The molecular portraits of breast tumors are conserved across microarray platforms

Bimodal gene expression patterns in breast cancer

We identified a set of genes with an unexpected bimodal distribution among breast cancer patients in multiple studies. The property of bimodality seems to be common, as these genes were found on multiple microarray platforms and in studies with different end-points and patient cohorts. Bimodal genes tend to cluster into small groups of four to six genes with synchronised expression within the group (but not between the groups), which makes them good candidates for robust conditional descriptors. The groups tend to form concise network modules underlying their function in cancerogenesis of breast neoplasms.

Histological and molecular types of breast cancer: is there a unifying taxonomy?

Breast cancer is a complex and heterogeneous disease, comprising multiple tumor entities associated with distinctive histological patterns and different biological features and clinical behaviors. Microarray-based high-throughput technologies have been employed to unravel the molecular characteristics of breast cancer, including its proclivity to disseminate to distant sites, and the molecular basis for histological grade. In addition, a breast cancer molecular taxonomy based solely on transcriptomic analysis has been proposed. Most microarray studies have focused on invasive ductal carcinomas of no special type, neglecting the important information about the biology and clinical behavior of breast cancers conveyed by histological type. Histological special types of breast cancer account for up to 25% of all invasive breast cancers. The histopathological characteristics of these cancers might be driven by specific genetic alterations, providing direct evidence for genotypic-phenotypic correlations between morphological patterns and molecular changes in breast cancer. We review the historical aspects of breast cancer taxonomy, discuss the possible origins of the diversity of breast cancer and propose an approach for the identification of novel therapeutic targets on the basis of histological special types of breast cancer.

Cytokeratin 19-positive circulating tumor cells in early breast cancer prognosis

In spite of the heterogeneity of breast cancer at the molecular level, circulating tumor cells (CTCs) may provide a novel prognostic marker. Approximately 20–40% of early breast cancer patients have detectable CTCs using reverse transcription PCR for CK19. The detection of CTCs before adjuvant chemotherapy or during tamoxifen administration has been demonstrated to be an independent adverse prognostic factor in women with early-stage breast cancer. The prognostic value of CTC detection is of great significance in subgroups of patients with estrogen receptor-negative and human EGF receptor 2-positive tumors. Prospective clinical trials are warranted in order to validate the use of CTCs as predictive and/or prognostic markers and assess their utility in individualizing therapy of patients with early breast cancer.

Triple negative breast cancers: clinical and prognostic implications

Triple negative breast cancers are defined by the absence of oestrogen, progesterone and HER2 expression. Most triple negative cancers display distinct clinical and pathological characteristics with a high proportion of these tumours occurring at a younger age of onset and in African-American women. Triple negative tumours typically demonstrate high histological grade and are the most common breast cancer subtype in BRCA1 carriers. In addition, many of the features of triple negative cancers are similar to those identified in the basal-like molecular subtype which has recently been characterised by gene expression profiling. Although the two groups overlap, they are not synonymous. Triple negative breast cancers are of pivotal clinical importance given the lack of therapeutic options. The prognostic significance of triple negative tumours remains unclear since the group is heterogeneous and worst prognosis seems to be mostly confined to those that express basal cytokeratins or epidermal growth factor receptor (EGFR). This review focuses on outlining the pathological, molecular, and clinical features of triple negative breast cancers, discusses its prognostic value and summarises current therapeutic approaches and future directions of research.

Molecular-based tumour subtypes of canine mammary carcinomas assessed by immunohistochemistry

Background

Human breast cancer is classified by gene expression profile into subtypes consisting of two hormone (oestrogen and/or progesterone) receptor-positive types (luminal-like A and luminal-like B) and three hormone receptor-negative types [human epidermal growth factor receptor 2-expressing, basal-like, and unclassified ("normal-like")]. Immunohistochemical surrogate panels are also proposed to potentially identify the molecular-based groups. The present study aimed to apply an immunohistochemical panel (anti-ER, -PR, -ERB-B2, -CK 5/6 and -CK14) in a series of canine malignant mammary tumours to verify the molecular-based classification, its correlation with invasion and grade, and its use as a prognostic aid in veterinary practice.

Results

Thirty-five tumours with luminal pattern (ER+ and PR+) were subgrouped into 13 A type and 22 B type, if ERB-B2 positive or negative. Most luminal-like A and basal-like tumours were grade 1 carcinomas, while the percentage of luminal B tumours was higher in grades 2 and 3 (Pearson Chi-square P = 0.009). No difference in the percentage of molecular subtypes was found between simple and complex/mixed carcinomas (Pearson Chi-square P = 0.47). No significant results were obtained by survival analysis, even if basal-like tumours had a more favourable prognosis than luminal-like lesions.

Conclusion

The panel of antibodies identified only three tumour groups (luminal-like A and B, and basal-like) in the dog. Even though canine mammary tumours may be a model of human breast cancer, the existence of the same carcinoma molecular subtypes in women awaits confirmation. Canine mammary carcinomas show high molecular heterogeneity, which would benefit from a classification based on molecular differences. Stage and grade showed independent associations with survival in the multivariate regression, while molecular subtype grouping and histological type did not show associations. This suggests that caution should be used when applying this classification to the dog, in which invasion and grade supply the most important prognostic information.

Integrative molecular profiling of triple negative breast cancers identifies amplicon drivers and potential therapeutic targets

Triple negative breast cancers (TNBCs) have a relatively poor prognosis and cannot be effectively treated with current targeted therapies. We searched for genes that have the potential to be therapeutic targets by identifying genes consistently over-expressed when amplified. Fifty-six TNBCs were subjected to high-resolution microarray-based comparative genomic hybridisation (aCGH), of which 24 were subjected to genome-wide gene expression analysis. TNBCs were genetically heterogeneous; no individual focal amplification was present at high frequency, although 78.6% of TNBCs harboured at least one focal amplification. Integration of aCGH and expression data revealed 40 genes significantly overexpressed when amplified, including the known oncogenes and potential therapeutic targets, FGFR2 (10q26.3), BUB3 (10q26.3), RAB20 (13q34), PKN1 (19p13.12), and NOTCH3 (19p13.12). We identified two TNBC cell lines with FGFR2 amplification, which both had constitutive activation of FGFR2. Amplified cell lines were highly sensitive to FGFR inhibitor PD173074, and to RNAi silencing of FGFR2. Treatment with PD173074 induced apoptosis resulting partly from inhibition of PI3K-AKT signalling. Independent validation using publicly available aCGH datasets revealed FGFR2 gene was amplified in 4% (6/165) of TNBC, but not in other subtypes (0/214, p=0.0065). Our analysis demonstrates that TNBCs are heterogeneous tumours with amplifications of FGFR2 in a subgroup of tumours.

[Gene expression based multigene prognostic and predictive tests in breast cancer]

Patient tailored therapy will serve the fundamentals of future cancer treatment. For this it will be imperative to characterize the tumor and to acquire precise predictive and prognostic information. We can achieve this by using not only monogenic (like ER, PR, HER-2, Ki-67) but also multigene assays, which can provide answers to several diagnostic questions simultaneously. We present a summary of currently available RT-PCR and microarray based multigene tests including MammaPrint, Oncotype DX, BLN Assay, Theros Breast Cancer Index SM, MapQuant DX, ARUP Breast Bioclassifier, Celera Metastatic Score, eXagen BCtm, Invasive Gene Signature, Wound Response Indicator and Mammostrat. Two of these (Oncotype DX and MammaPrint) are already incorporated in several diagnostic protocols. However, multiple unsolved issues deteriorate the value of these tests: generally the validation is poor, the gene sets do not confirm each other, the associated costs are high and the necessary bioinformatics is highly complex.

A taxonomy of epithelial human cancer and their metastases

Background

Microarray technology has allowed to molecularly characterize many different cancer sites. This technology has the potential to individualize therapy and to discover new drug targets. However, due to technological differences and issues in standardized sample collection no study has evaluated the molecular profile of epithelial human cancer in a large number of samples and tissues. Additionally, it has not yet been extensively investigated whether metastases resemble their tissue of origin or tissue of destination.

Methods

We studied the expression profiles of a series of 1566 primary and 178 metastases by unsupervised hierarchical clustering. The clustering profile was subsequently investigated and correlated with clinico-pathological data. Statistical enrichment of clinico-pathological annotations of groups of samples was investigated using Fisher exact test. Gene set enrichment analysis (GSEA) and DAVID functional enrichment analysis were used to investigate the molecular pathways. Kaplan-Meier survival analysis and log-rank tests were used to investigate prognostic significance of gene signatures.

Results

Large clusters corresponding to breast, gastrointestinal, ovarian and kidney primary tissues emerged from the data. Chromophobe renal cell carcinoma clustered together with follicular differentiated thyroid carcinoma, which supports recent morphological descriptions of thyroid follicular carcinoma-like tumors in the kidney and suggests that they represent a subtype of chromophobe carcinoma. We also found an expression signature identifying primary tumors of squamous cell histology in multiple tissues. Next, a subset of ovarian tumors enriched with endometrioid histology clustered together with endometrium tumors, confirming that they share their etiopathogenesis, which strongly differs from serous ovarian tumors. In addition, the clustering of colon and breast tumors correlated with clinico-pathological characteristics. Moreover, a signature was developed based on our unsupervised clustering of breast tumors and this was predictive for disease-specific survival in three independent studies. Next, the metastases from ovarian, breast, lung and vulva cluster with their tissue of origin while metastases from colon showed a bimodal distribution. A significant part clusters with tissue of origin while the remaining tumors cluster with the tissue of destination.

Conclusion

Our molecular taxonomy of epithelial human cancer indicates surprising correlations over tissues. This may have a significant impact on the classification of many cancer sites and may guide pathologists, both in research and daily practice. Moreover, these results based on unsupervised analysis yielded a signature predictive of clinical outcome in breast cancer. Additionally, we hypothesize that metastases from gastrointestinal origin either remember their tissue of origin or adapt to the tissue of destination. More specifically, colon metastases in the liver show strong evidence for such a bimodal tissue specific profile.

Resistance to Trastuzumab in Breast Cancer

HER2 is a transmembrane oncoprotein encoded by the HER2/neu gene and is overexpressed in approximately 20 to 25% of invasive breast cancers. It can be therapeutically targeted by trastuzumab, a humanized IgG1 kappa light chain monoclonal antibody. Although trastuzumab is currently considered one of the most effective treatments in oncology, a significant number of patients with HER2-overexpressing breast cancer do not benefit from it. Understanding the mechanisms of action and resistance to trastuzumab is therefore crucial for the development of new therapeutic strategies. This review discusses proposed trastuzumab mode of action as well as proposed mechanisms for resistance. Mechanisms for resistance are grouped into four main categories: (1) obstacles preventing trastuzumab binding to HER2; (2) upregulation of HER2 downstream signaling pathways; (3) signaling through alternate pathways; and (4) failure to trigger an immune-mediated mechanism to destroy tumor cells. These potential mechanisms through which trastuzumab resistance may arise have been used as a guide to develop drugs, presently in clinical trials, to overcome resistance. The mechanisms conferring trastuzumab resistance, when completely understood, will provide insight on how best to treat HER2-overexpressing breast cancer. The understanding of each mechanism of resistance is therefore critical for the educated development of strategies to overcome it, as well as for the development of tools that would allow definitive and efficient patient selection for each therapy. (Clin Cancer Res 2009;15(24):7479-91).

Comprehensive characterization of the DNA amplification at 13q34 in human breast cancer reveals TFDP1 and CUL4A as likely candidate target genes

Introduction

Breast cancer subtypes exhibit different genomic aberration patterns with a tendency for high-level amplifications in distinct chromosomal regions. These genomic aberrations may drive carcinogenesis through the upregulation of proto-oncogenes. We have characterized DNA amplification at the human chromosomal region 13q34 in breast cancer.

Methods

A set of 414 familial and sporadic breast cancer cases was studied for amplification at region 13q34 by fluorescence in situ hybridization (FISH) analysis on tissue microarrays. Defining the minimal common region of amplification in those cases with amplification at 13q34 was carried out using an array-based comparative genomic hybridization platform. We performed a quantitative real-time - polymerase chain reaction (qRT-PCR) gene expression analysis of 11 candidate genes located within the minimal common region of amplification. Protein expression levels of two of these genes (TFDP1 and CUL4A) were assessed by immunohistochemical assays on the same tissue microarrays used for FISH studies, and correlated with the expression of a panel of 33 antibodies previously analyzed.

Results

We have found 13q34 amplification in 4.5% of breast cancer samples, but the frequency increased to 8.1% in BRCA1-associated tumors and to 20% in basal-like tumors. Tumors with 13q34 amplification were associated with high grade, estrogen receptor negativity, and expression of EGFR, CCNE, CK5, and P-Cadherin, among other basal cell markers. We have defined a 1.83 megabases minimal common region of genomic amplification and carried out mRNA expression analyses of candidate genes located therein, identifying CUL4A and TFDP1 as the most likely target genes. Moreover, we have confirmed that tumors with 13q34 amplification significantly overexpress CUL4A and TFDP1 proteins. Tumors overexpressing either CUL4A or TFDP1 were associated with tumor proliferation and cell cycle progression markers.

Conclusions

We conclude that 13q34 amplification may be of relevance in tumor progression of basal-like breast cancers by inducing overexpression of CUL4A and TFDP1, which are both important in cell cycle regulation. Alternatively, as these genes were also overexpressed in non-basal-like tumor samples, they could play a wider role in cancer development by inducing tumor proliferation.

Subtypes of familial breast tumours revealed by expression and copy number profiling

Extensive expression profiling studies have shown that sporadic breast cancer is composed of five clinically relevant molecular subtypes. However, although BRCA1-related tumours are known to be predominantly basal-like, there are few published data on other classes of familial breast tumours. We analysed a cohort of 75 BRCA1, BRCA2 and non-BRCA1/2 breast tumours by gene expression profiling and found that 74% BRCA1 tumours were basal-like, 73% of BRCA2 tumours were luminal A or B, and 52% non-BRCA1/2 tumours were luminal A. Thirty-four tumours were also analysed by single nucleotide polymorphism-comparative genomic hybridization (SNP-CGH) arrays. Copy number data could predict whether a tumour was basal-like or luminal with high accuracy, but could not predict its mutation class. Basal-like BRCA1 and basal-like non-BRCA1 tumours were very similar, and contained the highest number of chromosome aberrations. We identified regions of frequent gain containing potential driver genes in the basal (8q and 12p) and luminal A tumours (1q and 17q). Regions of homozygous loss associated with decreased expression of potential tumour suppressor genes were also detected, including in basal tumours (5q and 9p), and basal and luminal tumours (10q). This study highlights the heterogeneity of familial tumours and the clinical consequences for treatment and prognosis.

A high-resolution integrated analysis of genetic and expression profiles of breast cancer cell lines

Tumour cell lines derived from breast cancer patients constitute one of the cornerstones of breast cancer research. To characterise breast cancer cell lines at the genetic level, we have developed a full tiling path bacterial artificial chromosome (BAC) array collection for comparative genomic hybridisation (aCGH). This aCGH BAC collection covers 98% of the entire human genome at a resolution of 40-60 kbp. We have used this platform alongside an in-house produced 17 K cDNA microarray set to characterise the genetic and transcriptomic profiles of 24 breast cancer cell lines, as well as cell types derived from non-diseased breast. We demonstrate that breast cancer cell lines have genomic and transcriptomic features that recapitulate those of primary breast cancers and can be reliably subclassified into basal-like and luminal subgroups. By overlaying aCGH and transcriptomic data, we have identified 753 genes whose expression correlate with copy number; this list comprised numerous oncogenes recurrently amplified and overexpressed in breast cancer (e.g., HER2, MYC, CCND1 and AURKA). Finally, we demonstrate that although breast cancer cell lines have genomic features usually found in grade III breast cancers (i.e., gains of 1q, 8q and 20q), basal-like and luminal cell lines are characterised by distinct genomic aberrations.

Impact of biospecimens handling on biomarker research in breast cancer

Background

Gene expression profiling is moving from the research setting to the practical clinical use.

Gene signatures able to correctly identify high risk breast cancer patients as well as to predict response to treatment are currently under intense investigation. While technical issues dealing with RNA preparation, choice of array platforms, statistical analytical tools are taken into account, the tissue collection process is seldom considered.

The time elapsed between surgical tissue removal and freezing of samples for biological characterizations is rarely well defined and/or recorded even for recently stored samples, despite the publications of standard operating procedures for biological sample collection for tissue banks.

Methods

Breast cancer samples from 11 patients were collected immediately after surgical removal and subdivided into aliquots. One was immediately frozen and the others were maintained at room temperature for respectively 2, 6 and 24 hrs. RNA was extracted and gene expression profile was determined using cDNA arrays. Phosphoprotein profiles were studied in parallel.

Results

Delayed freezing affected the RNA quality only in 3 samples, which were not subjected to gene profiling. In the 8 breast cancer cases with apparently intact RNA also in sample aliquots frozen at delayed times, 461 genes were modulated simply as a function of freezing timing. Some of these genes were included in gene signatures biologically and clinically relevant for breast cancer. Delayed freezing also affected detection of phosphoproteins, whose pattern may be crucial for clinical decision on target-directed drugs.

Conclusion

Time elapsed between surgery and freezing of samples appears to have a strong impact and should be considered as a mandatory variable to control for clinical implications of inadequate tissue handling.

Positive cross-talk between estrogen receptor and NF-kappaB in breast cancer

Estrogen receptors (ER) and nuclear factor-kappaB (NF-kappaB) are known to play important roles in breast cancer, but these factors are generally thought to repress each other's activity. However, we have recently found that ER and NF-kappaB can also act together in a positive manner to synergistically increase gene transcription. To examine the extent of cross-talk between ER and NF-kappaB, a microarray study was conducted in which MCF-7 breast cancer cells were treated with 17beta-estradiol (E(2)), tumor necrosis factor alpha (TNFalpha), or both. Follow-up studies with an ER antagonist and NF-kappaB inhibitors show that cross-talk between E(2) and TNFalpha is mediated by these two factors. We find that although transrepression between ER and NF-kappaB does occur, positive cross-talk is more prominent with three gene-specific patterns of regulation: (a) TNFalpha enhances E(2) action on approximately 30% of E(2)-upregulated genes; (b) E(2) enhances TNFalpha activity on approximately 15% of TNFalpha-upregulated genes; and (c) E(2) + TNFalpha causes a more than additive upregulation of approximately 60 genes. Consistent with their prosurvival roles, ER and NF-kappaB and their target gene, BIRC3, are involved in protecting breast cancer cells against apoptosis. Furthermore, genes positively regulated by E(2) + TNFalpha are clinically relevant because they are enriched in luminal B breast tumors and their expression profiles can distinguish a cohort of patients with poor outcome following endocrine treatment. Taken together, our findings suggest that positive cross-talk between ER and NF-kappaB is more extensive than anticipated and that these factors may act together to promote survival of breast cancer cells and progression to a more aggressive phenotype.

Cyclin D1 is a direct target of JAG1-mediated Notch signaling in breast cancer

The Notch ligand, JAG1 is associated with breast cancer recurrence. Herein, we report on a genomics approach to elucidate mechanisms downstream of JAG1 that promote breast cancer growth. In a survey of 46 breast cancer cell lines, we found that triple negative (TN; basal and mesenchymal ER-, PR-, and Her2-negative) lines express JAG1 at significantly higher levels than do HER2(+) or luminal (ER(+)) Her2(-) cell lines. In contrast to the luminal lines tested (T47D and MCF7), TN breast cancer cell lines (HCC1143 and MDA MB231) display high-level JAG1 expression and growth inhibition with RNA interference-induced JAG1 down-regulation. We used microarray profiling of TN tumor cells transfected with JAG1 siRNA to identify JAG1-regulated genes (P <or= 0.005; fold change >or=1.5). Among JAG1-regulated genes identified, cyclin D1 was found to be a direct target of NOTCH1 and NOTCH3. We show that JAG1 down-regulation reduces direct binding of Notch to the cyclin D1 promoter, reduced cyclin D1 expression and inhibition of cell cycle progression through the cyclin D1-dependant G1/S checkpoint. Furthermore, we show that cyclin D1 and JAG1 expression correlate in TN breast cancer expression datasets. These data suggest a model whereby JAG1 promotes cyclin D1-mediated proliferation of TN breast cancers.

Activation of host wound responses in breast cancer microenvironment

PURPOSE

Cancer progression is mediated by processes that are also important in wound repair. As a result, cancers have been conceptualized as overhealing wounds or "wounds that do not heal," and gene expression signatures reflective of wound repair have shown value as predictors of breast cancer survival. Despite the widespread acknowledgment of commonalities between host responses to wounds and host responses to cancer, the gene expression responses of normal tissue adjacent to cancers have not been well characterized.

EXPERIMENTAL DESIGN

Using RNA extracted from histologically normal breast tissue from 107 patients, including 60 reduction mammoplasty patients and 47 cancer patients, we measured whole genome expression profiles and identified a gene expression signature that is induced in response to breast cancer.

RESULTS

This signature represents an in vivo "wound response" signature that is differentially expressed in the normal tissue of breast cancer patients compared with those without disease and is highly accurate (at least 92% sensitivity and 98% specificity) in distinguishing diseased and nondiseased. The in vivo wound response signature is highly prognostic of breast cancer survival, and there is a strong association between the groups identified by this signature and those identified using serum-treated fibroblasts and other microenvironment-derived or microenvironment-related signatures.

CONCLUSIONS

The prevalence of the wound response signature in histologically normal tissue adjacent to breast cancer suggests that microenvironment response is an important variable in breast cancer progression and may be an important target for clinical interventions.

Mucinous and neuroendocrine breast carcinomas are transcriptionally distinct from invasive ductal carcinomas of no special type

Mucinous carcinoma is considered a distinct pathological entity. However, mucinous tumours can be divided into a least two groups: mucinous A (or paucicellular) and mucinous B (or hypercellular). Mucinous B cancers display histological features that significantly overlap with those of neuroendocrine carcinomas. We investigate using genome-wide oligonucleotide microarrays whether mucinous A, mucinous B and neuroendocrine carcinomas are entities distinct from histological grade- and molecular subtype-matched invasive ductal carcinomas of no special type. Mucinous A and B and five neuroendocrine carcinomas were of luminal A subtype, whereas one neuroendocrine tumour was of luminal B phenotype. When analysed in conjunction with grade- and molecular subtype-matched invasive ductal carcinomas, hierarchical clustering analysis showed that the majority of mucinous and neuroendocrine cancers formed a separate cluster. Significance analysis of microarrays identified 3155 genes differentially expressed between mucinous/ neuroendocrine carcinomas and grade- and molecular subtype-matched invasive ductal carcinomas (false discovery rate <0.85%), and revealed that genes associated with connective tissue/extracellular matrix were downregulated in mucinous/neuroendocrine cancers compared to invasive ductal carcinomas. When subjected to hierarchical clustering analysis separately, mucinous A cancers formed a discrete subgroup, whereas no separation was observed between mucinous B and neuroendocrine cancers. In fact, significance of microarray analysis showed no transcriptomic differences between mucinous B and neuroendocrine cancers, whereas mucinous A cancers displayed 89 up- and 26 downregulated genes when compared with mucinous B (false discovery rate <1.15%) and 368 up- and 48 downregulated genes when compared to neuroendocrine carcinomas (false discovery rate <1.0%). Our results provide circumstantial evidence to suggest that mucinous and neuroendocrine carcinomas are transcriptionally distinct from histological grade- and molecular subtype-matched invasive ductal carcinomas, and that luminal A breast cancers are a heterogeneous group of tumours. These findings support the contention that mucinous B and neuroendocrine carcinomas are part of a spectrum of lesions, whereas mucinous A is a discrete entity.

Gene expression profiling integrated into network modelling reveals heterogeneity in the mechanisms of BRCA1 tumorigenesis

BACKGROUND

Gene expression profiling has distinguished sporadic breast tumour classes with genetic and clinical differences. Less is known about the molecular classification of familial breast tumours, which are generally considered to be less heterogeneous. Here, we describe molecular signatures that define BRCA1 subclasses depending on the expression of the gene encoding for oestrogen receptor, ESR1.

METHODS

For this purpose, we have used the Oncochip v2, a cancer-related cDNA microarray to analyze 14 BRCA1-associated breast tumours.

RESULTS

Signatures were found to be molecularly associated with different biological processes and transcriptional regulatory programs. The signature of ESR1-positive tumours was mainly linked to cell proliferation and regulated by ER, whereas the signature of ESR1-negative tumours was mainly linked to the immune response and possibly regulated by transcription factors of the REL/NFkappaB family. These signatures were then verified in an independent series of familial and sporadic breast tumours, which revealed a possible prognostic value for each subclass. Over-expression of immune response genes seems to be a common feature of ER-negative sporadic and familial breast cancer and may be associated with good prognosis. Interestingly, the ESR1-negative tumours were substratified into two groups presenting slight differences in the magnitude of the expression of immune response transcripts and REL/NFkappaB transcription factors, which could be dependent on the type of BRCA1 germline mutation.

CONCLUSION

This study reveals the molecular complexity of BRCA1 breast tumours, which are found to display similarities to sporadic tumours, and suggests possible prognostic implications.

Can survival prediction be improved by merging gene expression data sets?

BACKGROUND

High-throughput gene expression profiling technologies generating a wealth of data, are increasingly used for characterization of tumor biopsies for clinical trials. By applying machine learning algorithms to such clinically documented data sets, one hopes to improve tumor diagnosis, prognosis, as well as prediction of treatment response. However, the limited number of patients enrolled in a single trial study limits the power of machine learning approaches due to over-fitting. One could partially overcome this limitation by merging data from different studies. Nevertheless, such data sets differ from each other with regard to technical biases, patient selection criteria and follow-up treatment. It is therefore not clear at all whether the advantage of increased sample size outweighs the disadvantage of higher heterogeneity of merged data sets. Here, we present a systematic study to answer this question specifically for breast cancer data sets. We use survival prediction based on Cox regression as an assay to measure the added value of merged data sets.

RESULTS

Using time-dependent Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) and hazard ratio as performance measures, we see in overall no significant improvement or deterioration of survival prediction with merged data sets as compared to individual data sets. This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets. Surprisingly, we found that the overall best performance was achieved with a single-gene predictor consisting of CYB5D1.

CONCLUSIONS

Merging did not deteriorate performance on average despite (a) The diversity of microarray platforms used. (b) The heterogeneity of patients cohorts. (c) The heterogeneity of breast cancer disease. (d) Substantial variation of time to death or relapse. (e) The reduced number of genes in the merged data sets. Predictors derived from the merged data sets were more robust, consistent and reproducible across microarray platforms. Moreover, merging data sets from different studies helps to better understand the biases of individual studies and can lead to the identification of strong survival factors like CYB5D1 expression.

High ACAT1 expression in estrogen receptor negative basal-like breast cancer cells is associated with LDL-induced proliferation

The specific role of dietary fat in breast cancer progression is unclear, although a low-fat diet was associated with decreased recurrence of estrogen receptor alpha negative (ER(-)) breast cancer. ER(-) basal-like MDA-MB-231 and MDA-MB-436 breast cancer cell lines contained a greater number of cytoplasmic lipid droplets compared to luminal ER(+) MCF-7 cells. Therefore, we studied lipid storage functions in these cells. Both triacylglycerol and cholesteryl ester (CE) concentrations were higher in the ER(-) cells, but the ability to synthesize CE distinguished the two types of breast cancer cells. Higher baseline, oleic acid- and LDL-stimulated CE concentrations were found in ER(-) compared to ER(+) cells. The differences corresponded to greater mRNA and protein levels of acyl-CoA:cholesterol acyltransferase 1 (ACAT1), higher ACAT activity, higher caveolin-1 protein levels, greater LDL uptake, and lower de novo cholesterol synthesis in ER(-) cells. Human LDL stimulated proliferation of ER(-) MDA-MB-231 cells, but had little effect on proliferation of ER(+) MCF-7 cells. The functional significance of these findings was demonstrated by the observation that the ACAT inhibitor CP-113,818 reduced proliferation of breast cancer cells, and specifically reduced LDL-induced proliferation of ER(-) cells. Taken together, our studies show that a greater ability to take up, store and utilize exogenous cholesterol confers a proliferative advantage to basal-like ER(-) breast cancer cells. Differences in lipid uptake and storage capability may at least partially explain the differential effect of a low-fat diet on human breast cancer recurrence.

A study of high-nuclear-grade breast cancer in Thailand: subclassification and correlation with prognostic factors and immunohistochemical study

OBJECTIVES

To classify high-nuclear-grade breast cancer (BC) into typical medullary carcinoma (TMC), atypical medullary carcinoma (AMC), and non-medullary carcinoma (NMC), and luminal A, luminal B, and HER2, and to correlate these tumors with other prognostic factors.

MATERIALS AND METHODS

A retrospective study reviewing high-nuclear-grade BCs. The patients' age, histologic types, various histologic features, axillary lymph node (ALN) status, and results of immunohistochemical (IHC) study were recorded and analyzed.

RESULTS

One-hundred and eighty-one cases of high-nuclear-grade BCs were reviewed and categorized into IDC, NOS (140, 77.3%), TMC (1, 0.6%), AMC (21, 11.6%), and others (19, 10.5%). The median age was younger in AMC than in NMC patients. NMC patients had a higher incidence of LVI and ALN metastasis with involvement of more than four lymph nodes (p = 0.006) whereas AMC patients had a higher mitotic index. Forty-six (35.9%) cases were triple-negative (TN), including 1 (100%), 7 (53.9%) and 38 (33.3%) cases of TMC, AMC, and NMC, respectively. AMC had a significantly lower number of node metastases (p = 0.006) than NMC; whereas TN had higher MI (p = 0.001) than non-TN. The non-TN group was subclassified into luminal A, luminal B, and HER2. Of these, TN and luminal B occurred at younger age (p = 0.01) whereas TN and luminal A had a higher mitotic count. TN had lower incidence of LNM including higher number of LNM.

CONCLUSION

Overall, AMC-TN group showed a basal-like prognostic factor expression. NMC may be separated into TN and non-TN, with possibly different behavior. These sub-groupings should continue to be used. Interestingly, luminal A in our study tended to correlate with poor prognostic factors, thus, luminal A with high nuclear grade may not be representative of the usual luminal group profiles.

Genetic characterization of breast cancer and implications for clinical management

Breast cancer is a genetic disease caused by the accumulation of mutations in neoplastic cells. In the last few years, high-throughput microarray-based molecular analysis has provided increasingly more coherent information about the genetic aberrations in breast cancer. New biomarkers and molecular techniques are slowly becoming part of the diagnostic and prognostic armamentarium available for pathologists and oncologists to tailor the therapy for breast cancer patients. In this review, we will focus on the contribution of breast cancer somatic genetics to our understanding of breast cancer biology and its impact on breast cancer patient management.

Confounding effects in "A six-gene signature predicting breast cancer lung metastasis"

The majority of breast cancer deaths result from metastases rather than from direct effects of the primary tumor itself. Recently, Landemaine and colleagues described a six-gene signature purported to predict lung metastasis risk. They analyzed gene expression in 23 metastases from breast cancer patients (5 lung, 18 non-lung) identifying a 21-gene signature. Expression of 16 of these was analyzed in primary breast tumors from 72 patients with known outcome, and six were selected that were predictive of lung metastases: DSC2, TFCP2L1, UGT8, ITGB8, ANP32E, and FERMT1. Despite the value of such a signature, our analysis indicates that this analysis ignored potentially important confounding factors and that their signature is instead a surrogate for molecular subtype.

BRCA1-deficient mammary tumor cells are dependent on EZH2 expression and sensitive to Polycomb Repressive Complex 2-inhibitor 3-deazaneplanocin A

Introduction

Treatment of breast cancer is becoming more individualized with the recognition of tumor subgroups that respond differently to available therapies. Breast cancer 1 gene (BRCA1)-deficient tumors are usually of the basal subtype and associated with poor survival rates, highlighting the need for more effective therapy.

Methods

We investigated a mouse model that closely mimics breast cancer arising in BRCA1-mutation carriers to better understand the molecular mechanism of tumor progression and tested whether targeting of the Polycomb-group protein EZH2 would be a putative therapy for BRCA1-deficient tumors.

Results

Gene expression analysis demonstrated that EZH2 is overexpressed in BRCA1-deficient mouse mammary tumors. By immunohistochemistry we show that an increase in EZH2 protein levels is also evident in tumors from BRCA1-mutation carriers. EZH2 is responsible for repression of genes driving differentiation and could thus be involved in the undifferentiated phenotype of these tumors. Importantly, we show that BRCA1-deficient cancer cells are selectively dependent on their elevated EZH2 levels. In addition, a chemical inhibitor of EZH2, 3-deazaneplanocin A (DZNep), is about 20-fold more effective in killing BRCA1-deficient cells compared to BRCA1-proficient mammary tumor cells.

Conclusions

We demonstrate by specific knock-down experiments that EZH2 overexpression is functionally relevant in BRCA1-deficient breast cancer cells. The effectiveness of a small molecule inhibitor indicates that EZH2 is a druggable target. The overexpression of EZH2 in all basal-like breast cancers warrants further investigation of the potential for targeting the genetic make-up of this particular breast cancer type.

A core MYC gene expression signature is prominent in basal-like breast cancer but only partially overlaps the core serum response

BACKGROUND

The MYC oncogene contributes to induction and growth of many cancers but the full spectrum of the MYC transcriptional response remains unclear.

METHODOLOGY/PRINCIPAL FINDINGS

Using microarrays, we conducted a detailed kinetic study of genes that respond to MYCN or MYCNDeltaMBII induction in primary human fibroblasts. In parallel, we determined the response to steady state overexpression of MYCN and MYCNDeltaMBII in the same cell type. An overlapping set of 398 genes from the two protocols was designated a 'Core MYC Signature' and used for further analysis. Comparison of the Core MYC Signature to a published study of the genes induced by serum stimulation revealed that only 7.4% of the Core MYC Signature genes are in the Core Serum Response and display similar expression changes to both MYC and serum. Furthermore, more than 50% of the Core MYC Signature genes were not influenced by serum stimulation. In contrast, comparison to a panel of breast cancers revealed a strong concordance in gene expression between the Core MYC Signature and the basal-like breast tumor subtype, which is a subtype with poor prognosis. This concordance was supported by the higher average level of MYC expression in the same tumor samples.

CONCLUSIONS/SIGNIFICANCE

The Core MYC Signature has clinical relevance as this profile can be used to deduce an underlying genetic program that is likely to contribute to a clinical phenotype. Therefore, the presence of the Core MYC Signature may predict clinical responsiveness to therapeutics that are designed to disrupt MYC-mediated phenotypes.

An integrative genomic and transcriptomic analysis reveals molecular pathways and networks regulated by copy number aberrations in basal-like, HER2 and luminal cancers

Breast cancer is a heterogeneous disease caused by the accumulation of genetic changes in neoplastic cells. We hypothesised that molecular subtypes of breast cancer may be driven by specific constellations of genes whose expression is regulated by gene copy number aberrations. To address this question, we analysed a series of 48 microdissected grade III ductal carcinomas using high resolution microarray comparative genomic hybridisation and mRNA expression arrays. There were 5,931 genes whose expression significantly correlates with copy number identified; out of these, 1,897 genes were significantly differentially expressed between basal-like, HER2 and luminal tumours. Ingenuity Pathway Analysis (IPA) revealed that 'G1/S cell cycle regulation' and 'BRCA1 in DNA damage control' pathways were significantly enriched for genes whose expression correlates with copy number and are differentially expressed between the molecular subtypes of breast cancer. IPA of genes whose expression significantly correlates with copy number in each molecular subtype individually revealed that canonical pathways involved in oestrogen receptor (ER) signalling and DNA repair are enriched for these genes. We also identified 32, 157 and 265 genes significantly overexpressed when amplified in basal-like, HER2 and luminal cancers, respectively. These lists include known and novel potential therapeutic targets (e.g. HER2 and PPM1D in HER2 cancers). Our results provide strong circumstantial evidence that different patterns of genetic aberrations in distinct molecular subtypes of breast cancer contribute to their specific transcriptomic profiles and that biological phenomena characteristic of each subtype (e.g. proliferation, HER2 and ER signalling) may be driven by specific patterns of copy number aberrations.

Concordance of clinical and molecular breast cancer subtyping in the context of preoperative chemotherapy response

ER, PR and HER2 status in breast cancer are important markers for the selection of drug therapy. By immunohistochemistry (IHC), three major breast cancer subtypes can be distinguished: Triple negative (TN(IHC)), HER2+(IHC) and Luminal(IHC) (ER+(IHC)/HER2-(IHC)). By using the intrinsic gene set defined by Hu et al. five molecular subtypes (Basal(mRNA), HER2+(mRNA), Luminal A(mRNA), Luminal B(mRNA) and Normal-like(mRNA)) can be defined. We studied the concordance between analogous subtypes and their prediction of response to neoadjuvant chemotherapy. We classified 195 breast tumors by both IHC and mRNA expression analysis of patients who received neoadjuvant treatment at the Netherlands Cancer institute for Stage II-III breast cancer between 2000 and 2007. The pathological complete remission (pCR) rate was used to assess chemotherapy response. The IHC and molecular subtypes showed high concordance with the exception of the HER2+(IHC) group. 60% of the HER2+(IHC) tumors were not classified as HER2+(mRNA). The HER2+(IHC)/Luminal A or B(mRNA) group had a low response rate to a trastuzumab-chemotherapy combination with a pCR rate of 8%, while the HER2+(mRNA) group had a pCR rate of 54%. The Luminal A(mRNA) and Luminal B(mRNA) groups showed similar degrees of response to chemotherapy. Neither the PR status nor the endocrine responsiveness index subdivided the ER+(IHC) tumors accurately into Luminal A(mRNA) and Luminal B(mRNA) groups. Molecular subtyping suggests the existence of a HER2+(IHC)/Luminal(mRNA) group that responds poorly to trastuzumab-based chemotherapy. For Luminal(IHC) and triple negative(IHC) tumors, further subdivision into molecular subgroups does not offer a clear advantage in treatment selection.

The role of miR-206 in the epidermal growth factor (EGF) induced repression of estrogen receptor-alpha (ERalpha) signaling and a luminal phenotype in MCF-7 breast cancer cells

Epidermal growth factor (EGF) receptor (EGFR)/MAPK signaling can induce a switch in MCF-7 breast cancer cells, from an estrogen receptor (ER)alpha-positive, Luminal-A phenotype, to an ERalpha-negative, Basal-like phenotype. Although mechanisms for this switch remain obscure, Basal-like cancers are typically high grade and confer a poorer clinical prognosis. We previously reported that miR-206 and ERalpha repress each other's expression in MCF-7 cells in a double-negative feedback loop. We show herein that miR-206 coordinately targets mRNAs encoding the coactivator proteins steroid receptor coactivator (SRC)-1 and SRC-3, and the transcription factor GATA-3, all of which contribute to estrogenic signaling and a Luminal-A phenotype. Overexpression of miR-206 repressed estrogen-mediated responses in MCF-7 cells, even in the presence of ERalpha encoded by an mRNA lacking a 3'-untranslated region, suggesting miR-206 affects estrogen signaling by targeting mRNAs encoding ERalpha-associated coregulatory proteins. Furthermore, EGF treatments enhanced miR-206 levels in MCF-7 cells and ERalpha-negative, EGFR-positive MDA-MB-231 cells, whereas EGFR small interfering RNA, or PD153035, an EGFR inhibitor, or U0126, a MAPK kinase inhibitor, significantly reduced miR-206 levels in MDA-MB-231 cells. Blocking EGF-induced enhancement of miR-206 with antagomiR-206 abrogated the EGF-inhibitory effect on ERalpha, SRC-1, and SRC-3 levels, and on estrogen response element-luciferase activity, indicating that EGFR signaling represses estrogenic responses in MCF-7 cells by enhancing miR-206 activity. Elevated miR-206 levels in MCF-7 cells ultimately resulted in reduced cell proliferation, enhanced apoptosis, and reduced expression of multiple estrogen-responsive genes. In conclusion, miR-206 contributes to EGFR-mediated abrogation of estrogenic responses in MCF-7 cells, contributes to a Luminal-A- to Basal-like phenotypic switch, and may be a measure of EGFR response within Basal-like breast tumors.

An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer

Introduction

Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation.

Methods

We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies.

Results

We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient.

Conclusions

Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.

Molecular characterization of breast cancer with high-resolution oligonucleotide comparative genomic hybridization array

PURPOSE

We used high-resolution oligonucleotide comparative genomic hybridization (CGH) arrays and matching gene expression array data to identify dysregulated genes and to classify breast cancers according to gene copy number anomalies.

EXPERIMENTAL DESIGN

DNA was extracted from 106 pretreatment fine needle aspirations of stage II-III breast cancers that received preoperative chemotherapy. CGH was done using Agilent Human 4 x 44K arrays. Gene expression data generated with Affymetrix U133A gene chips was also available on 103 patients. All P values were adjusted for multiple comparisons.

RESULTS

The average number of copy number abnormalities in individual tumors was 76 (range 1-318). Eleven and 37 distinct minimal common regions were gained or lost in >20% of samples, respectively. Several potential therapeutic targets were identified, including FGFR1 that showed high-level amplification in 10% of cases. Close correlation between DNA copy number and mRNA expression levels was detected. Nonnegative matrix factorization (NMF) clustering of DNA copy number aberrations revealed three distinct molecular classes in this data set. NMF class I was characterized by a high rate of triple-negative cancers (64%) and gains of 6p21. VEGFA, E2F3, and NOTCH4 were also gained in 29% to 34% of triple-negative tumors. A gain of ERBB2 gene was observed in 52% of NMF class II and class III was characterized by a high rate of estrogen receptor-positive tumors (73%) and a low rate of pathologic complete response to preoperative chemotherapy (3%).

CONCLUSION

The present study identified dysregulated genes that could classify breast cancer and may represent novel therapeutic targets for molecular subsets of cancers.

Multigene classifiers, prognostic factors, and predictors of breast cancer clinical outcome

A series of multigene classifiers, prognostic and predictive tests have recently been introduced as potentially useful adjuncts for the management of recently diagnosed breast cancer patients. These tests have used both slide-based methods including immunohistochemistry and fluorescence in situ hybridization and nonmorphology driven molecular platforms including quantitative multiplex real time polymerase chain reaction and genomic microarray profiling. In this review, a series of partially and completely commercialized multigene assays are compared with the standard breast cancer clinico-pathologic variables and biomarkers and evaluated as to the level of their scientific validation, current clinical utility, regulatory approval status, and estimated cost-benefit. A comparison of the Oncotype Dx and MammaPrint assays indicates that the Oncotype Dx test has the advantages of an earlier commercial launch in the US, wide acceptance for payment by third party payors, the ease of use of formalin fixed paraffin embedded tissues, a recommendation as ready for use by the American Society of Clinical Oncology Breast Cancer Tumor Markers Update Committee, a continuous rather than dichotomous algorithm, inclusion of both estrogen receptor (ER) and human epidermal growth factor receptor 2 in the mRNA profile, an ability to serve as both a prognostic and predictive test for certain hormonal and chemotherapeutic agents, demonstrated cost-effectiveness in 1 published study, and a high accrual rate for the prospective validation clinical trial (Trial Assigning Individualized Options for Treatment Rx). The MammaPrint assay has the advantages of a 510(k) clearance by the US Food and Drug Administration, a larger gene number which may enhance further utility, and the potentially wider patient eligibility including lymph node-positive, ER-negative, and younger patients being accrued into the prospective trial (the Microarray in Node-negative Disease may Avoid ChemoTherapy). A number of other assays have specific predictive goals most often focused on the efficacy of tamoxifen in ER-positive patients such as the Two-gene Ratio test and the Cytochrome P450 CYP2D6 genotyping assay.

A novel lung metastasis signature links Wnt signaling with cancer cell self-renewal and epithelial-mesenchymal transition in basal-like breast cancer

The establishment of metastasis depends on the ability of cancer cells to acquire a migratory phenotype combined with their capacity to recreate a secondary tumor in a distant tissue. In epithelial cancers, such as those of the breast, the epithelial-mesenchymal transition (EMT) is associated with basal-like breast cancers, generates cells with stem-like properties, and enables cancer cell dissemination and metastasis. However, the molecular mechanism(s) that connects stem cell-like characteristics with EMT has yet to be defined. Using an orthotopic model of human breast cancer metastasis to lung, we identified a poor prognosis gene signature, in which several components of the wnt signaling pathway were overexpressed in early lung metastases. The wnt genes identified in this signature were strongly associated with human basal-like breast cancers. We found that inhibiting wnt signaling through LRP6 reduced the capacity of cancer cells to self-renew and seed tumors in vivo. Furthermore, inhibition of wnt signaling resulted in the reexpression of breast epithelial differentiation markers and repression of EMT transcription factors SLUG and TWIST. Collectively, these results provide a molecular link between self-renewal, EMT, and metastasis in basal-like breast cancers.

Subtype-specific peripheral blood gene expression profiles in recent-onset juvenile idiopathic arthritis

OBJECTIVE

To identify differences in peripheral blood gene expression between patients with different subclasses of juvenile idiopathic arthritis (JIA) and healthy controls in a multicenter study of patients with recent-onset JIA prior to treatment with disease-modifying antirheumatic drugs (DMARDs) or biologic agents.

METHODS

Peripheral blood mononuclear cells (PBMCs) from 59 healthy children and 136 patients with JIA (28 with enthesitis-related arthritis [ERA], 42 with persistent oligoarthritis, 45 with rheumatoid factor [RF]-negative polyarthritis, and 21 with systemic disease) were isolated from whole blood. Poly(A) RNA was labeled using a commercial RNA amplification and labeling system (NuGEN Ovation), and gene expression profiles were obtained using commercial expression microarrays (Affymetrix HG-U133 Plus 2.0).

RESULTS

A total of 9,501 differentially expressed probe sets were identified among the JIA subtypes and controls (by analysis of variance; false discovery rate 5%). Specifically, 193, 1,036, 873, and 7,595 probe sets were different in PBMCs from the controls compared with those from the ERA, persistent oligoarthritis, RF-negative polyarthritis, and systemic JIA patients, respectively. In patients with persistent oligoarthritis, RF-negative polyarthritis, and systemic JIA subtypes, up-regulation of genes associated with interleukin-10 (IL-10) signaling was prominent. A hemoglobin cluster was identified that was underexpressed in ERA patients but overexpressed in systemic JIA patients. The influence of JAK/STAT, ERK/MAPK, IL-2, and B cell receptor signaling pathways was evident in patients with persistent oligoarthritis. In systemic JIA, up-regulation of innate immune pathways, including IL-6, Toll-like receptor/IL-1 receptor, and peroxisome proliferator-activated receptor signaling, were noted, along with down-regulation of gene networks related to natural killer cells and T cells. Complement and coagulation pathways were up-regulated in systemic JIA, with a subset of these genes being differentially expressed in other subtypes as well.

CONCLUSION

Expression analysis identified differentially expressed genes in PBMCs obtained early in the disease from patients with different subtypes of JIA and in healthy controls, providing evidence of immunobiologic differences between these forms of childhood arthritis.

Basal-like breast carcinoma: from expression profiling to routine practice

CONTEXT

Advances in the understanding of the molecular and genetic mechanisms of breast cancer have led to realization of the heterogeneity of the disease and the promise of a new era of individualized management for patients with breast cancer. The advent and use of high-throughput molecular methods for the study of breast cancer have brought to the forefront the existence of the so-called basal-like breast cancers, which have been shown to have distinct biologic and clinical characteristics.

OBJECTIVE

To critically assess the clinicopathologic features of basal-like breast cancer, discuss the morphologic and immunophenotypic features of basal-like cancer, and explore the criteria that can be used to identify these tumors in routine practice.

DATA SOURCES

A Medline/PubMed search was conducted using the terms "basal-like," "(basal OR basaloid OR basal-like) AND breast cancer." All articles in English language were retrieved and critically reviewed.

CONCLUSIONS

Basal-like breast cancers constitute a distinct, yet heterogeneous, class of neoplasms associated with specific histologic features and poor prognosis despite high response rates to neoadjuvant chemotherapy. Basal-like breast cancers have features that recapitulate those of tumors arising in BRCA1 mutation carriers, and the majority of patients with BRCA1 germline mutations develop basal-like breast cancers. At the molecular level, basal-like cancers harbor a transcriptome that is distinct from that of hormone-receptor-positive or HER2-amplified tumors, being characterized by the expression of genes usually found in basal/myoepithelial cells of the breast. However, translating the new concepts about basal-like cancer into clinical practice has proven a Herculean task, given the lack of an internationally accepted definition for these tumors and for the method of identification in routine practice.

In vivo antitumor activity of MEK and phosphatidylinositol 3-kinase inhibitors in basal-like breast cancer models

PURPOSE

The pathways underlying basal-like breast cancer are poorly understood, and as yet, there is no approved targeted therapy for this disease. We investigated the role of mitogen-activated protein kinase kinase (MEK) and phosphatidylinositol 3-kinase (PI3K) inhibitors as targeted therapies for basal-like breast cancer.

EXPERIMENTAL DESIGN

We used pharmacogenomic analysis of a large panel of breast cancer cell lines with detailed accompanying molecular information to identify molecular predictors of response to a potent and selective inhibitor of MEK and also to define molecular mechanisms underlying combined MEK and PI3K targeting in basal-like breast cancer. Hypotheses were confirmed by testing in multiple tumor xenograft models.

RESULTS

We found that basal-like breast cancer models have an activated RAS-like transcriptional program and show greater sensitivity to a selective inhibitor of MEK compared with models representative of other breast cancer subtypes. We also showed that loss of PTEN is a negative predictor of response to MEK inhibition, that treatment with a selective MEK inhibitor caused up-regulation of PI3K pathway signaling, and that dual blockade of both PI3K and MEK/extracellular signal-regulated kinase signaling synergized to potently impair the growth of basal-like breast cancer models in vitro and in vivo.

CONCLUSIONS

Our studies suggest that single-agent MEK inhibition is a promising therapeutic modality for basal-like breast cancers with intact PTEN, and also provide a basis for rational combination of MEK and PI3K inhibitors in basal-like cancers with both intact and deleted PTEN.

Genomic antagonism between retinoic acid and estrogen signaling in breast cancer

Retinoic acid (RA) triggers antiproliferative effects in tumor cells, and therefore RA and its synthetic analogs have great potential as anticarcinogenic agents. Retinoic acid receptors (RARs) mediate RA effects by directly regulating gene expression. To define the genetic network regulated by RARs in breast cancer, we identified RAR genomic targets using chromatin immunoprecipitation and expression analysis. We found that RAR binding throughout the genome is highly coincident with estrogen receptor alpha (ERalpha) binding, resulting in a widespread crosstalk of RA and estrogen signaling to antagonistically regulate breast cancer-associated genes. ERalpha- and RAR-binding sites appear to be coevolved on a large scale throughout the human genome, often resulting in competitive binding activity at nearby or overlapping cis-regulatory elements. The highly coordinated intersection between these two critical nuclear hormone receptor signaling pathways provides a global mechanism for balancing gene expression output via local regulatory interactions dispersed throughout the genome.

Integrative analysis of cyclin protein levels identifies cyclin b1 as a classifier and predictor of outcomes in breast cancer

PURPOSE

We studied the expression levels of cyclins B1, D1, and E1 and the implications of cyclin overexpression for patient outcomes in distinct breast cancer subtypes defined by clinical variables and transcriptional profiling.

EXPERIMENTAL DESIGN

The expression levels of cyclins B1, D1, and E1 were quantified in 779 breast tumors and 53 cell lines using reverse phase protein arrays and/or transcriptional profiling.

RESULTS

Whereas cyclin E1 overexpression was a specific marker of triple-negative and basal-like tumors, cyclin B1 overexpression occurred in poor prognosis hormone receptor-positive, luminal B and basal-like breast cancers. Cyclin D1 overexpression occurred in luminal and normal-like cancers. Breast cancer subgroups defined by integrated expression of cyclins B1, D1, and E1 correlated significantly (P < 0.000001) with tumor subtypes defined by transcriptional profiling and clinical criteria. Across three hormone receptor-positive data sets, cyclin B1 was the dominant cyclin associated with poor prognosis in univariate and multivariate analyses. Although CCNE1 was present in significantly higher copy numbers in basal-like versus other subtypes (ANOVA P < 0.001), CCNB1 gene copy number did not show gain in breast cancer. Instead, cyclin B1 expression was increased in tumors with co-occurrence of TP53 mutations and MYC amplification, a combination that seems to characterize basal-like and luminal B tumors. CCNB1 gene expression was significantly correlated with PLK, CENPE, and AURKB gene expression.

CONCLUSION

Cyclins B1, D1, and E1 have distinct expressions in different breast cancer subtypes. Novel PLK, CENPE, and AURKB inhibitors should be assessed for therapeutic utility in poor prognosis cyclin B1-overexpressing breast cancers.

A mouse mammary gland involution mRNA signature identifies biological pathways potentially associated with breast cancer metastasis

Mouse mammary gland involution resembles a wound healing response with suppressed inflammation. Wound healing and inflammation are also associated with tumour development, and a 'wound-healing' gene expression signature can predict metastasis formation and survival. Recent studies have shown that an involuting mammary gland stroma can promote metastasis. It could therefore be hypothesised that gene expression signatures from an involuting mouse mammary gland may provide new insights into the physiological pathways that promote breast cancer progression. Indeed, using the HOPACH clustering method, the human orthologues of genes that were differentially regulated at day 3 of mammary gland involution and showed prolonged expression throughout the first 4 days of involution distinguished breast cancers in the NKI 295 breast cancer dataset with low and high metastatic activity. Most strikingly, genes associated with copper ion homeostasis and with HIF-1 promoter binding sites were the most over-represented, linking this signature to hypoxia. Further, six out of the ten mRNAs with strongest up-regulation in cancers with poor survival code for secreted factors, identifying potential candidates that may be involved in stromal/matrix-enhanced metastasis formation/breast cancer development. This method therefore identified biological processes that occur during mammary gland involution, which may be critical in promoting breast cancer metastasis that could form a basis for future investigation, and supports a role for copper in breast cancer development.

Local recurrence after breast-conserving therapy in relation to gene expression patterns in a large series of patients

PURPOSE

The majority of patients with early-stage breast cancer are treated with breast-conserving therapy (BCT). Several clinical risk factors are associated with local recurrence (LR) after BCT but are unable to explain all instances of LR after BCT. Here, gene expression microarrays are used to identify novel risk factors for LR after BCT.

EXPERIMENTAL DESIGN

Gene expression profiles of 56 primary invasive breast carcinomas from patients who developed a LR after BCT were compared with profiles of 109 tumors from patients who did not develop a LR after BCT. Both unsupervised and supervised methods of classification were used to separate patients into groups corresponding to disease outcome. In addition, for 15 patients, the gene expression profile in the recurrence was compared with that of the primary tumor.

RESULTS

The two main clusters found by hierarchical cluster analysis of all 165 primary invasive breast carcinomas revealed no association with LR. Predefined gene sets (molecular subtypes and "chromosomal instability" signature) are associated with LR (P = 0.0002 and 0.003, respectively). Significant analysis of microarrays revealed an association between LR and cell proliferation, not captured by histologic grading. Class prediction analysis constructed a gene classifier, which was successfully validated, cross-platform, on an independent data set of 161 patients (log-rank P = 0.041). In multivariate analysis, young age was the only independent predictor of LR.

CONCLUSIONS

We have constructed and cross-platform validated a gene expression profile predictive for LR after BCT, which is characterized by genes involved in cell proliferation but not a surrogate for high histologic grade.

[Genome-wide expression profiling as a clinical tool: are we there yet?]

Breast cancer is a heterogeneous disease, encompassing a plethora of histological types and clinical courses. Current histopathological classification systems for breast cancer are based on descriptive entities that are of prognostic significance. Few prognostic markers beyond those offered by histopathological analysis are available. Furthermore, a very limited armamentarium of predictive biomarkers has been introduced in clinical practice. High throughput molecular technologies are reshaping our understanding of breast cancer, of which microarray-based gene expression has received the most attention. This method has been successfully used to derive a molecular taxonomy for breast cancer, which has provided interesting insights into the biology of the disease. Microarray-based class prediction studies have generated a multitude of prognostic/predictive signatures. Although these signatures have not been fully translated to clinical practice as yet, they herald the promise of an improvement in breast cancer treatment decision-making. It should be noted, however, that most of the signatures developed to date seem to have discriminatory power almost restricted to oestrogen receptor-positive disease. This review addresses the contribution of gene expression profiling to our understanding of breast cancer and its clinical management and what has yet to be done for these classifiers to be incorporated in clinical practice.

Characterization of a naturally occurring breast cancer subset enriched in epithelial-to-mesenchymal transition and stem cell characteristics

Metaplastic breast cancers (MBC) are aggressive, chemoresistant tumors characterized by lineage plasticity. To advance understanding of their pathogenesis and relatedness to other breast cancer subtypes, 28 MBCs were compared with common breast cancers using comparative genomic hybridization, transcriptional profiling, and reverse-phase protein arrays and by sequencing for common breast cancer mutations. MBCs showed unique DNA copy number aberrations compared with common breast cancers. PIK3CA mutations were detected in 9 of 19 MBCs (47.4%) versus 80 of 232 hormone receptor-positive cancers (34.5%; P = 0.32), 17 of 75 HER-2-positive samples (22.7%; P = 0.04), 20 of 240 basal-like cancers (8.3%; P < 0.0001), and 0 of 14 claudin-low tumors (P = 0.004). Of 7 phosphatidylinositol 3-kinase/AKT pathway phosphorylation sites, 6 were more highly phosphorylated in MBCs than in other breast tumor subtypes. The majority of MBCs displayed mRNA profiles different from those of the most common, including basal-like cancers. By transcriptional profiling, MBCs and the recently identified claudin-low breast cancer subset constitute related receptor-negative subgroups characterized by low expression of GATA3-regulated genes and of genes responsible for cell-cell adhesion with enrichment for markers linked to stem cell function and epithelial-to-mesenchymal transition (EMT). In contrast to other breast cancers, claudin-low tumors and most MBCs showed a significant similarity to a "tumorigenic" signature defined using CD44(+)/CD24(-) breast tumor-initiating stem cell-like cells. MBCs and claudin-low tumors are thus enriched in EMT and stem cell-like features, and may arise from an earlier, more chemoresistant breast epithelial precursor than basal-like or luminal cancers. PIK3CA mutations, EMT, and stem cell-like characteristics likely contribute to the poor outcomes of MBC and suggest novel therapeutic targets.

Genetic alterations and oncogenic pathways associated with breast cancer subtypes

Breast cancers can be divided into subtypes with important implications for prognosis and treatment. We set out to characterize the genetic alterations observed in different breast cancer subtypes and to identify specific candidate genes and pathways associated with subtype biology. mRNA expression levels of estrogen receptor, progesterone receptor, and HER2 were shown to predict marker status determined by immunohistochemistry and to be effective at assigning samples to subtypes. HER2(+) cancers were shown to have the greatest frequency of high-level amplification (independent of the ERBB2 amplicon itself), but triple-negative cancers had the highest overall frequencies of copy gain. Triple-negative cancers also were shown to have more frequent loss of phosphatase and tensin homologue and mutation of RB1, which may contribute to genomic instability. We identified and validated seven regions of copy number alteration associated with different subtypes, and used integrative bioinformatics analysis to identify candidate oncogenes and tumor suppressors, including ERBB2, GRB7, MYST2, PPM1D, CCND1, HDAC2, FOXA1, and RASA1. We tested the candidate oncogene MYST2 and showed that it enhances the anchorage-independent growth of breast cancer cells. The genome-wide and region-specific differences between subtypes suggest the differential activation of oncogenic pathways.

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.