Refinement of breast cancer classification by molecular characterization of histological special types

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.

The Journal of Pathology 2008 Jeremy Jass Prize for Research Excellence in Pathology

The first Jass Prize for Research Excellence has been awarded to a group from Hannover in Germany. These authors discovered the epigenetic inactivation of microRNA gene hsa-mir-9-1 in human breast cancer and characterized its biological and clinical relevance. This frequent epigenetic silencing was found to occur early in the development of breast cancer, and illustrates another mechanism by which tumour development is influenced by genes that operate without expression as proteins.

Molecular markers of breast axillary lymph node metastasis

In breast cancer, axillary lymph node status is one of the most important prognostic variables and a crucial component to the staging system. Several clinico-histopathological parameters are considered to be strong predictors of metastasis; however, they fail to accurately classify breast tumors according to their clinical behavior and to predict which patients will have disease recurrence. Methods based on genome-wide microarray analyses have been used to identify molecular markers with respect to the development of axillary lymph node metastasis. Most of these markers can be detected in the primary tumors, which can potentially lead to the ability to identify patients at the time of diagnosis who are at high risk for lymph node metastasis, allowing for early intervention and more suitable adjuvant treatments.

Disease signatures are robust across tissues and experiments

Meta-analyses combining gene expression microarray experiments offer new insights into the molecular pathophysiology of disease not evident from individual experiments. Although the established technical reproducibility of microarrays serves as a basis for meta-analysis, pathophysiological reproducibility across experiments is not well established. In this study, we carried out a large-scale analysis of disease-associated experiments obtained from NCBI GEO, and evaluated their concordance across a broad range of diseases and tissue types. On evaluating 429 experiments, representing 238 diseases and 122 tissues from 8435 microarrays, we find evidence for a general, pathophysiological concordance between experiments measuring the same disease condition. Furthermore, we find that the molecular signature of disease across tissues is overall more prominent than the signature of tissue expression across diseases. The results offer new insight into the quality of public microarray data using pathophysiological metrics, and support new directions in meta-analysis that include characterization of the commonalities of disease irrespective of tissue, as well as the creation of multi-tissue systems models of disease pathology using public data.

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.

Gene expression meta-analysis supports existence of molecular apocrine breast cancer with a role for androgen receptor and implies interactions with ErbB family

Background

Pathway discovery from gene expression data can provide important insight into the relationship between signaling networks and cancer biology. Oncogenic signaling pathways are commonly inferred by comparison with signatures derived from cell lines. We use the Molecular Apocrine subtype of breast cancer to demonstrate our ability to infer pathways directly from patients' gene expression data with pattern analysis algorithms.

Methods

We combine data from two studies that propose the existence of the Molecular Apocrine phenotype. We use quantile normalization and XPN to minimize institutional bias in the data. We use hierarchical clustering, principal components analysis, and comparison of gene signatures derived from Significance Analysis of Microarrays to establish the existence of the Molecular Apocrine subtype and the equivalence of its molecular phenotype across both institutions. Statistical significance was computed using the Fasano & Franceschini test for separation of principal components and the hypergeometric probability formula for significance of overlap in gene signatures. We perform pathway analysis using LeFEminer and Backward Chaining Rule Induction to identify a signaling network that differentiates the subset. We identify a larger cohort of samples in the public domain, and use Gene Shaving and Robust Bayesian Network Analysis to detect pathways that interact with the defining signal.

Results

We demonstrate that the two separately introduced ER^- breast cancer subsets represent the same tumor type, called Molecular Apocrine breast cancer. LeFEminer and Backward Chaining Rule Induction support a role for AR signaling as a pathway that differentiates this subset from others. Gene Shaving and Robust Bayesian Network Analysis detect interactions between the AR pathway, EGFR trafficking signals, and ErbB2.

Conclusion

We propose criteria for meta-analysis that are able to demonstrate statistical significance in establishing molecular equivalence of subsets across institutions. Data mining strategies used here provide an alternative method to comparison with cell lines for discovering seminal pathways and interactions between signaling networks. Analysis of Molecular Apocrine breast cancer implies that therapies targeting AR might be hampered if interactions with ErbB family members are not addressed.

Sam-pointed domain containing Ets transcription factor in luminal breast cancer pathogenesis

We previously described frequent overexpression of Sam-pointed domain containing Ets transcription factor (SPDEF), also known as PDEF, in human breast cancer, and suggested a role for this transcription factor in breast tumor progression. To seek evidence in support of this hypothesis, the MCF-12A breast epithelial cell line was transfected with an SPDEF expression plasmid or with control vector plasmid and the transfected cells tested for their tumorigenic growth in vivo. The data showed that SPDEF expression in MCF-12A cells induced accelerated tumor growth in severe combined immune deficient mice compared with vector-transfected MCF-12A cells. Furthermore, Gene Expression Omnibus and Oncomine databases were mined to determine any correlation between SPDEF expression levels and clinical outcome. High SPDEF expression correlated with poor overall survival of patients with estrogen receptor+ breast cancer, in three independent data sets. In contrast, little correlation was observed between SPDEF expression and cancer relapse or remote metastases. SPDEF expression was further found to be restricted to tumors arising in the luminal epithelial lineage including estrogen receptor+ luminal subtype breast tumors, Her2/neu-positive tumors, and apocrine carcinomas. In contrast, little SPDEF expression was found in the basal subtype of breast tumors. Based on these results, we hypothesize that SPDEF has a function in the specification of the progenitor cells of the luminal epithelial lineage that become targets of oncogenesis in luminal breast cancer.

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.

Mixed micropapillary-ductal carcinomas of the breast: a genomic and immunohistochemical analysis of morphologically distinct components

Micropapillary carcinomas (MPCs) can present as a rare histological special type of breast cancer; however, this histological type is more frequently found admixed with invasive ductal carcinomas of no special type (IDC-NSTs). We have previously demonstrated that pure MPCs constitute a distinct entity at the morphological and genetic levels. Here, we sought to determine whether mixed MPCs have genomic aberrations similar to those found in pure MPCs, and to investigate whether the distinct morphological components of MPCs harbour different genetic aberrations. Using high-resolution microarray comparative genomic hybridization (aCGH), we profiled a series of 10 MPCs of mixed histology and 20 IDC-NSTs matched for grade and oestrogen receptor (ER) status. In addition, we generated tissue microarrays containing a series of 24 pure and 40 mixed MPCs and performed immunohistochemical analysis with ER, progesterone receptor (PR), Ki-67, HER2, cytokeratin (CK) 5/6, CK14, CK17, EGFR, topoisomerase-IIalpha, cyclin D1, caveolin-1 and E-cadherin antibodies. In situ hybridization was employed to evaluate the prevalence of HER2, TOP2A, EGFR, CCND1, MYC and FGFR1 gene amplification. Our results demonstrate that mixed MPCs harbour similar patterns of genomic aberrations and phenotype (82.5% luminal and 17.5% HER2) compared to pure MPCs. A comparison between the distinct morphological components of mixed MPCs in a pairwise fashion revealed that both components harbour strikingly similar genomic profiles. When compared to grade- and ER-matched IDC-NSTs, mixed MPCs significantly more frequently harboured amplification of multiple regions on 8q (adjusted Fisher's p value < 0.05). Furthermore, mixed MPCs displayed higher proliferative rates than grade- and ER-matched IDC-NSTs. Our results suggest that micropapillary differentiation in breast cancer may identify a subgroup of more aggressive ER-positive breast carcinomas, even in those featuring a mixed histology, and that mixed MPCs are more closely related to pure MPCs than to IDC-NSTs.

Breast carcinoma--rare types: review of the literature

Invasive breast cancer is a heterogeneous disease in its presentation, pathological classification and clinical course. However, there are more than a dozen variants which are less common but still very well defined by the World Health Organization (WHO) classification. The rarity of many of these neoplasms does not allow large or randomized studies to define the optimal treatment. Many of the descriptions of these cancers are from case reports and small series. Our review brings updated information on 16 epithelial subtypes as classified by the WHO system with a very concise histopathology description and parameters helpful in the clinic. The aim of our review is to provide a tool for breast cancer caregivers which will enable a better understanding of the disease and its optimal approach to therapy. This may also stand as a clinical framework for a future understanding of these rarer breast cancers when gene analysis work is reported.

Expression of FOXA1 and GATA-3 in breast cancer: the prognostic significance in hormone receptor-negative tumours

Introduction

The expression of additional genes, other than oestrogen receptor (ER), may be important to the hormone-responsive phenotype of breast cancer. Microarray analyses have revealed that forkhead box A1 (FOXA1) and GATA binding protein 3 (GATA-3) are expressed in close association with ERα, both encoding for transcription factors with a potential involvement in the ERα-mediated action in breast cancer. The purpose of this study was to explore if the expression of FOXA1 and GATA-3 may provide an opportunity to stratify subsets of patients that could have better outcome, among the ERα-negative/poor prognosis breast cancer group.

Methods

We evaluate FOXA1 and GATA-3 expression in 249 breast carcinomas by immunohistochemistry, associating it with breast cancer molecular markers, clinicopathological features and patient's survival. The clinicopathological features and immunohistochemical markers of the tumours were compared using the chi-square test and ANOVA. Disease-free survival was analysed through Kaplan–Meier survival curves and Cox regression.

Results

FOXA1 expression was demonstrated in 42% of invasive carcinomas, while GATA-3 was detected in 48% of the cases. FOXA1 expression was inversely associated with tumour size, Nottingham Prognostic Index, histological grade, lymph vascular invasion, lymph node stage and human epidermal growth factor receptor-2 (HER-2) overexpression, while GATA-3 expression showed inverse association with histological grade and HER-2. Both FOXA1 and GATA-3 were directly associated with ERα and progesterone receptor. Among FOXA1-positive tumours, 83.1% are comprised in the luminal A subtype, similar to GATA-3 where 87.7% of positive tumours were classified within this molecular subtype. In the subset of ERα-negative patients, those who were FOXA1-negative had a 3.61-fold increased risk of breast cancer recurrence when compared with the FOXA1-positive.

Conclusions

FOXA1 was a significant predictor of good outcome in breast cancer, whereas GATA-3 was an important luminal marker. The expression of FOXA1 may be used for risk stratification among ERα-negative patients.

Mucinous Lesions of the Breast

Breast lesions associated with extracellular mucin production are uncommon and constitute a wide spectrum of lesions ranging from benign cyst to mucinous carcinoma. Intracytoplasmic mucin can be seen rarely in benign metaplasias but is a common finding in invasive and in situ carcinomas. In this article, we discuss the differential diagnosis of breast lesions associated with mucin production and other entities that show histologic changes that mimic mucin production.

Gene and chromosomal alterations in sporadic breast cancer: correlation with histopathological features and implications for genesis and progression

A number of gene and chromosome alterations have been identified in sporadic breast carcinomas, and their clinical implications have been investigated. Changes in proto-oncogenes and tumor-suppressor genes, e.g., HER2, p53, and E-cadherin, and various numerical and structural chromosome alterations are strongly correlated with histological type and grade in breast carcinomas. The amount of information on these alterations has been dramatically increased by the introduction of high-throughput molecular cytogenetic approaches. In the near future, breast cancers will be classified into specific groups according to their profile of gene and chromosome alterations, allowing more effective personalized therapies targeting the associated molecular pathways.

[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.

Unraveling breast cancer heterogeneity through transcriptomic and epigenomic analysis

Breast cancer diversity is histologically evident as various proliferative benign lesions, in situ carcinomas, and invasive carcinomas that may develop into distant metastases. Breast tumor molecular subtypes have been defined by genome-wide expression microarray technology and reveal associations between genetic alterations and the malignant phenotype. Early work has been conducted to use subtype-specific biomarkers to elucidate targeted treatment options early in the course of breast cancer progression. Additionally, DNA methylation is an epigenetic modification that contributes to breast cancer progression by transcriptionally silencing certain tumor suppressor genes. Among the genes characterized as targets for silencing are well-established tumor suppressors such as RASSF1A, RARB, SFN, and TGM2. Measuring elevated gene copy number and aberrant gene promoter methylation can further facilitate characterization of breast tumor molecular subtype; however, profiling of breast tumors based on epigenetic criteria has yet to be established. Epigenomic analysis has been investigated for clinical applicability, and it has great promise when used in combination with minimally invasive techniques for both diagnostic and prognostic purposes.

Novel therapeutic strategy for breast cancer: mammalian target of rapamycin inhibition

BACKGROUND

Mammalian target of rapamycin (mTOR) plays a central role in regulating cellular protein synthesis. Dysregulation of mTOR signaling pathway is strongly associated with tumorigenesis, angiogenesis, tumor progression and drug resistance. Inhibition of mTOR might not only promote cell cycle arrest, but also sensitize resistant cancer cells to chemotherapeutic and other targeted agents.

OBJECTIVE

To review and summarize the mechanism of mTOR on regulation of protein synthesis and latest clinical data, and to discuss the novel therapeutic strategy for the use of mTOR inhibitors in the treatment of breast cancer.

METHODS

A review of published literatures and conference abstracts obtained from MEDLINE, American Society of Clinical Oncology Meeting and San Antonio Breast Cancer Symposia proceedings for results of previous preclinical and latest clinical studies of mTOR inhibition in breast cancer was performed.

CONCLUSIONS

mTOR inhibitors seemed to be potentially useful for the treatment of breast cancer with acceptable safety profile. The challenge remains the identification of suitable candidates with different phenotypes. More structured studies incorporating molecular, clinical and translational research need to be initiated. Future research on mTOR inhibitors for breast cancer should focus on the evaluation of optimal schedule, patient selection and combination strategies to maximize the use of this new class of targeted agents.

Pleomorphic lobular carcinoma of the breast: molecular pathology and clinical impact

Pleomorphic lobular carcinoma of the breast is a recently described morphological variant of classic invasive lobular carcinoma with an aggressive behavior. Morphologically, pleomorphic lobular carcinoma elicits a similar pattern of infiltrative growth as invasive lobular carcinoma, yet neoplastic cells have marked nuclear atypia and pleomorphism. Pleomorphic lobular carcinoma and the in situ counterpart, pleomorphic lobular carcinoma in situ, are frequently hormone receptor (estrogen-, progesterone- and androgen-receptor)-positive and E-cadherin and β-catenin-negative, attaining to their lobular nature. Tumors can also be positive for HER2, p53, ki67 and GCDFP-15 and harbor frequent chromosomal alterations involving gains on 1q and 16p, losses on 11q and 16q, and genomic amplifications in the region of 8q24, 11q13, 12q13, 17q12 and 20q13. Recent gene-expression profiling classified pleomorphic lobular carcinoma as ‘molecular apocrine’ tumors reflecting the frequent apocrine differentiation of the tumors. In support for the aggressive biological features described for pleomorphic lobular carcinoma, accumulating clinical data demonstrate that it has an aggressive clinical course. It is now important to define the most appropriate management strategy for patients diagnosed with pleomorphic lobular carcinoma.

Molecular characterization of apocrine carcinoma of the breast: validation of an apocrine protein signature in a well-defined cohort

Invasive apocrine carcinomas (IACs), as defined by morphological features, correspond to 0.3-4% of all invasive ductal carcinomas (IDC), and despite the fact that they are histologically distinct from other breast lesions there are currently no standard molecular criteria available for their diagnosis and no unequivocal information as to their prognosis. In an effort to address these concerns we have been using protein expression profiling technologies in combination with mass spectrometry and immunohistochemistry (IHC) to discover specific biomarkers that could allow us to molecularly characterize these lesions as well as to dissect some of the steps in the processes underlying breast apocrine metaplasia and development of precancerous apocrine lesions. Establishing these apocrine-specific markers as best practice for the routine pathology evaluation of breast cancer, however, will require their validation in large cohorts of patients. Towards this goal we have composed a panel of antibodies against components of an apocrine protein signature that includes probes against the apocrine-specific markers 15-prostaglandin dehydrogenase (15-PGDH), and acyl-CoA synthetase medium-chain family member 1 (ACSM1), in addition to a set of categorizing markers that are consistently expressed (AR, CD24) or not expressed (ERα, PgR, Bcl-2, and GATA-3) by apocrine metaplasia in benign breast lesions and apocrine sweat glands. This panel was used to analyze a well-defined cohort consisting of 14 apocrine ductal carcinoma in situ (ADCIS), and 33 IACs diagnosed at the Cancer Institute Hospital, Tokyo between 1997 and 2001. Samples were originally classified on the basis of cellular morphology with all cases having more than 90% of the tumour cells exhibiting cytological features typical of apocrine cells. Using the expression of 15-PGDH and/or ACSM1 as the main criterion, but taking into account the expression of other markers, we were able to identify unambiguously 13 out of 14 ADCIS (92.9%) and 20 out of 33 (60.6%) IAC samples, respectively, as being of apocrine origin. Our results demonstrate that IACs correspond to a distinct, even if heterogeneous, molecular subgroup of breast carcinomas that can be readily identified in an unbiased way using a combination of markers that recapitulate the phenotype of apocrine sweat glands (15-PGDH(+), ACSM1(+), AR(+), CD24(+), ERα(-), PgR(-), Bcl-2(-), and GATA-3(-)). These results pave the way for addressing issues such as prognosis of IACs, patient stratification for targeted therapeutics, as well as research strategies for identifying novel therapeutic targets for developing new cancer therapies.

Triple-negative breast cancer: risk factors to potential targets

Triple-negative breast cancer has recently been recognized as an important subgroup of breast cancer with a distinct outcome and therapeutic approach when compared with other subgroups of breast cancer. Triple-negative breast cancer comprises primarily, but not exclusively, a molecularly distinct subtype of breast cancer, the basal-like subtype. We do not yet have an assay to identify basal-like breast cancer in clinical samples, so triple-negative breast cancer has become a commonly used proxy for this subtype. The molecular biology and pathophysiology of triple-negative breast cancer are not completely understood, but understanding is improving rapidly with the advent of sophisticated molecular biology platforms. Moreover, the established risk factors of breast cancer as a whole may not apply to this unique subgroup of patients. Finally, because triple-negative breast cancer is defined by the absence of a target, there are currently limitations to using a tailored therapeutic approach, leaving conventional cytotoxic therapies as the mainstay. Active preclinical and clinical research programs focus on defining the clinical behavior, delineating the risk factors, and more completely understanding the molecular biology of triple-negative breast cancer to improve prevention, optimize conventional agents, and unveil novel therapeutic targets. This CCR focus article will review the current state of the art on triple-negative breast cancer.

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

Background

Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures.

Methods

A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis.

Results

The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results.

Conclusion

The proposed meta-analysis approach has the ability to detect a set of differentially expressed genes with the least amount of within-group variability, thus providing highly stable gene lists for class prediction. Increased statistical power and stringent filtering criteria used in the present study also make identification of novel candidate genes possible and may provide further insight to improve our understanding of breast cancer development.

Breast cancer special types: why bother?

Breast cancer is a heterogeneous disease, encompassing multiple entities associated with distinct biological features and clinical behaviours. Microarray-based expression profiling analysis has been used to unravel the molecular underpinning of several characteristics of breast cancer, including its proclivity to disseminate to distant sites and the molecular basis of histological grade. Furthermore, a breast cancer molecular classification based on transcriptional analysis has been proposed. However, microarray studies have primarily analysed invasive ductal carcinomas of no special type. Histological special types of breast cancer, which account for up to 25% of all invasive breast cancers, have not been systematically studied. Despite the limited interest, in recent years it has become apparent that the histopathological characteristics of these cancers may be underpinned by distinct arrays of genetic changes, providing direct evidence for genotypic-phenotypic correlations between morphological patterns and molecular changes in breast cancer (eg t(12;15) in secretory carcinoma of the breast). Here we review the molecular characteristics of special types of breast cancer, with special emphasis on their microarray-based expression profiles and their impact on our understanding of breast cancer.

Microarray-based Gene Expression Profiling as a Clinical Tool for Breast Cancer Management: Are We There Yet?

Breast cancer is a heterogeneous disease, encompassing several histological types and clinical behaviors. Current histopathological classification systems are based on descriptive entities with prognostic significance. Few prognostic and predictive markers beyond those offered by histopathological analysis are available. High-throughput molecular technologies are reshaping our understanding of breast cancer, of which microarray-based gene expression has received most attention. This method has been used to derive a molecular taxonomy for breast cancer, which has provided interesting insights into the biology of the disease. Class prediction studies have generated a multitude of prognostic/predictive signatures, which herald the promise for an improvement in treatment decision making. However, most of the signatures developed to date seem to have discriminatory power almost restricted to estrogen receptor—positive disease. This review addresses the contribution of gene expression profiling to our understanding of breast cancer and its clinical management.

Molecular and morphological analysis of adenoid cystic carcinoma of the breast with synchronous tubular adenosis

Adenoid cystic carcinoma (ACC) of the breast is a rare tumour. Its recognition as a special type of breast carcinoma is very important because its prognosis is better than the not-otherwise-specified invasive ductal carcinoma and its treatment may not include axillary dissection. Tubular adenosis (TA) is a very rare condition of the breast that is histologically benign; however, it has been described in association with invasive ductal carcinoma. There are scant data regarding the molecular genomic alterations in ACC of the breast and no data has been presented on TA. Herein, we provide a morphological characterisation of TA arising synchronically with ACC in the breast. To characterise these lesions, we performed ultrastructural analysis, three-dimensional reconstruction and molecular analysis using immunohistochemistry and comparative genomic hybridisation. The copy number alterations found in ACC were restricted to small deletions on 16p and 17q only, whereas the TA harboured gains on 1q, 5p, 8q, 10q, 11p and 11q and losses on 1p, 10q, 11q, 12q, 14q, 15q and 16q. These molecular data highlight the genomic instability of TA, a benign florid proliferation intermingled with ACC, and do not provide evidence of molecular evolution from TA to ACC.

Metaplastic breast carcinomas are basal-like breast cancers: a genomic profiling analysis

BACKGROUND

Metaplastic breast carcinomas (MBCs) comprise a group of aggressive and chemotherapy resistant cancers characterised by neoplastic cells displaying differentiation towards squamous epithelium or mesenchymal elements. Previous histopathological and immunohistochemical analysis of MBCs suggested that these cancers would have a basal-like profile.

METHODS

We investigated the molecular subtype of 20 MBCs using microarray-based expression profiling data. These data were compared with those of 79 invasive ductal carcinomas (IDCs) of basal-like phenotype by unsupervised hierarchical clustering, supervised analysis and pathway analysis.

RESULTS

We demonstrate that 95% of all MBCs are of basal-like molecular subtype. Furthermore, unsupervised hierarchical clustering analysis and pathway analysis of the profiles of MBCs revealed that MBCs are part of the spectrum of basal-like breast cancers. Significance analysis of microarrays (SAM) identified 1,385 transcripts differentially expressed between MBCs and IDCs of basal-like phenotype. Pathway analysis using these genes revealed that DNA repair pathways, including BRCA1 pathway, PTEN, a gene whose loss of function is associated with resistance to chemotherapy, and TOP2A, the molecular target of anthracyclines, are significantly downregulated in MBCs compared to basal-like IDCs. These findings may at least in part explain the reported poor responses to chemotherapy of MBCs. Furthermore, MBCs showed significantly higher expression of genes related to myoepithelial differentiation and epithelial to mesenchymal transition (EMT).

CONCLUSIONS

Our results demonstrate that MBCs are part of the spectrum of basal-like breast carcinomas and display a myoepithelial and EMT-like molecular make-up. The reported poorer response to chemotherapeutic agents in patients with MBCs may stem from downregulated DNA damage response pathways, PTEN and TOP2A.