene expression-based predictors for ER-positive breast cancer treated with adjuvant tamoxifen 
Annals of Oncology  2012;23(11):2866-2873.
Background
ER-positive (ER+ ) breast cancer includes all of the intrinsic molecular subtypes, although the luminal A and B subtypes predominate. In this study, we evaluated the ability of six clinically relevant genomic signatures to predict relapse in patients with ER+ tumors treated with adjuvant tamoxifen only.
Methods
Four microarray datasets were combined and research-based versions of PAM50 intrinsic subtyping and risk of relapse (PAM50-ROR) score, 21-gene recurrence score (OncotypeDX), Mammaprint, Rotterdam 76 gene, index of sensitivity to endocrine therapy (SET) and an estrogen-induced gene set were evaluated. Distant relapse-free survival (DRFS) was estimated by Kaplan–Meier and log-rank tests, and multivariable analyses were done using Cox regression analysis. Harrell's C-index was also used to estimate performance.
Results
All signatures were prognostic in patients with ER+ node-negative tumors, whereas most were prognostic in ER+ node-positive disease. Among the signatures evaluated, PAM50-ROR, OncotypeDX, Mammaprint and SET were consistently found to be independent predictors of relapse. A combination of all signatures significantly increased the performance prediction. Importantly, low-risk tumors (>90% DRFS at 8.5 years) were identified by the majority of signatures only within node-negative disease, and these tumors were mostly luminal A (78%–100%).
Conclusions
Most established genomic signatures were successful in outcome predictions in ER+ breast cancer and provided statistically independent information. From a clinical perspective, multiple signatures combined together most accurately predicted outcome, but a common finding was that each signature identified a subset of luminal A patients with node-negative disease who might be considered suitable candidates for adjuvant endocrine therapy alone.
doi:10.1093/annonc/mds080
PMCID: PMC3477878  PMID: 22532584
breast cancer; genomics; luminal; mammaprint; oncotype; PAM50
6.  Prediction consistency and clinical presentations of breast cancer molecular subtypes for Han Chinese population 
Journal of Translational Medicine  2012;10(Suppl 1):S10.
Background
Breast cancer is a heterogeneous disease in terms of transcriptional aberrations; moreover, microarray gene expression profiles had defined 5 molecular subtypes based on certain intrinsic genes. This study aimed to evaluate the prediction consistency of breast cancer molecular subtypes from 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50) as well as clinical presentations of each molecualr subtype in Han Chinese population.
Methods
In all, 169 breast cancer samples (44 from Taiwan and 125 from China) of Han Chinese population were gathered, and the gene expression features corresponding to 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50) were retrieved for molecular subtype prediction.
Results
For Sørlie 500 and Hu 306 intrinsic gene set, mean-centring of genes and distance-weighted discrimination (DWD) remarkably reduced the number of unclassified cases. Regarding pairwise agreement, the highest predictive consistency was found between Hu 306 and PAM50. In all, 150 and 126 samples were assigned into identical subtypes by both Hu 306 and PAM50 genes, under mean-centring and DWD. Luminal B tended to show a higher nuclear grade and have more HER2 over-expression status than luminal A did. No basal-like breast tumours were ER positive, and most HER2-enriched breast tumours showed HER2 over-expression, whereas, only two-thirds of ER negativity/HER2 over-expression tumros were predicted as HER2-enriched molecular subtype. For 44 Taiwanese breast cancers with survival data, a better prognosis of luminal A than luminal B subtype in ER-postive breast cancers and a better prognosis of basal-like than HER2-enriched subtype in ER-negative breast cancers was observed.
Conclusions
We suggest that the intrinsic signature Hu 306 or PAM50 be used for breast cancers in the Han Chinese population during molecular subtyping. For the prognostic value and decision making based on intrinsic subtypes, further prospective study with longer survival data is needed.
doi:10.1186/1479-5876-10-S1-S10
PMCID: PMC3445863  PMID: 23046482
7.  Subtyping of Breast Cancer by Immunohistochemistry to Investigate a Relationship between Subtype and Short and Long Term Survival: A Collaborative Analysis of Data for 10,159 Cases from 12 Studies 
PLoS Medicine  2010;7(5):e1000279.
Paul Pharoah and colleagues evaluate the prognostic significance of immunohistochemical subtype classification in more than 10,000 breast cancer cases with early disease, and examine the influence of a patient's survival time on the prediction of future survival.
Background
Immunohistochemical markers are often used to classify breast cancer into subtypes that are biologically distinct and behave differently. The aim of this study was to estimate mortality for patients with the major subtypes of breast cancer as classified using five immunohistochemical markers, to investigate patterns of mortality over time, and to test for heterogeneity by subtype.
Methods and Findings
We pooled data from more than 10,000 cases of invasive breast cancer from 12 studies that had collected information on hormone receptor status, human epidermal growth factor receptor-2 (HER2) status, and at least one basal marker (cytokeratin [CK]5/6 or epidermal growth factor receptor [EGFR]) together with survival time data. Tumours were classified as luminal and nonluminal tumours according to hormone receptor expression. These two groups were further subdivided according to expression of HER2, and finally, the luminal and nonluminal HER2-negative tumours were categorised according to expression of basal markers. Changes in mortality rates over time differed by subtype. In women with luminal HER2-negative subtypes, mortality rates were constant over time, whereas mortality rates associated with the luminal HER2-positive and nonluminal subtypes tended to peak within 5 y of diagnosis and then decline over time. In the first 5 y after diagnosis the nonluminal tumours were associated with a poorer prognosis, but over longer follow-up times the prognosis was poorer in the luminal subtypes, with the worst prognosis at 15 y being in the luminal HER2-positive tumours. Basal marker expression distinguished the HER2-negative luminal and nonluminal tumours into different subtypes. These patterns were independent of any systemic adjuvant therapy.
Conclusions
The six subtypes of breast cancer defined by expression of five markers show distinct behaviours with important differences in short term and long term prognosis. Application of these markers in the clinical setting could have the potential to improve the targeting of adjuvant chemotherapy to those most likely to benefit. The different patterns of mortality over time also suggest important biological differences between the subtypes that may result in differences in response to specific therapies, and that stratification of breast cancers by clinically relevant subtypes in clinical trials is urgently required.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Each year, more than one million women discover they have breast cancer. Breast cancer begins when cells in the breast's milk-producing glands or in the tubes (ducts) that take milk to the nipples acquire genetic changes that allow them to divide uncontrollably and to move around the body (metastasize). The uncontrolled cell division leads to the formation of a lump that can be detected by mammography (a breast X-ray) or by manual breast examination. Breast cancer is treated by surgical removal of the lump or, if the cancer has started to spread, by removal of the whole breast (mastectomy). Surgery is usually followed by radiotherapy or chemotherapy. These “adjuvant” therapies are designed to kill any remaining cancer cells but can make women very ill. Generally speaking, the outlook (prognosis) for women with breast cancer is good. In the United States, for example, nearly 90% of affected women are still alive five years after their diagnosis.
Why Was This Study Done?
Because there are several types of cells in the milk ducts and glands, there are several subtypes of breast cancer. Luminal tumors, for example, begin in the cells that line the ducts and glands and usually grow slowly; basal-type tumors arise in deeper layers of the ducts and glands and tend to grow quickly. Clinicians need to distinguish between different breast cancer subtypes so that they can give women a realistic prognosis and can give adjuvant treatments to those women who are most likely to benefit. One way to distinguish between different subtypes is to stain breast cancer samples using antibodies (immune system proteins) that recognize particular proteins (antigens). This “immunohistochemical” approach can identify several breast cancer subtypes but its prognostic value and the best way to classify breast tumors remains unclear. In this study, the researchers investigate the survival over time of women with six major subtypes of breast cancer classified using five immunohistochemical markers: the estrogen receptor and the progesterone receptor (two hormone receptors expressed by luminal cells), the human epidermal growth factors receptor-2 (HER2, a protein marker used to select specific adjuvant therapies), and CK5/6 and EGFR (proteins expressed by basal cells).
What Did the Researchers Do and Find?
The researchers pooled data on survival time and on the expression of the five immunohistochemical markers from more than 10,000 cases of breast cancer from 12 studies. They then divided the tumors into six subtypes on the basis of their marker expression: luminal (hormone receptor-positive), HER2-positive tumors; luminal, HER2-negative, basal marker-positive tumors; luminal, HER2-negative, basal marker-negative tumors; nonluminal (hormone receptor-negative), HER2-positive tumors; nonluminal, HER2-negative, basal marker-positive tumors; and nonluminal, HER2-negative, basal marker-negative tumors. In the first five years after diagnosis, women with nonluminal tumor subtypes had the worst prognosis but at 15 years after diagnosis, women with luminal HER2-positive tumors had the worst prognosis. Furthermore, death rates (the percentage of affected women dying each year) differed by subtype over time. Thus, women with the two luminal HER2-negative subtypes were as likely to die soon after diagnosis as at later times whereas the death rates associated with nonluminal subtypes peaked within five years of diagnosis and then declined.
What Do These Findings Mean?
These and other findings indicate that the six subtypes of breast cancer defined by the expression of five immunohistochemical markers have distinct biological characteristics that are associated with important differences in short-term and long-term outcomes. Because different laboratories measured the immunohistochemical markers using different methods, it is possible that some of the tumors included in this study were misclassified. However, the finding of clear differences in the behavior of the immunochemically classified subtypes suggests that the use of the five markers for tumor classification might be robust enough for routine clinical practice. The application of these markers in the clinical setting, suggest the researchers, could improve the targeting of adjuvant therapies to those women most likely to benefit. Furthermore, note the researchers, these findings strongly suggest that subtype-specific responses should be evaluated in future clinical trials of treatments for breast cancer.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000279.
This study is further discussed in a PLoS Medicine Perspective by Stefan Ambs
The US National Cancer Institute provides detailed information for patients and health professionals on all aspects of breast cancer (in English and Spanish)
The American Cancer Society has a detailed guide to breast cancer, which includes information on the immunochemical classification of breast cancer subtypes
The UK charities MacMillan Cancer Support and Cancer Research UK also provide detailed information about breast cancer
The MedlinePlus Encyclopedia provides information for patients about breast cancer; Medline Plus provides links to many other breast cancer resources (in English and Spanish)
doi:10.1371/journal.pmed.1000279
PMCID: PMC2876119  PMID: 20520800
8.  Gene Expression Profiling for Guiding Adjuvant Chemotherapy Decisions in Women with Early Breast Cancer 
Executive Summary
In February 2010, the Medical Advisory Secretariat (MAS) began work on evidence-based reviews of published literature surrounding three pharmacogenomic tests. This project came about when Cancer Care Ontario (CCO) asked MAS to provide evidence-based analyses on the effectiveness and cost-effectiveness of three oncology pharmacogenomic tests currently in use in Ontario.
Evidence-based analyses have been prepared for each of these technologies. These have been completed in conjunction with internal and external stakeholders, including a Provincial Expert Panel on Pharmacogenomics (PEPP). Within the PEPP, subgroup committees were developed for each disease area. For each technology, an economic analysis was also completed by the Toronto Health Economics and Technology Assessment Collaborative (THETA) and is summarized within the reports.
The following reports can be publicly accessed at the MAS website at: www.health.gov.on.ca/mas or at www.health.gov.on.ca/english/providers/program/mas/mas_about.html
Gene Expression Profiling for Guiding Adjuvant Chemotherapy Decisions in Women with Early Breast Cancer: An Evidence-Based and Economic Analysis
Epidermal Growth Factor Receptor Mutation (EGFR) Testing for Prediction of Response to EGFR-Targeting Tyrosine Kinase Inhibitor (TKI) Drugs in Patients with Advanced Non-Small-Cell Lung Cancer: An Evidence-Based and Ecopnomic Analysis
K-RAS testing in Treatment Decisions for Advanced Colorectal Cancer: an Evidence-Based and Economic Analysis
Objective
To review and synthesize the available evidence regarding the laboratory performance, prognostic value, and predictive value of Oncotype-DX for the target population.
Clinical Need: Condition and Target Population
The target population of this review is women with newly diagnosed early stage (stage I–IIIa) invasive breast cancer that is estrogen-receptor (ER) positive and/or progesterone-receptor (PR) positive. Much of this review, however, is relevant for women with early stage (I and II) invasive breast cancer that is specifically ER positive, lymph node (LN) negative and human epidermal growth factor receptor 2 (HER-2/neu) negative. This refined population represents an estimated incident population of 3,315 new breast cancers in Ontario (according to 2007 data). Currently it is estimated that only 15% of these women will develop a distant metastasis at 10 years; however, a far great proportion currently receive adjuvant chemotherapy, suggesting that more women are being treated with chemotherapy than can benefit. There is therefore a need to develop better prognostic and predictive tools to improve the selection of women that may benefit from adjuvant chemotherapy.
Technology of Concern
The Oncotype-DX Breast Cancer Assay (Genomic Health, Redwood City, CA) quantifies gene expression for 21 genes in breast cancer tissue by performing reverse transcription polymerase chain reaction (RT-PCR) on formalin-fixed paraffin-embedded (FFPE) tumour blocks that are obtained during initial surgery (lumpectomy, mastectomy, or core biopsy) of women with early breast cancer that is newly diagnosed. The panel of 21 genes include genes associated with tumour proliferation and invasion, as well as other genes related to HER-2/neu expression, ER expression, and progesterone receptor (PR) expression.
Research Questions
What is the laboratory performance of Oncotype-DX?
How reliable is Oncotype-DX (i.e., how repeatable and reproducible is Oncotype-DX)?
How often does Oncotype-DX fail to give a useable result?
What is the prognostic value of Oncotype-DX?*
Is Oncotype-DX recurrence score associated with the risk of distant recurrence or death due to any cause in women with early breast cancer receiving tamoxifen?
What is the predictive value of Oncotype-DX?*
Does Oncoytpe-DX recurrence score predict significant benefit in terms of improvements in 10-year distant recurrence or death due to any cause for women receiving tamoxifen plus chemotherapy in comparison to women receiving tamoxifen alone?
How does Oncotype-DX compare to other known predictors of risk such as Adjuvant! Online?
How does Oncotype-DX impact patient quality of life and clinical/patient decision-making?
Research Methods
Literature Search
Search Strategy
A literature search was performed on March 19th, 2010 using OVID MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, the Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Cochrane Library, and the International Agency for Health Technology Assessment (INAHTA) for studies published from January 1st, 2006 to March 19th, 2010. A starting search date of January 1st, 2006 was because a comprehensive systematic review of Oncotype-DX was identified in preliminary literature searching. This systematic review, by Marchionni et al. (2008), included literature up to January 1st, 2007. All studies identified in the review by Marchionni et al. as well as those identified in updated literature searching were used to form the evidentiary base of this review. The quality of the overall body of evidence was identified as high, moderate, low or very low according to GRADE methodology.
Inclusion Criteria
Any observational trial, controlled clinical trial, randomized controlled trial (RCT), meta-analysis or systematic review that reported on the laboratory performance, prognostic value and/or predictive value of Oncotype-DX testing, or other outcome relevant to the Key Questions, specific to the target population was included.
Exclusion Criteria
Studies that did not report original data or original data analysis,
Studies published in a language other than English,
Studies reported only in abstract or as poster presentations (such publications were not sought nor included in this review since the MAS does not generally consider evidence that is not subject to peer review nor does the MAS consider evidence that lacks detailed description of methodology).
Outcomes of Interest
Outcomes of interest varied depending on the Key Question. For the Key Questions of prognostic and predictive value (Key Questions #2 and #3), the prospectively defined primary outcome was risk of 10-year distant recurrence. The prospectively defined secondary outcome was 10-year death due to any cause (i.e., overall survival). All additional outcomes such as risk of locoregional recurrence or disease-free survival (DFS) were not prospectively determined for this review but were reported as presented in included trials; these outcomes are referenced as tertiary outcomes in this review. Outcomes for other Key Questions (i.e., Key Questions #1, #4 and #5) were not prospectively defined due to the variability in endpoints relevant for these questions.
Summary of Findings
A total of 26 studies were included. Of these 26 studies, only five studies were relevant to the primary questions of this review (Key Questions #2 and #3). The following conclusions were drawn from the entire body of evidence:
There is a lack of external validation to support the reliability of Oncotype-DX; however, the current available evidence derived from internal industry validation studies suggests that Oncotype-DX is reliable (i.e., Oncotype-DX is repeatable and reproducible).
Current available evidence suggests a moderate failure rate of Oncotype-DX testing; however, the failure rate observed across clinical trials included in this review is likely inflated; the current Ontario experience suggests an acceptably lower rate of test failure.
In women with newly diagnosed early breast cancer (stage I–II) that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node negative:
There is low quality evidence that Oncotype-DX has prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole (the latter for postmenopausal women only),
There is very low quality evidence that Oncotype-DX can predict which women will benefit from adjuvant CMF/MF chemotherapy in women being treated with adjuvant tamoxifen.
In postmenopausal women with newly diagnosed early breast cancer that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node positive:
There is low quality evidence that Oncotype-DX has limited prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole,
There is very low quality evidence that Oncotype-DX has limited predictive value for predicting which women will benefit from adjuvant CAF chemotherapy in women who are being treated with adjuvant tamoxifen.
There are methodological and statistical limitations that affect both the generalizability of the current available evidence, as well as the magnitude and statistical strength of the observed effect sizes; in particular:
Of the major predictive trials, Oncotype-DX scores were only produced for a small subset of women (<40% of the original randomized population) potentially disabling the effects of treatment randomization and opening the possibility of selection bias;
Data is not specific to HER-2/neu-negative women;
There were limitations with multivariate statistical analyses.
Additional trials of observational design may provide further validation of the prognostic and predictive value of Oncotype-DX; however, it is unlikely that prospective or randomized data will become available in the near future due to ethical, time and resource considerations.
There is currently insufficient evidence investigating how Oncoytpe-DX compares to other known prognostic estimators of risk, such as Adjuvant! Online, and there is insufficient evidence investigating how Oncotype-DX would impact clinician/patient decision-making in a setting generalizable to Ontario.
PMCID: PMC3382301  PMID: 23074401
9.  Ki67 Index, HER2 Status, and Prognosis of Patients With Luminal B Breast Cancer 
Background
Gene expression profiling of breast cancer has identified two biologically distinct estrogen receptor (ER)-positive subtypes of breast cancer: luminal A and luminal B. Luminal B tumors have higher proliferation and poorer prognosis than luminal A tumors. In this study, we developed a clinically practical immunohistochemistry assay to distinguish luminal B from luminal A tumors and investigated its ability to separate tumors according to breast cancer recurrence-free and disease-specific survival.
Methods
Tumors from a cohort of 357 patients with invasive breast carcinomas were subtyped by gene expression profile. Hormone receptor status, HER2 status, and the Ki67 index (percentage of Ki67-positive cancer nuclei) were determined immunohistochemically. Receiver operating characteristic curves were used to determine the Ki67 cut point to distinguish luminal B from luminal A tumors. The prognostic value of the immunohistochemical assignment for breast cancer recurrence-free and disease-specific survival was investigated with an independent tissue microarray series of 4046 breast cancers by use of Kaplan–Meier curves and multivariable Cox regression.
Results
Gene expression profiling classified 101 (28%) of the 357 tumors as luminal A and 69 (19%) as luminal B. The best Ki67 index cut point to distinguish luminal B from luminal A tumors was 13.25%. In an independent cohort of 4046 patients with breast cancer, 2847 had hormone receptor–positive tumors. When HER2 immunohistochemistry and the Ki67 index were used to subtype these 2847 tumors, we classified 1530 (59%, 95% confidence interval [CI] = 57% to 61%) as luminal A, 846 (33%, 95% CI = 31% to 34%) as luminal B, and 222 (9%, 95% CI = 7% to 10%) as luminal–HER2 positive. Luminal B and luminal–HER2-positive breast cancers were statistically significantly associated with poor breast cancer recurrence-free and disease-specific survival in all adjuvant systemic treatment categories. Of particular relevance are women who received tamoxifen as their sole adjuvant systemic therapy, among whom the 10-year breast cancer–specific survival was 79% (95% CI = 76% to 83%) for luminal A, 64% (95% CI = 59% to 70%) for luminal B, and 57% (95% CI = 47% to 69%) for luminal–HER2 subtypes.
Conclusion
Expression of ER, progesterone receptor, and HER2 proteins and the Ki67 index appear to distinguish luminal A from luminal B breast cancer subtypes.
doi:10.1093/jnci/djp082
PMCID: PMC2684553  PMID: 19436038
10.  Intrinsic subtypes from PAM50 gene expression assay in a population-based breast cancer cohort: Differences by age, race, and tumor characteristics 
Background
Data are lacking to describe gene expression-based breast cancer intrinsic subtype patterns for population-based patient groups.
Methods
We studied a diverse cohort of women with breast cancer from the Life After Cancer Epidemiology (LACE) and Pathways studies. RNA was extracted from 1 mm punches from fixed tumor tissue. Quantitative reverse-transcriptase polymerase chain reaction (RT-qPCR) was conducted for the 50 genes that comprise the PAM50 intrinsic subtype classifier.
Results
In a subcohort of 1,319 women, the overall subtype distribution based on PAM50 was 53.1% Luminal A, 20.5% Luminal B, 13.0% HER2-enriched, 9.8% Basal-like, and 3.6% Normal-like. Among low-risk endocrine positive tumors (i.e. estrogen and progesterone receptor positive by immunohistochemistry, Her2 negative, and low histologic grade), only 76.5% were categorized as Luminal A by PAM50. Continuous-scale Luminal A, Luminal B, HER2-enriched, and Normal-like scores from PAM50 were mutually positively correlated; Basal-like score was inversely correlated with other subtypes. The proportion with non-Luminal A subtype decreased with older age at diagnosis, p trend < 0.0001. Compared with non-Hispanic whites, African-American women were more likely to have Basal-like tumors, age-adjusted odds ratio (OR) 4.4 (95% CI 2.3,8.4), whereas Asian and Pacific Islander women had reduced odds of Basal-like subtype, OR 0.5 (95% CI 0.3,0.9).
Conclusions
Our data indicate that over 50% of breast cancers treated in the community have Luminal A subtype. Gene expression-based classification shifted some tumors categorized as low risk by surrogate clinicopathological criteria to higher-risk subtypes.
Impact
Subtyping in a population-based cohort revealed distinct profiles by age and race.
doi:10.1158/1055-9965.EPI-13-1023
PMCID: PMC4011983  PMID: 24521995
breast neoplasms; cohort studies; intrinsic subtypes; PAM50
11.  Molecular characterisation of formalin-fixed paraffin-embedded (FFPE) breast tumour specimens using a custom 512-gene breast cancer bead array-based platform 
British Journal of Cancer  2011;105(10):1574-1581.
Background:
Formalin-fixed, paraffin-embedded (FFPE) tumour tissue represents an immense but mainly untapped resource with respect to molecular profiling. The DASL (cDNA-mediated Annealing, Selection, extension, and Ligation) assay is a recently described, RT–PCR-based, highly multiplexed high-throughput gene expression platform developed by Illumina specifically for fragmented RNA typically obtained from FFPE specimens, which enables expression profiling. In order to extend the utility of the DASL assay for breast cancer, we have custom designed and validated a 512-gene human breast cancer panel.
Methods:
The RNA from FFPE breast tumour specimens were analysed using the DASL assay. Breast cancer subtype was defined from pathology immunohistochemical (IHC) staining. Differentially expressed genes between the IHC-defined subtypes were assessed by prediction analysis of microarrays (PAM) and then used in the analysis of two published data sets with clinical outcome data.
Results:
Gene expression signatures on our custom breast cancer panel were very reproducible between replicates (average Pearson's R2=0.962) and the 152 genes common to both the standard cancer DASL panel (Illumina) and our breast cancer DASL panel were similarly expressed for samples run on both panels (average R2=0.877). Moreover, expression of ESR1, PGR and ERBB2 corresponded well with their respective pathology-defined IHC status. A 30-gene set indicative of IHC-defined breast cancer subtypes was found to segregate samples based on their subtype in our data sets and published data sets. Furthermore, several of these genes were significantly associated with overall survival (OS) and relapse-free survival (RFS) in these previously published data sets, indicating that they are biomarkers of the different breast cancer subtypes and the prognostic outcomes associated with these subtypes.
Conclusion:
We have demonstrated the ability to expression profile degraded RNA transcripts derived from FFPE tissues on the DASL platform. Importantly, we have identified a 30-biomarker gene set that can classify breast cancer into subtypes and have shown that a subset of these markers is prognostic of OS and RFS.
doi:10.1038/bjc.2011.355
PMCID: PMC3242517  PMID: 22067903
breast cancer; DASL assay; bead array; formalin-fixed, paraffin-embedded (FFPE); relapse-free survival (RFS); overall survival (OS)
12.  Diagnosis of Basal-Like Breast Cancer Using a FOXC1-Based Assay 
Background:
Diagnosis of basal-like breast cancer (BLBC) remains a bottleneck to conducting effective clinical trials for this aggressive subtype. We postulated that elevated expression of Forkhead Box transcription factor C1 (FOXC1) is a simple and accurate diagnostic biomarker for BLBC.
Methods:
Accuracy of FOXC1 expression in identifying BLBC was compared with the PAM50 gene expression panel in gene expression microarray (GEM) (n = 1992) and quantitative real-time polymerase chain reaction (qRT-PCR) (n = 349) datasets. A FOXC1-based immunohistochemical (IHC) assay was developed and assessed in 96 archival formalin-fixed, paraffin-embedded (FFPE) breast cancer samples that also underwent PAM50 profiling. All statistical tests were two-sided.
Results:
A FOXC1-based two-tier assay (IHC +/- qRT-PCR) accurately identified BLBC (AUC = 0.88) in an independent cohort of FFPE samples, validating the accuracy of FOXC1-defined BLBC in GEM (AUC = 0.90) and qRT-PCR (AUC = 0.88) studies, when compared with platform-specific PAM50-defined BLBC. The hazard ratio (HR) for disease-specific survival in patients having FOXC1-defined BLBC was 1.71 (95% CI = 1.31 to 2.23, P < .001), comparable to PAM50 assay-defined BLBC (HR = 1.74, 95% CI = 1.40 to 2.17, P < .001). FOXC1 expression also predicted the development of brain metastasis. Importantly, unlike triple-negative or Core Basal IHC definitions, a FOXC1-based definition is able to identify BLBC in both ER+ and HER2+ patients.
Conclusion:
A FOXC1-based two-tier assay, by virtue of being rapid, simple, accurate, and cost-effective may emerge as the diagnostic assay of choice for BLBC. Such a test could substantially improve clinical trial enrichment of BLBC patients and accelerate the identification of effective chemotherapeutic options for this aggressive disease.
doi:10.1093/jnci/djv148
PMCID: PMC4554196  PMID: 26041837
13.  Molecular subtype and tumor characteristics of breast cancer metastases as assessed by gene expression significantly influence patient post-relapse survival 
Annals of Oncology  2014;26(1):81-88.
An enhanced understanding of the biology of breast cancer metastases is needed to individualize patient management. Here, we show that tumor characteristics of breast cancer metastases significantly influence post-relapse survival, emphasizing that molecular investigation at relapse offers clinically relevant information, with the potential to improve patient management and survival.
Background
We and others have recently shown that tumor characteristics are altered throughout tumor progression. These findings emphasize the need for re-examination of tumor characteristics at relapse and have led to recommendations from ESMO and the Swedish Breast Cancer group. Here, we aim to determine whether tumor characteristics and molecular subtypes in breast cancer metastases confer clinically relevant prognostic information for patients.
Patients and methods
The translational aspect of the Swedish multicenter randomized trial called TEX included 111 patients with at least one biopsy from a morphologically confirmed locoregional or distant breast cancer metastasis diagnosed from December 2002 until June 2007. All patients had detailed clinical information, complete follow-up, and metastasis gene expression information (Affymetrix array GPL10379). We assessed the previously published gene expression modules describing biological processes [proliferation, apoptosis, human epidermal receptor 2 (HER2) and estrogen (ER) signaling, tumor invasion, immune response, and angiogenesis] and pathways (Ras, MAPK, PTEN, AKT-MTOR, PI3KCA, IGF1, Src, Myc, E2F3, and β-catenin) and the intrinsic subtypes (PAM50). Furthermore, by contrasting genes expressed in the metastases in relation to survival, we derived a poor metastasis survival signature.
Results
A significant reduction in post-relapse breast cancer-specific survival was associated with low-ER receptor signaling and apoptosis gene module scores, and high AKT-MTOR, Ras, and β-catenin module scores. Similarly, intrinsic subtyping of the metastases provided statistically significant post-relapse survival information with the worst survival outcome in the basal-like [hazard ratio (HR) 3.7; 95% confidence interval (CI) 1.3–10.9] and HER2-enriched (HR 4.4; 95% CI 1.5–12.8) subtypes compared with the luminal A subtype. Overall, 25% of the metastases were basal-like, 32% HER2-enriched, 10% luminal A, 28% luminal B, and 5% normal-like.
Conclusions
We show that tumor characteristics and molecular subtypes of breast cancer metastases significantly influence post-relapse patient survival, emphasizing that molecular investigations at relapse provide prognostic and clinically relevant information.
ClinicalTrials.gov
This is the translational part of the Swedish multicenter and randomized trial TEX, clinicaltrials.gov identifier nct01433614 (http://www.clinicaltrials.gov/ct2/show/nct01433614).
doi:10.1093/annonc/mdu498
PMCID: PMC4269343  PMID: 25361981
breast cancer metastases; metastasis characteristics; TEX randomized trial; gene expression; gene modules; biopsy at relapse
14.  Prognostic Significance of Progesterone Receptor–Positive Tumor Cells Within Immunohistochemically Defined Luminal A Breast Cancer 
Journal of Clinical Oncology  2012;31(2):203-209.
Purpose
Current immunohistochemical (IHC)-based definitions of luminal A and B breast cancers are imperfect when compared with multigene expression-based assays. In this study, we sought to improve the IHC subtyping by examining the pathologic and gene expression characteristics of genomically defined luminal A and B subtypes.
Patients and Methods
Gene expression and pathologic features were collected from primary tumors across five independent cohorts: British Columbia Cancer Agency (BCCA) tamoxifen-treated only, Grupo Español de Investigación en Cáncer de Mama 9906 trial, BCCA no systemic treatment cohort, PAM50 microarray training data set, and a combined publicly available microarray data set. Optimal cutoffs of percentage of progesterone receptor (PR) –positive tumor cells to predict survival were derived and independently tested. Multivariable Cox models were used to test the prognostic significance.
Results
Clinicopathologic comparisons among luminal A and B subtypes consistently identified higher rates of PR positivity, human epidermal growth factor receptor 2 (HER2) negativity, and histologic grade 1 in luminal A tumors. Quantitative PR gene and protein expression were also found to be significantly higher in luminal A tumors. An empiric cutoff of more than 20% of PR-positive tumor cells was statistically chosen and proved significant for predicting survival differences within IHC-defined luminal A tumors independently of endocrine therapy administration. Finally, no additional prognostic value within hormonal receptor (HR) –positive/HER2-negative disease was observed with the use of the IHC4 score when intrinsic IHC-based subtypes were used that included the more than 20% PR-positive tumor cells and vice versa.
Conclusion
Semiquantitative IHC expression of PR adds prognostic value within the current IHC-based luminal A definition by improving the identification of good outcome breast cancers. The new proposed IHC-based definition of luminal A tumors is HR positive/HER2 negative/Ki-67 less than 14%, and PR more than 20%.
doi:10.1200/JCO.2012.43.4134
PMCID: PMC3532392  PMID: 23233704
15.  ELF5 Suppresses Estrogen Sensitivity and Underpins the Acquisition of Antiestrogen Resistance in Luminal Breast Cancer 
PLoS Biology  2012;10(12):e1001461.
The transcription factor ELF5 is responsible for gene expression patterning underlying molecular subtypes of breast cancer and may mediate acquired resistance to anti-estrogen therapy.
We have previously shown that during pregnancy the E-twenty-six (ETS) transcription factor ELF5 directs the differentiation of mammary progenitor cells toward the estrogen receptor (ER)-negative and milk producing cell lineage, raising the possibility that ELF5 may suppress the estrogen sensitivity of breast cancers. To test this we constructed inducible models of ELF5 expression in ER positive luminal breast cancer cells and interrogated them using transcript profiling and chromatin immunoprecipitation of DNA followed by DNA sequencing (ChIP-Seq). ELF5 suppressed ER and FOXA1 expression and broadly suppressed ER-driven patterns of gene expression including sets of genes distinguishing the luminal molecular subtype. Direct transcriptional targets of ELF5, which included FOXA1, EGFR, and MYC, accurately classified a large cohort of breast cancers into their intrinsic molecular subtypes, predicted ER status with high precision, and defined groups with differential prognosis. Knockdown of ELF5 in basal breast cancer cell lines suppressed basal patterns of gene expression and produced a shift in molecular subtype toward the claudin-low and normal-like groups. Luminal breast cancer cells that acquired resistance to the antiestrogen Tamoxifen showed greatly elevated levels of ELF5 and its transcriptional signature, and became dependent on ELF5 for proliferation, compared to the parental cells. Thus ELF5 provides a key transcriptional determinant of breast cancer molecular subtype by suppression of estrogen sensitivity in luminal breast cancer cells and promotion of basal characteristics in basal breast cancer cells, an action that may be utilised to acquire antiestrogen resistance.
Author Summary
The molecular subtypes of breast cancer are distinguished by their intrinsic patterns of gene expression and can be used to group patients with different prognoses and treatment options. Although molecular subtyping tests are currently under evaluation, some of them are already in use to better tailor therapy for patients; however, the molecular events that are responsible for these different patterns of gene expression in breast cancer are largely undefined. The elucidation of their mechanistic basis would improve our understanding of the disease process and enhance the chances of developing better predictive and prognostic markers, new therapies, and interventions to overcome resistance to existing therapies. Here, we show that the transcription factor ELF5 is responsible for much of the patterning of gene expression that distinguishes the breast cancer subtypes. Additionally, our data suggest that ELF5 may also be involved in the development of resistance to therapies designed to stop estrogen stimulation of breast cancer. These effects of ELF5 appear to represent a partial carryover into breast cancer of its normal role in the mammary gland, where it is responsible for the development of milk-producing structures during pregnancy.
doi:10.1371/journal.pbio.1001461
PMCID: PMC3531499  PMID: 23300383
16.  Association of high obesity with PAM50 breast cancer intrinsic subtypes and gene expression 
BMC Cancer  2015;15:278.
Background
Invasive breast cancers are now commonly classified using gene expression into biologically and clinically distinct tumor subtypes. However, the role of obesity in breast tumor gene expression and intrinsic subtype is unknown.
Methods
Early-stage breast cancer (BC) patients (n = 1,676) were sampled from two prospective cohorts. The PAM50 qRT-PCR assay was used to: a) assess tumor gene expression levels for ESR1, PGR, ERBB2, and 10 proliferation genes and b) classify tumors into intrinsic subtype (Luminal A, Luminal B, Basal-like, HER2-enriched, Normal-like). Body mass index (BMI) around BC diagnosis (kg/m2) was categorized as: underweight (<18.5), normal (18.5-24), overweight (25–29), mildly obese (30–34), and highly obese (≥35). In a cross-sectional analysis, we evaluated associations of BMI with gene expression using linear regression models, and associations of BMI with non-Luminal A intrinsic subtypes, compared with Luminal A subtype, using multinomial logistic regression. Statistical significance tests were two-sided.
Results
Highly obese women had tumors with higher expression of proliferation genes compared with normal weight women (adjusted mean difference = 0.44; 95% CI: 0.18, 0.71), yet mildly obese (adjusted mean difference = 0.16; 95% CI: −0.06, 0.38) and overweight (adjusted mean difference = 0.18; 95% CI: −0.01, 0.36) women did not. This association was stronger in postmenopausal women (p for interaction = 0.06). Being highly obese, however, was inversely associated with ESR1 expression (adjusted mean difference = −0.95; 95% CI: −1.47, −0.42) compared with being normal weight, whereas being mildly obese and overweight were not. In addition, women with Basal-like and Luminal B subtypes, relative to those with Luminal A subtype, were more likely to be highly obese, compared with normal-weight.
Conclusions
ER expression may not increase correspondingly with increasing degree of obesity. Highly obese patients are more likely to have tumor subtypes associated with high proliferation and poorer prognosis.
Electronic supplementary material
The online version of this article (doi:10.1186/s12885-015-1263-4) contains supplementary material, which is available to authorized users.
doi:10.1186/s12885-015-1263-4
PMCID: PMC4403771  PMID: 25884832
Breast cancer; Obesity; Body mass index; PAM50 intrinsic subtype classifier; Tumor subtype; Gene expression; ESR1; PGR; ERBB2; Proliferation
17.  Age-Specific Changes in Intrinsic Breast Cancer Subtypes: A Focus on Older Women 
The Oncologist  2014;19(10):1076-1083.
The PAM50 algorithm was used to analyze data from publicly available clinical and gene expression microarray data sets. The association of age and tumor subtype with survival was assessed. More favorable breast cancer subtypes increase with age, but older patients still have a substantial percentage of high-risk tumor subtypes. After controlling for subtype, treatment, tumor size, nodal status, and grade, increasing age had no impact on survival.
Purpose.
Breast cancer (BC) is a disease of aging and the number of older BC patients in the U.S. is rising. Immunohistochemical data show that with increasing age, the incidence of hormone receptor-positive tumors increases, whereas the incidence of triple-negative tumors decreases. Few data exist on the frequency of molecular subtypes in older women. Here, we characterize the incidence and outcomes of BC patients by molecular subtypes and age.
Patients and Methods.
Data from 3,947 patients were pooled from publicly available clinical and gene expression microarray data sets. The PAM50 algorithm was used to classify tumors into five BC intrinsic subtypes: luminal A, luminal B, HER2-enriched, basal-like, and normal-like. The association of age and subtype with recurrence-free survival (RFS), overall survival, and disease-specific survival (DSS) was assessed.
Results.
The incidence of luminal (A, B, and A+B) tumors increased with age (p < .01, p < .0001, and p < .0001, respectively), whereas the percentage of basal-like tumors decreased (p < .0001). Among patients 70 years and older, luminal B, HER2-enriched, and basal-like tumors were found at a frequency of 32%, 11%, and 9%, respectively. In older women, luminal subtypes had better outcomes than basal-like and HER2-enriched subtypes. After controlling for subtype, treatment, tumor size, nodal status, and grade, increasing age had no impact on RFS or DSS.
Conclusion.
More favorable BC subtypes increase with age, but older patients still have a substantial percentage of high-risk tumor subtypes. After accounting for tumor subtypes, age at diagnosis is not an independent prognostic factor for outcome.
doi:10.1634/theoncologist.2014-0184
PMCID: PMC4200998  PMID: 25142841
Gene microarray; Breast cancer; Age; Elderly
18.  Yes-associated protein (YAP) is differentially expressed in tumor and stroma according to the molecular subtype of breast cancer 
In this study, we aimed to clarify the expression profiles of Yes-associated protein (YAP) and phosphorylated YAP (pYAP) protein and to verify the clinical implication of the expression of YAP protein in human breast cancer. We selected 678 cases of formalin-fixed paraffin-embedded (FFPE) breast cancer tissue to construct tissue microarray (TMA) blocks. We performed immunohistochemical staining of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth receptor-2 (HER-2) and Ki-67 and fluorescent in situ hybridization (FISH) assay for HER-2 on the TMA sections and divided breast cancers into molecular subtypes: luminal A, luminal B, HER-2, triple negative breast cancer (TNBC). Then, we examined YAP and pYAP expression status using immunohistochemical analysis according to the molecular subtypes of breast cancer. We found that HER-2 type breast cancer demonstrated elevated expression level in tumoral cytoplasmic YAP (P = 0.011) and pYAP (P = 0.049). Expressions of stromal YAP (P = 0.002) and pYAP (P < 0.001) were higher in luminal B and HER-2 type breast cancer but lower in TNBC. In univariate analysis, nuclear YAP expression of tumor cells was associated with shorter overall survival (OS) (P = 0.024). Cytoplasmic YAP expression of HER-2 type breast cancer cells negatively affected disease-free survival (DFS) (P = 0.034). In conclusion, we concluded that there was a significant difference in YAP and pYAP expression status according to molecular subtypes and tumoral and cellular components of breast cancers. Finally, we found that nuclear and cytoplasmic YAP expression could be a prognostic marker for breast cancer patients.
PMCID: PMC4097213  PMID: 25031743
Breast cancer; molecular subtype; YAP
19.  Prognostic ability of EndoPredict compared to research-based versions of the PAM50 risk of recurrence (ROR) scores in node-positive, estrogen receptor-positive, and HER2-negative breast cancer. A GEICAM/9906 sub-study 
There are several prognostic multigene-based tests for managing breast cancer (BC), but limited data comparing them in the same cohort. We compared the prognostic performance of the EndoPredict (EP) test (standardized for pathology laboratory) with the research-based PAM50 non-standardized qRT-PCR assay in node-positive estrogen receptor-positive (ER+) and HER2-negative (HER2−) BC patients receiving adjuvant chemotherapy followed by endocrine therapy (ET) in the GEICAM/9906 trial. EP and PAM50 risk of recurrence (ROR) scores [based on subtype (ROR-S) and on subtype and proliferation (ROR-P)] were compared in 536 ER+/HER2− patients. Scores combined with clinical information were evaluated: ROR-T (ROR-S, tumor size), ROR-PT (ROR-P, tumor size), and EPclin (EP, tumor size, nodal status). Patients were assigned to risk-categories according to prespecified cutoffs. Distant metastasis-free survival (MFS) was analyzed by Kaplan–Meier. ROR-S, ROR-P, and EP scores identified a low-risk group with a relative better outcome (10-year MFS: ROR-S 87 %; ROR-P 89 %; EP 93 %). There was no significant difference between tests. Predictors including clinical information showed superior prognostic performance compared to molecular scores alone (10-year MFS, low-risk group: ROR-T 88 %; ROR-PT 92 %; EPclin 100 %). The EPclin-based risk stratification achieved a significantly improved prediction of MFS compared to ROR-T, but not ROR-PT. All signatures added prognostic information to common clinical parameters. EPclin provided independent prognostic information beyond ROR-T and ROR-PT. ROR and EP can reliably predict risk of distant metastasis in node-positive ER+/HER2− BC patients treated with chemotherapy and ET. Addition of clinical parameters into risk scores improves their prognostic ability.
Electronic supplementary material
The online version of this article (doi:10.1007/s10549-016-3725-z) contains supplementary material, which is available to authorized users.
doi:10.1007/s10549-016-3725-z
PMCID: PMC4788691  PMID: 26909792
Breast cancer; PAM50; EndoPredict; Chemotherapy; Prognosis
20.  Agreement in Risk Prediction Between the 21-Gene Recurrence Score Assay (Oncotype DX®) and the PAM50 Breast Cancer Intrinsic Classifier™ in Early-Stage Estrogen Receptor–Positive Breast Cancer 
The Oncologist  2012;17(4):492-498.
Risk assignment in breast cancer patients using the PAM50 Breast Cancer Intrinsic Classifier™ and the Oncotype DX® Recurrence Score in the same population was compared. There is good agreement between the two assays for high and low prognostic risk assignment but PAM50 assigns more patients to the low risk category. About half of the intermediate risk RS group was reclassified as low risk luminal A by PAM50, which suggests a potential complementary use for the assays.
Purpose.
To compare risk assignment by PAM50 Breast Cancer Intrinsic Classifier™ and Oncotype DX_Recurrence Score (RS) in the same population.
Methods.
RNA was extracted from 151 estrogen receptor (ER)+ stage I–II breast cancers and gene expression profiled using PAM50 “intrinsic” subtyping test.
Results.
One hundred eight cases had complete molecular information; 103 (95%) were classified as luminal A (n = 76) or luminal B (n = 27). Ninety-two percent (n = 98) had a low (n = 59) or intermediate (n = 39) RS. Among luminal A cancers, 70% had low (n = 53) and the remainder (n = 23) had an intermediate RS. Among luminal B cancers, nine were high (33%) and 13 were intermediate (48%) by the RS. Almost all cancers with a high RS were classified as luminal B (90%, n = 9). One high RS cancer was identified as basal-like and had low ER/ESR1 and low human epidermal growth factor receptor 2 (HER2) expression by quantitative polymerase chain reaction in both assays. The majority of low RS cases were luminal A (83%, n = 53). Importantly, half of the intermediate RS cancers were re-categorized as low risk luminal A subtype by PAM50.
Conclusion.
There is good agreement between the two assays for high (i.e., luminal B or RS > 31) and low (i.e., luminal B or RS < 18) prognostic risk assignment but PAM50 assigns more patients to the low risk category. About half of the intermediate RS group was reclassified as luminal A by PAM50.
doi:10.1634/theoncologist.2012-0007
PMCID: PMC3336833  PMID: 22418568
Oncotype DX®; PAM50 assay; Gene expression profiles; Breast cancer; Prognosis
21.  Expression and methylation patterns partition luminal-A breast tumors into distinct prognostic subgroups 
Background
Breast cancer is a heterogeneous disease comprising several biologically different types, exhibiting diverse responses to treatment. In the past years, gene expression profiling has led to definition of several “intrinsic subtypes” of breast cancer (basal-like, HER2-enriched, luminal-A, luminal-B and normal-like), and microarray based predictors such as PAM50 have been developed. Despite their advantage over traditional histopathological classification, precise identification of breast cancer subtypes, especially within the largest and highly variable luminal-A class, remains a challenge. In this study, we revisited the molecular classification of breast tumors using both expression and methylation data obtained from The Cancer Genome Atlas (TCGA).
Methods
Unsupervised clustering was applied on 1148 and 679 breast cancer samples using RNA-Seq and DNA methylation data, respectively. Clusters were evaluated using clinical information and by comparison to PAM50 subtypes. Differentially expressed genes and differentially methylated CpGs were tested for enrichment using various annotation sets. Survival analysis was conducted on the identified clusters using the log-rank test and Cox proportional hazards model.
Results
The clusters in both expression and methylation datasets had only moderate agreement with PAM50 calls, while our partitioning of the luminal samples had better five-year prognostic value than the luminal-A/luminal-B assignment as called by PAM50. Our analysis partitioned the expression profiles of the luminal-A samples into two biologically distinct subgroups exhibiting differential expression of immune-related genes, with one subgroup carrying significantly higher risk for five-year recurrence. Analysis of the luminal-A samples using methylation data identified a cluster of patients with poorer survival, characterized by distinct hyper-methylation of developmental genes. Cox multivariate survival analysis confirmed the prognostic significance of the two partitions after adjustment for commonly used factors such as age and pathological stage.
Conclusions
Modern genomic datasets reveal large heterogeneity among luminal breast tumors. Our analysis of these data provides two prognostic gene sets that dissect and explain tumor variability within the luminal-A subgroup, thus, contributing to the advancement of subtype-specific diagnosis and treatment.
Electronic supplementary material
The online version of this article (doi:10.1186/s13058-016-0724-2) contains supplementary material, which is available to authorized users.
doi:10.1186/s13058-016-0724-2
PMCID: PMC4936004  PMID: 27386846
Breast cancer subtypes; Luminal-A; Unsupervised analysis; Clustering; RNA-Seq; DNA methylation
22.  Impact of intrinsic subtype on predicting axillary lymph node metastasis in breast cancer 
Oncology Letters  2014;8(4):1707-1712.
Axillary lymph node (LN) metastasis is one of the most important prognostic factors for the survival of breast cancer. The correlation between LN metastasis and the tumor (T) category has previously been investigated in certain case series. At present, the initial treatment approach is to define the intrinsic subtype, as it is significant in determining medical treatments, as well as being a prognostic factor. However, the intrinsic subtype is not known to predict the frequency of LN metastasis. The aim of the present study was to evaluate the frequency of LN metastasis with regard to tumor size according to the intrinsic subtype. In total, 654 patients with primary breast cancer were evaluated who underwent surgical resection between 2010 and 2011 at the Aichi Cancer Center Hospital (Nagoya, Aichi). The clinical and pathological data were analyzed for patients who underwent an axillary LN dissection or a sentinel LN biopsy for primary breast cancer. The intrinsic subtype of the primary tumors was classified using immunohistochemical staining of thin, paraffin-embedded sections. In total, 157 (24.0%) of the 654 patients exhibited LN metastasis, and according to the primary tumor category, a larger tumor size was found to correlate with a higher proportion of LN positivity, as well as with the luminal A subtypes (n=364). In luminal B subtypes (n=110), T1a (n=2), T1b (n=12), T1c (n=55), T2 (n=34), and T3 (n=2) exhibited 50, 8.3, 38.2, 55.9 and 50% LN positivity, respectively. In luminal-human epidermal growth factor receptor 2 (HER2) subtypes (n=46), T1c (n=17), T2 (n=10), and T3 (n=1) exhibited 40.1, 60 and 100% LN positivity, respectively. In HER2 subtypes (n=53), T1a (n=6), T1b (n=4), T1c (n=15), and T2 (n=10) exhibited 16.7, 25, 46.7 and 60% LN positivity, respectively. In triple-negative subtypes (n=81), T1b (n=15), T1c (n=29), T2 (n=20), and T3 (n=2) exhibited 26.7, 24.1, 50 and 50% LN positivity, respectively. In conclusion, the intrinsic subtype is significant in predicting the frequency of LN metastasis with regard to tumor size.
doi:10.3892/ol.2014.2333
PMCID: PMC4156270  PMID: 25202396
breast cancer; intrinsic subtype; lymph node metastasis; tumor size
23.  Improvement of the clinical applicability of the Genomic Grade Index through a qRT-PCR test performed on frozen and formalin-fixed paraffin-embedded tissues 
BMC Genomics  2009;10:424.
Background
Proliferation and tumor differentiation captured by the genomic grade index (GGI) are important prognostic indicators in breast cancer (BC) especially for the estrogen receptor positive (ER+) disease. The aims of this study were to convert this microarray index to a qRT-PCR assay (PCR-GGI), which could be realized on formalin fixed paraffin embedded samples (FFPE), and to assess its prognostic performance and predictive value of clinical benefit in early and advanced ER+ BC patients treated with tamoxifen.
Methods
The accuracy and concordance of the PCR-GGI with the GGI was assessed using BC patients for which frozen and FFPE tissues as well as microarray data were available (n = 19). The evaluation of the prognostic value of the PCR-GGI was assessed on FFPE material using a consecutive series of 212 systemically treated early BC patients. The predictive performance for tamoxifen benefit was assessed using two ER+ BC populations treated either with adjuvant tamoxifen only (n = 77+139) or first-line tamoxifen for advanced disease (n = 270).
Results
The PCR-GGI is based on the expression of 8 genes (4 representative of the GGI and 4 reference genes). A significant correlation was observed between the microarray-derived GGI and the qRT-PCR assay using frozen (ρ = 0.95, p < 10E-06) and FFPE material (ρ = 0.89, p < 10E-06). The prognostic performance of the PCR-GGI was confirmed on FFPE samples (HRunivar. = 1.89; [95CI:1.01-3.54], p = 0.05). The PCR-GGI further identified two subgroups of patients with statistically different time to distant metastasis free survival (DMFS) across the two cohorts of ER+ BC patients treated with adjuvant tamoxifen. Additionally, the PCR-GGI was associated with response to tamoxifen in the advanced setting (HRunivar. = 1.98; [95CI:1.51-2.59], p = 6.9E-07).
Conclusion
PCR-GGI recapitulates in an accurate and reproducible manner the performances of the GGI using frozen and FFPE samples.
doi:10.1186/1471-2164-10-424
PMCID: PMC2756282  PMID: 19744330
24.  Response and survival of breast cancer intrinsic subtypes following multi-agent neoadjuvant chemotherapy 
BMC Medicine  2015;13:303.
Background
Predicting treatment benefit and/or outcome before any therapeutic intervention has taken place would be clinically very useful. Herein, we evaluate the ability of the intrinsic subtypes and the risk of relapse score at diagnosis to predict survival and response following neoadjuvant chemotherapy. In addition, we evaluated the ability of the Claudin-low and 7-TNBCtype classifications to predict response within triple-negative breast cancer (TNBC).
Methods
Gene expression and clinical-pathological data were evaluated in a combined dataset of 957 breast cancer patients, including 350 with TNBC, treated with sequential anthracycline and anti-microtubule-based neoadjuvant regimens. Intrinsic subtype, risk of relapse score based on subtype and proliferation (ROR-P), the Claudin-low subtype and the 7-TNBCtype subtype classification were evaluated. Logistic regression models for pathological complete response (pCR) and Cox models for distant relapse-free survival (DRFS) were used.
Results
Basal-like, Luminal A, Luminal B, and HER2-enriched subtypes represented 32.7 %, 30.6 %, 18.2 %, and 10.3 % of cases, respectively. Intrinsic subtype was independently associated with pCR in all patients, in hormone receptor-positive/HER2-negative disease, in HER2-positive disease, and in TNBC. The pCR rate of Basal-like disease was >35 % across all clinical cohorts. Neither the Claudin-low nor the 7-TNBCtype subtype classifications predicted pCR within TNBCs after accounting for intrinsic subtype. Finally, intrinsic subtype and ROR-P provided independent prognostic information beyond clinicopathological variables and type of pathological response. A 5-year DRFS of 97.5 % (92.8–100.0 %) was observed in these neoadjuvant-treated and clinically node-negative patients predicted to be low risk by ROR-P (i.e. 57.4 % of Luminal A tumors with clinically node-negative disease).
Conclusions
Intrinsic subtyping at diagnosis provides prognostic and predictive information for patients receiving neoadjuvant chemotherapy. Although we could not exclude a survival benefit of neoadjuvant chemotherapy in patients with early breast cancer with clinically node-negative and ROR-low disease at diagnosis, the absolute benefit of cytotoxic therapy in this group might be rather small (if any).
Electronic supplementary material
The online version of this article (doi:10.1186/s12916-015-0540-z) contains supplementary material, which is available to authorized users.
doi:10.1186/s12916-015-0540-z
PMCID: PMC4683815  PMID: 26684470
Biomarker; Breast cancer; Gene expression; Intrinsic subtypes; Triple-negative
25.  Molecular risk assessment of BIG 1-98 participants by expression profiling using RNA from archival tissue 
BMC Cancer  2010;10:37.
Background
The purpose of the work reported here is to test reliable molecular profiles using routinely processed formalin-fixed paraffin-embedded (FFPE) tissues from participants of the clinical trial BIG 1-98 with a median follow-up of 60 months.
Methods
RNA from fresh frozen (FF) and FFPE tumor samples of 82 patients were used for quality control, and independent FFPE tissues of 342 postmenopausal participants of BIG 1-98 with ER-positive cancer were analyzed by measuring prospectively selected genes and computing scores representing the functions of the estrogen receptor (eight genes, ER_8), the progesterone receptor (five genes, PGR_5), Her2 (two genes, HER2_2), and proliferation (ten genes, PRO_10) by quantitative reverse transcription PCR (qRT-PCR) on TaqMan Low Density Arrays. Molecular scores were computed for each category and ER_8, PGR_5, HER2_2, and PRO_10 scores were combined into a RISK_25 score.
Results
Pearson correlation coefficients between FF- and FFPE-derived scores were at least 0.94 and high concordance was observed between molecular scores and immunohistochemical data. The HER2_2, PGR_5, PRO_10 and RISK_25 scores were significant predictors of disease free-survival (DFS) in univariate Cox proportional hazard regression. PRO_10 and RISK_25 scores predicted DFS in patients with histological grade II breast cancer and in lymph node positive disease. The PRO_10 and PGR_5 scores were independent predictors of DFS in multivariate Cox regression models incorporating clinical risk indicators; PRO_10 outperformed Ki-67 labeling index in multivariate Cox proportional hazard analyses.
Conclusions
Scores representing the endocrine responsiveness and proliferation status of breast cancers were developed from gene expression analyses based on RNA derived from FFPE tissues. The validation of the molecular scores with tumor samples of participants of the BIG 1-98 trial demonstrates that such scores can serve as independent prognostic factors to estimate disease free survival (DFS) in postmenopausal patients with estrogen receptor positive breast cancer.
Trial Registration
Current Controlled Trials: NCT00004205
doi:10.1186/1471-2407-10-37
PMCID: PMC2829498  PMID: 20144231

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