Comparative genomic hybridization analysis of benign and invasive male breast neoplasms

Comparative genomic hybridization (CGH) analysis was performed for the identification of chromosomal imbalances in two benign gynecomastias and one malignant breast carcinoma derived from patients with male breast disease and compared with cytogenetic analysis in two of the three cases. CGH analysis demonstrated overrepresentation of 8q in all three cases. One case of gynecomastia presented gain of 1p34.3similar topter. 11p14similar toq12. and 17p11.2similar toqter, and loss of 1q41similar toqter and 4q33similar toqter. The other gynecomastia presented del(1)(q41) as detected by both cytogenetic and CGH analysis. CGH analysis of the invasive ductal carcinoma confirmed a gain of 17p11.2similar toqter previously detected by cytogenetic analysis. These regions showed some similarity in their pattern of imbalance to the chromosomal alterations described in female and male breast cancer. (C) 2002 Elsevier B.V. All rights reserved.

Methylation profile of TP53 regulatory pathway and mtDNA alterations in breast cancer patients lacking TP53 mutations.

The present study investigated promoter hypermethylation of TP53 regulatory pathways providing a potential link between epigenetic changes and mitochondrial DNA (mtDNA) alterations in breast cancer patients lacking a TP53 mutation. The possibility of using the cancer-specific alterations in serum samples as a blood-based test was also explored. Triple-matched samples (cancerous tissues, matched adjacent normal tissues and serum samples) from breast cancer patients were screened for TP53 mutations, and the promoter methylation profile of P14(ARF), MDM2, TP53 and PTEN genes was analyzed as well as mtDNA alterations, including D-loop mutations and mtDNA content. In the studied cohort, no mutation was found in TP53 (DNA-binding domain). Comparison of P14(ARF) and PTEN methylation patterns showed significant hypermethylation levels in tumor tissues (P < 0.05 and <0.01, respectively) whereas the TP53 tumor suppressor gene was not hypermethylated (P < 0.511). The proportion of PTEN methylation was significantly higher in serum than in the normal tissues and it has a significant correlation to tumor tissues (P < 0.05). mtDNA analysis revealed 36.36% somatic and 90.91% germline mutations in the D-loop region and also significant mtDNA depletion in tumor tissues (P < 0.01). In addition, the mtDNA content in matched serum was significantly lower than in the normal tissues (P < 0.05). These data can provide an insight into the management of a therapeutic approach based on the reversal of epigenetic silencing of the crucial genes involved in regulatory pathways of the tumor suppressor TP53. Additionally, release of significant aberrant methylated PTEN in matched serum samples might represent a promising biomarker for breast cancer.

Identification of estrogen-responsive DNA sequences by transient expression experiments in a human breast cancer cell line.

The expression of a hybrid gene formed by the promoter region of the Xenopus laevis vitellogenin gene B1 and the CAT coding region is regulated by estrogen when the gene is transfected into hormone-responsive MCF-7 cells. Furthermore, the 5' flanking region of the gene B1 alone can confer inducibility to heterologous promoters, although to a varying extent depending on the promoter used. Deletion mapping of he vitellogenin hormone-responsive sequences revealed that a 13 bp element 5'-AGTCACTGTGACC-3' at position -334 is essential for estrogen inducibility. We have shown previously that this 13 bp element is present upstream of several liver-specific estrogen-inducible genes.

Increased expression of urokinase-type plasminogen activator mRNA determines adverse prognosis in ErbB2-positive primary breast cancer.

PURPOSE: To evaluate and validate mRNA expression markers capable of identifying patients with ErbB2-positive breast cancer associated with distant metastasis and reduced survival. PATIENTS AND METHODS: Expression of 60 genes involved in breast cancer biology was assessed by quantitative real-time PCR (qrt-PCR) in 317 primary breast cancer patients and correlated with clinical outcome data. Results were validated subsequently using two previously published and publicly available microarray data sets with different patient populations comprising 295 and 286 breast cancer samples, respectively. RESULTS: Of the 60 genes measured by qrt-PCR, urokinase-type plasminogen activator (uPA or PLAU) mRNA expression was the most significant marker associated with distant metastasis-free survival (MFS) by univariate Cox analysis in patients with ErbB2-positive tumors and an independent factor in multivariate analysis. Subsequent validation in two microarray data sets confirmed the prognostic value of uPA in ErbB2-positive tumors by both univariate and multivariate analysis. uPA mRNA expression was not significantly associated with MFS in ErbB2-negative tumors. Kaplan-Meier analysis showed in all three study populations that patients with ErbB2-positive/uPA-positive tumors exhibited significantly reduced MFS (hazard ratios [HR], 4.3; 95% CI, 1.6 to 11.8; HR, 2.7; 95% CI, 1.2 to 6.2; and, HR, 2.8; 95% CI, 1.1 to 7.1; all P < .02) as compared with the group with ErbB2-positive/uPA-negative tumors who exhibited similar outcome to those with ErbB2-negative tumors, irrespective of uPA status. CONCLUSION: After evaluation of 898 breast cancer patients, uPA mRNA expression emerged as a powerful prognostic indicator in ErbB2-positive tumors. These results were consistent among three independent study populations assayed by different techniques, including qrt-PCR and two microarray platforms.

Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.

BACKGROUND: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profiles of breast cancers and whether such profiles could be used to improve histologic grading. METHODS: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. RESULTS: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P < .001, log-rank test). CONCLUSIONS: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value.

Identification of molecular apocrine breast tumours by microarray analysis.

Previous microarray studies on breast cancer identified multiple tumour classes, of which the most prominent, named luminal and basal, differ in expression of the oestrogen receptor alpha gene (ER). We report here the identification of a group of breast tumours with increased androgen signalling and a 'molecular apocrine' gene expression profile. Tumour samples from 49 patients with large operable or locally advanced breast cancers were tested on Affymetrix U133A gene expression microarrays. Principal components analysis and hierarchical clustering split the tumours into three groups: basal, luminal and a group we call molecular apocrine. All of the molecular apocrine tumours have strong apocrine features on histological examination (P=0.0002). The molecular apocrine group is androgen receptor (AR) positive and contains all of the ER-negative tumours outside the basal group. Kolmogorov-Smirnov testing indicates that oestrogen signalling is most active in the luminal group, and androgen signalling is most active in the molecular apocrine group. ERBB2 amplification is commoner in the molecular apocrine than the other groups. Genes that best split the three groups were identified by Wilcoxon test. Correlation of the average expression profile of these genes in our data with the expression profile of individual tumours in four published breast cancer studies suggest that molecular apocrine tumours represent 8-14% of tumours in these studies. Our data show that it is possible with microarray data to divide mammary tumour cells into three groups based on steroid receptor activity: luminal (ER+ AR+), basal (ER- AR-) and molecular apocrine (ER- AR+).

Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade.

PURPOSE: A number of microarray studies have reported distinct molecular profiles of breast cancers (BC), such as basal-like, ErbB2-like, and two to three luminal-like subtypes. These were associated with different clinical outcomes. However, although the basal and the ErbB2 subtypes are repeatedly recognized, identification of estrogen receptor (ER) -positive subtypes has been inconsistent. Therefore, refinement of their molecular definition is needed. MATERIALS AND METHODS: We have previously reported a gene expression grade index (GGI), which defines histologic grade based on gene expression profiles. Using this algorithm, we assigned ER-positive BC to either high-or low-genomic grade subgroups and compared these with previously reported ER-positive molecular classifications. As further validation, we classified 666 ER-positive samples into subtypes and assessed their clinical outcome. RESULTS: Two ER-positive molecular subgroups (high and low genomic grade) could be defined using the GGI. Despite tracking a single biologic pathway, these were highly comparable to the previously described luminal A and B classification and significantly correlated to the risk groups produced using the 21-gene recurrence score. The two subtypes were associated with statistically distinct clinical outcome in both systemically untreated and tamoxifen-treated populations. CONCLUSION: The use of genomic grade can identify two clinically distinct ER-positive molecular subtypes in a simple and highly reproducible manner across multiple data sets. This study emphasizes the important role of proliferation-related genes in predicting prognosis in ER-positive BC.

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data.

INTRODUCTION: Diverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells. METHODS: Malignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays. RESULTS: MPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours. CONCLUSION: Using highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.

Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer.

BACKGROUND: A 70-gene signature was previously shown to have prognostic value in patients with node-negative breast cancer. Our goal was to validate the signature in an independent group of patients. METHODS: Patients (n = 307, with 137 events after a median follow-up of 13.6 years) from five European centers were divided into high- and low-risk groups based on the gene signature classification and on clinical risk classifications. Patients were assigned to the gene signature low-risk group if their 5-year distant metastasis-free survival probability as estimated by the gene signature was greater than 90%. Patients were assigned to the clinicopathologic low-risk group if their 10-year survival probability, as estimated by Adjuvant! software, was greater than 88% (for estrogen receptor [ER]-positive patients) or 92% (for ER-negative patients). Hazard ratios (HRs) were estimated to compare time to distant metastases, disease-free survival, and overall survival in high- versus low-risk groups. RESULTS: The 70-gene signature outperformed the clinicopathologic risk assessment in predicting all endpoints. For time to distant metastases, the gene signature yielded HR = 2.32 (95% confidence interval [CI] = 1.35 to 4.00) without adjustment for clinical risk and hazard ratios ranging from 2.13 to 2.15 after adjustment for various estimates of clinical risk; clinicopathologic risk using Adjuvant! software yielded an unadjusted HR = 1.68 (95% CI = 0.92 to 3.07). For overall survival, the gene signature yielded an unadjusted HR = 2.79 (95% CI = 1.60 to 4.87) and adjusted hazard ratios ranging from 2.63 to 2.89; clinicopathologic risk yielded an unadjusted HR = 1.67 (95% CI = 0.93 to 2.98). For patients in the gene signature high-risk group, 10-year overall survival was 0.69 for patients in both the low- and high-clinical risk groups; for patients in the gene signature low-risk group, the 10-year survival rates were 0.88 and 0.89, respectively. CONCLUSIONS: The 70-gene signature adds independent prognostic information to clinicopathologic risk assessment for patients with early breast cancer.

Low E2F1 transcript levels are a strong determinant of favorable breast cancer outcome.

INTRODUCTION: We investigated whether mRNA levels of E2F1, a key transcription factor involved in proliferation, differentiation and apoptosis, could be used as a surrogate marker for the determination of breast cancer outcome. METHODS: E2F1 and other proliferation markers were measured by quantitative RT-PCR in 317 primary breast cancer patients from the Stiftung Tumorbank Basel. Correlations to one another as well as to the estrogen receptor and ERBB2 status and clinical outcome were investigated. Results were validated and further compared with expression-based prognostic profiles using The Netherlands Cancer Institute microarray data set reported by Fan and colleagues. RESULTS: E2F1 mRNA expression levels correlated strongly with the expression of other proliferation markers, and low values were mainly found in estrogen receptor-positive and ERBB2-negative phenotypes. Patients with low E2F1-expressing tumors were associated with favorable outcome (hazard ratio = 4.3 (95% confidence interval = 1.8-9.9), P = 0.001). These results were consistent in univariate and multivariate Cox analyses, and were successfully validated in The Netherlands Cancer Institute data set. Furthermore, E2F1 expression levels correlated well with the 70-gene signature displaying the ability of selecting a common subset of patients at good prognosis. Breast cancer patients' outcome was comparably predictable by E2F1 levels, by the 70-gene signature, by the intrinsic subtype gene classification, by the wound response signature and by the recurrence score. CONCLUSION: Assessment of E2F1 at the mRNA level in primary breast cancer is a strong determinant of breast cancer patient outcome. E2F1 expression identified patients at low risk of metastasis irrespective of the estrogen receptor and ERBB2 status, and demonstrated similar prognostic performance to different gene expression-based predictors.

Lack of EGFR-activating mutations in European patients with triple-negative breast cancer could emphasise geographic and ethnic variations in breast cancer mutation profiles.

INTRODUCTION: Triple-negative breast cancers (TNBCs) are characterised by lack of expression of hormone receptors and epidermal growth factor receptor 2 (HER-2). As they frequently express epidermal growth factor receptors (EGFRs), anti-EGFR therapies are currently assessed for this breast cancer subtype as an alternative to treatments that target HER-2 or hormone receptors. Recently, EGFR-activating mutations have been reported in TNBC specimens in an East Asian population. Because variations in the frequency of EGFR-activating mutations in East Asians and other patients with lung cancer have been described, we evaluated the EGFR mutational profile in tumour samples from European patients with TNBC. METHODS: We selected from a DNA tumour bank 229 DNA samples isolated from frozen, histologically proven and macrodissected invasive TNBC specimens from European patients. PCR and high-resolution melting (HRM) analyses were used to detect mutations in exons 19 and 21 of EGFR. The results were then confirmed by bidirectional sequencing of all samples. RESULTS: HRM analysis allowed the detection of three EGFR exon 21 mutations, but no exon 19 mutations. There was 100% concordance between the HRM and sequencing results. The three patients with EGFR exon 21 abnormal HRM profiles harboured the rare R836R SNP, but no EGFR-activating mutation was identified. CONCLUSIONS: This study highlights variations in the prevalence of EGFR mutations in TNBC. These variations have crucial implications for the design of clinical trials involving anti-EGFR treatments in TNBC and for identifying the potential target population.

New insights into the mechanisms of organ-specific breast cancer metastasis.

Despite the substantial advances obtained in the treatment of localized malignancies, metastatic disease still lacks effective treatment and remains the primary cause of cancer mortality, including in breast cancer. Thus, in order to improve the survival of cancer patients it is necessary to effectively improve prevention or treatment of metastasis. To achieve this goal, complementary strategies can be envisaged: the first one is the eradication of established metastases by adding novel modalities to current treatments, such as immunotherapy or targeted therapies. A second one is to prevent tumor cell dissemination to secondary organs by targeting specific steps governing the metastatic cascade and organ-specific tropism. A third one is to block the colonization of secondary organs and subsequent cancer cell growth by impinging on the ability of disseminated cancer cells to adapt to the novel microenvironment. To obtain optimal results it might be necessary to combine these strategies. The development of therapeutic approaches aimed at preventing dissemination and organ colonization requires a deeper understanding of the specific genetic events occurring in cancer cells and of the host responses that co-operate to promote metastasis formation. Recent developments in the field disclosed novel mechanisms of metastasis. In particular the crosstalk between disseminated cancer cells and the host microenvironment is emerging as a critical determinant of metastasis. The identification of tissue-specific signals involved in metastatic progression will open the way to new therapeutic strategies. Here, we will review recent progress in the field, with particular emphasis on the mechanisms of organ specific dissemination and colonization of breast cancer.

Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen.

Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+ BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.Results: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95% CI: 1.29-3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.Conclusion: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.

Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair.

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.