Distinctive patterns of Her-2/neu, c-myc, and cyclin D1 gene amplification by fluorescence in situ hybridization in primary human breast cancers

The evolution of tumour phylogenetics: principles and practice

Rapid advances in high-throughput sequencing and a growing realization of the importance of evolutionary theory to cancer genomics have led to a proliferation of phylogenetic studies of tumour progression. These studies have yielded not only new insights but also a plethora of experimental approaches, sometimes reaching conflicting or poorly supported conclusions. Here, we consider this body of work in light of the key computational principles underpinning phylogenetic inference, with the goal of providing practical guidance on the design and analysis of scientifically rigorous tumour phylogeny studies. We survey the range of methods and tools available to the researcher, their key applications, and the various unsolved problems, closing with a perspective on the prospects and broader implications of this field.

FISHtrees 3.0: Tumor Phylogenetics Using a Ploidy Probe

Advances in fluorescence in situ hybridization (FISH) make it feasible to detect multiple copy-number changes in hundreds of cells of solid tumors. Studies using FISH, sequencing, and other technologies have revealed substantial intra-tumor heterogeneity. The evolution of subclones in tumors may be modeled by phylogenies. Tumors often harbor aneuploid or polyploid cell populations. Using a FISH probe to estimate changes in ploidy can guide the creation of trees that model changes in ploidy and individual gene copy-number variations. We present FISHtrees 3.0, which implements a ploidy-based tree building method based on mixed integer linear programming (MILP). The ploidy-based modeling in FISHtrees includes a new formulation of the problem of merging trees for changes of a single gene into trees modeling changes in multiple genes and the ploidy. When multiple samples are collected from each patient, varying over time or tumor regions, it is useful to evaluate similarities in tumor progression among the samples. Therefore, we further implemented in FISHtrees 3.0 a new method to build consensus graphs for multiple samples. We validate FISHtrees 3.0 on a simulated data and on FISH data from paired cases of cervical primary and metastatic tumors and on paired breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). Tests on simulated data show improved accuracy of the ploidy-based approach relative to prior ploidyless methods. Tests on real data further demonstrate novel insights these methods offer into tumor progression processes. Trees for DCIS samples are significantly less complex than trees for paired IDC samples. Consensus graphs show substantial divergence among most paired samples from both sets. Low consensus between DCIS and IDC trees may help explain the difficulty in finding biomarkers that predict which DCIS cases are at most risk to progress to IDC. The FISHtrees software is available at ftp://ftp.ncbi.nih.gov/pub/FISHtrees.

MYC functions are specific in biological subtypes of breast cancer and confers resistance to endocrine therapy in luminal tumours

BACKGROUND

MYC is amplified in approximately 15% of breast cancers (BCs) and is associated with poor outcome. c-MYC protein is multi-faceted and participates in many aspects of cellular function and is linked with therapeutic response in BCs. We hypothesised that the functional role of c-MYC differs between molecular subtypes of BCs.

METHODS

We therefore investigated the correlation between c-MYC protein expression and other proteins involved in different cellular functions together with clinicopathological parameters, patients' outcome and treatments in a large early-stage molecularly characterised series of primary invasive BCs (n=1106) using immunohistochemistry. The METABRIC BC cohort (n=1980) was evaluated for MYC mRNA expression and a systems biology approach utilised to identify genes associated with MYC in the different BC molecular subtypes.

RESULTS

High MYC and c-MYC expression was significantly associated with poor prognostic factors, including grade and basal-like BCs. In luminal A tumours, c-MYC was associated with ATM (P=0.005), Cyclin B1 (P=0.002), PIK3CA (P=0.009) and Ki67 (P<0.001). In contrast, in basal-like tumours, c-MYC showed positive association with Cyclin E (P=0.003) and p16 (P=0.042) expression only. c-MYC was an independent predictor of a shorter distant metastases-free survival in luminal A LN+ tumours treated with endocrine therapy (ET; P=0.013). In luminal tumours treated with ET, MYC mRNA expression was associated with BC-specific survival (P=0.001). In ER-positive tumours, MYC was associated with expression of translational genes while in ER-negative tumours it was associated with upregulation of glucose metabolism genes.

CONCLUSIONS

c-MYC function is associated with specific molecular subtypes of BCs and its overexpression confers resistance to ET. The diverse mechanisms of c-MYC function in the different molecular classes of BCs warrants further investigation particularly as potential therapeutic targets.

Medoidshift clustering applied to genomic bulk tumor data

Despite the enormous medical impact of cancers and intensive study of their biology, detailed characterization of tumor growth and development remains elusive. This difficulty occurs in large part because of enormous heterogeneity in the molecular mechanisms of cancer progression, both tumor-to-tumor and cell-to-cell in single tumors. Advances in genomic technologies, especially at the single-cell level, are improving the situation, but these approaches are held back by limitations of the biotechnologies for gathering genomic data from heterogeneous cell populations and the computational methods for making sense of those data. One popular way to gain the advantages of whole-genome methods without the cost of single-cell genomics has been the use of computational deconvolution (unmixing) methods to reconstruct clonal heterogeneity from bulk genomic data. These methods, too, are limited by the difficulty of inferring genomic profiles of rare or subtly varying clonal subpopulations from bulk data, a problem that can be computationally reduced to that of reconstructing the geometry of point clouds of tumor samples in a genome space. Here, we present a new method to improve that reconstruction by better identifying subspaces corresponding to tumors produced from mixtures of distinct combinations of clonal subpopulations. We develop a nonparametric clustering method based on medoidshift clustering for identifying subgroups of tumors expected to correspond to distinct trajectories of evolutionary progression. We show on synthetic and real tumor copy-number data that this new method substantially improves our ability to resolve discrete tumor subgroups, a key step in the process of accurately deconvolving tumor genomic data and inferring clonal heterogeneity from bulk data.

Algorithms to model single gene, single chromosome, and whole genome copy number changes jointly in tumor phylogenetics

We present methods to construct phylogenetic models of tumor progression at the cellular level that include copy number changes at the scale of single genes, entire chromosomes, and the whole genome. The methods are designed for data collected by fluorescence in situ hybridization (FISH), an experimental technique especially well suited to characterizing intratumor heterogeneity using counts of probes to genetic regions frequently gained or lost in tumor development. Here, we develop new provably optimal methods for computing an edit distance between the copy number states of two cells given evolution by copy number changes of single probes, all probes on a chromosome, or all probes in the genome. We then apply this theory to develop a practical heuristic algorithm, implemented in publicly available software, for inferring tumor phylogenies on data from potentially hundreds of single cells by this evolutionary model. We demonstrate and validate the methods on simulated data and published FISH data from cervical cancers and breast cancers. Our computational experiments show that the new model and algorithm lead to more parsimonious trees than prior methods for single-tumor phylogenetics and to improved performance on various classification tasks, such as distinguishing primary tumors from metastases obtained from the same patient population.

Cancer is an evolutionary system whose growth and development is attributed to aberrations in well-known genes and to cancer-type specific genomic imbalances. Here, we present methods for reconstructing the evolution of individual tumors based on cell-to-cell variations between copy numbers of targeted regions of the genome. The methods are designed to work with fluorescence in situ hybridization (FISH), a technique that allows one to profile copy number changes in potentially thousands of single cells per study. Our work advances the prior art by developing theory and practical algorithms for building evolutionary trees of single tumors that can model gain or loss of genetic regions at the scale of single genes, whole chromosomes, or the entire genome, all common events in tumor evolution. We apply these methods on simulated and real tumor data to demonstrate substantial improvements in tree-building accuracy and in our ability to accurately classify tumors from their inferred evolutionary models. The newly developed algorithms have been released through our publicly available software, FISHtrees.

Phylogenetic analysis of multiprobe fluorescence in situ hybridization data from tumor cell populations

Motivation: Development and progression of solid tumors can be attributed to a process of mutations, which typically includes changes in the number of copies of genes or genomic regions. Although comparisons of cells within single tumors show extensive heterogeneity, recurring features of their evolutionary process may be discerned by comparing multiple regions or cells of a tumor. A useful source of data for studying likely progression of individual tumors is fluorescence in situ hybridization (FISH), which allows one to count copy numbers of several genes in hundreds of single cells. Novel algorithms for interpreting such data phylogenetically are needed, however, to reconstruct likely evolutionary trajectories from states of single cells and facilitate analysis of tumor evolution.

Results: In this article, we develop phylogenetic methods to infer likely models of tumor progression using FISH copy number data and apply them to a study of FISH data from two cancer types. Statistical analyses of topological characteristics of the tree-based model provide insights into likely tumor progression pathways consistent with the prior literature. Furthermore, tree statistics from the resulting phylogenies can be used as features for prediction methods. This results in improved accuracy, relative to unstructured gene copy number data, at predicting tumor state and future metastasis.

Availability: Source code for software that does FISH tree building (FISHtrees) and the data on cervical and breast cancer examined here are available at ftp://ftp.ncbi.nlm.nih.gov/pub/FISHtrees.

Contact:sachowdh@andrew.cmu.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Inference of tumor phylogenies from genomic assays on heterogeneous samples

Tumorigenesis can in principle result from many combinations of mutations, but only a few roughly equivalent sequences of mutations, or "progression pathways," seem to account for most human tumors. Phylogenetics provides a promising way to identify common progression pathways and markers of those pathways. This approach, however, can be confounded by the high heterogeneity within and between tumors, which makes it difficult to identify conserved progression stages or organize them into robust progression pathways. To tackle this problem, we previously developed methods for inferring progression stages from heterogeneous tumor profiles through computational unmixing. In this paper, we develop a novel pipeline for building trees of tumor evolution from the unmixed tumor data. The pipeline implements a statistical approach for identifying robust progression markers from unmixed tumor data and calling those markers in inferred cell states. The result is a set of phylogenetic characters and their assignments in progression states to which we apply maximum parsimony phylogenetic inference to infer tumor progression pathways. We demonstrate the full pipeline on simulated and real comparative genomic hybridization (CGH) data, validating its effectiveness and making novel predictions of major progression pathways and ancestral cell states in breast cancers.

RECONSTRUCTING TUMOR PHYLOGENIES FROM HETEROGENEOUS SINGLE-CELL DATA

Studies of gene expression in cancerous tumors have revealed that tumors presenting indistinguishable symptoms in the clinic can be substantially different entities at the molecular level. The ability to distinguish between these genetically distinct cancers will make possible more accurate prognoses and more finely targeted therapeutics, provided we can characterize commonly occurring cancer sub-types and the specific molecular abnormalities that produce them. We develop a new method for identifying these common tumor progression pathways by applying phylogeny inference algorithms to single-cell assays, taking advantage of information on tumor heterogeneity lost to prior microarray-based approaches. We combine this approach with expectation maximization to infer unknown parameters used in the phylogeny construction. We further develop new algorithms to merge inferred trees across different assays. We validate the expectation maximization method on simulated data and demonstrate the combined approach on a set of fluorescent in situ hybridization (FISH) data measuring cell-by-cell gene and chromosome copy numbers in a large sample of breast cancers. The results further validate the proposed computational methods by showing consistency with several previous findings on these cancers and provide novel insights into the mechanisms of tumor progression in these patients.

MYC and Breast Cancer

MYC is a key regulator of cell growth, proliferation, metabolism, differentiation, and apoptosis. MYC deregulation contributes to breast cancer development and progression and is associated with poor outcomes. Multiple mechanisms are involved in MYC deregulation in breast cancer, including gene amplification, transcriptional regulation, and mRNA and protein stabilization, which correlate with loss of tumor suppressors and activation of oncogenic pathways. The heterogeneity in breast cancer is increasingly recognized. Breast cancer has been classified into 5 or more subtypes based on gene expression profiles, and each subtype has distinct biological features and clinical outcomes. Among these subtypes, basal-like tumor is associated with a poor prognosis and has a lack of therapeutic targets. MYC is overexpressed in the basal-like subtype and may serve as a target for this aggressive subtype of breast cancer. Tumor suppressor BRCA1 inhibits MYC's transcriptional and transforming activity. Loss of BRCA1 with MYC overexpression leads to the development of breast cancer-especially, basal-like breast cancer. As a downstream effector of estrogen receptor and epidermal growth factor receptor family pathways, MYC may contribute to resistance to adjuvant therapy. Targeting MYC-regulated pathways in combination with inhibitors of other oncogenic pathways may provide a promising therapeutic strategy for breast cancer, the basal-like subtype in particular.

Applying unmixing to gene expression data for tumor phylogeny inference

BACKGROUND

While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall into a relatively small number of "sub-types," each characterized a roughly equivalent sequence of mutations by which it progresses in different patients. There is currently great interest in identifying the common sub-types and applying them to the development of diagnostics or therapeutics. Phylogenetic methods have shown great promise for inferring common patterns of tumor progression, but suffer from limits of the technologies available for assaying differences between and within tumors. One approach to tumor phylogenetics uses differences between single cells within tumors, gaining valuable information about intra-tumor heterogeneity but allowing only a few markers per cell. An alternative approach uses tissue-wide measures of whole tumors to provide a detailed picture of averaged tumor state but at the cost of losing information about intra-tumor heterogeneity.

RESULTS

The present work applies "unmixing" methods, which separate complex data sets into combinations of simpler components, to attempt to gain advantages of both tissue-wide and single-cell approaches to cancer phylogenetics. We develop an unmixing method to infer recurring cell states from microarray measurements of tumor populations and use the inferred mixtures of states in individual tumors to identify possible evolutionary relationships among tumor cells. Validation on simulated data shows the method can accurately separate small numbers of cell states and infer phylogenetic relationships among them. Application to a lung cancer dataset shows that the method can identify cell states corresponding to common lung tumor types and suggest possible evolutionary relationships among them that show good correspondence with our current understanding of lung tumor development.

CONCLUSIONS

Unmixing methods provide a way to make use of both intra-tumor heterogeneity and large probe sets for tumor phylogeny inference, establishing a new avenue towards the construction of detailed, accurate portraits of common tumor sub-types and the mechanisms by which they develop. These reconstructions are likely to have future value in discovering and diagnosing novel cancer sub-types and in identifying targets for therapeutic development.

The role of HER2 in early breast cancer metastasis and the origins of resistance to HER2-targeted therapies

The HER2 gene encodes the receptor tyrosine kinase HER2 and is often over-expressed or amplified in breast cancer. Up-regulation of HER2 contributes to tumor progression. Many aspects of tumor growth are favorably affected through activation of HER2 signaling. Indeed, HER2 plays a role in increasing proliferation and survival of the primary tumor and distant lesions which upon completion of full transformation cause metastases. P185(HER2/neu) receptors and signaling from them and associated molecules increase motility of both intravasating and extravasating cells, decrease apoptosis, enhance signaling interactions with the microenvironment, regulate adhesion, as well as a multitude of other functions. Recent experimental and clinical evidence supports the view that the spread of incompletely transformed cells occurs at a very early stage in tumor progression. This review concerns the identification and characterization of HER2, the evolution of the metastasis model, and the more recent cancer stem cell model. In particular, we review the evidence for an emerging mechanism of HER2(+) breast cancer progression, whereby the untransformed HER2-expressing cell shows characteristics of stem/progenitor cell, metastasizes, and then completes its final transformation at the secondary site.

Heritable variation of ERBB2 and breast cancer risk

Amplification of the epithelial growth factor receptor gene ERBB2 (HER2, NEU) in breast cancer is associated with a poor clinical prognosis. In mammary gland development, this receptor plays a role in ductal and lobuloalveolar differentiation. We conducted a systematic investigation of the role of genetic variation of the ERBB2 gene in breast cancer risk in a study of 842 histologically confirmed invasive breast cancer cases and 1,108 controls from the Shanghai Breast Cancer Study. We observed that the ERBB2 gene resides within a locus of high linkage disequilibrium, composed of three major ancestral haplotypes in the study population. These haplotypes are marked by simple tandem repeat and single nucleotide polymorphisms, including the missense variants I655V and P1170A. We observed a risk-modifying effect of a highly polymorphic simple tandem repeat within an evolutionarily conserved region, 4.4 kb upstream from the ERBB2 transcription start site. Under a dominant genetic model, the age-adjusted odds ratio was 1.74 (95% confidence interval, 1.27-2.37). Its association with breast cancer, and with breast cancer stratified by histology, by histologic grade, and by stage, remained significant after correction for multiple comparisons. In contrast, we observed no association of ERBB2 single nucleotide polymorphism haplotypes with breast cancer predisposition.

MYC in breast tumor progression

Breast cancer is the second leading cause of cancer deaths and is the most frequently diagnosed cancer in women of industrialized nations. Breast cancer progression is a multistep process involving genetic and epigenetic alterations that drive normal breast cells into highly malignant derivatives with metastatic potential. MYC is a proto-oncogene whose protein product contains a basic helix-loop-helix domain. MYC functions as a transcription factor regulating up to 15% of all human genes. MYC is regulated at multiple levels, and the protein is a downstream effector of several signaling pathways. In breast cancer cells, MYC target genes are involved in cell growth, transformation, angiogenesis and cell-cycle control. BRCA1 is linked to transcriptional regulation through interaction with MYC. Although the relationship between amplification and overexpression is not clearly delineated, MYC amplification is significantly correlated with aggressive tumor phenotypes and poor clinical outcomes. MYC amplification is emerging as an important predictor of response to HER2-targeted therapies and its role in BRCA1-associated breast cancer makes it an important target in basal-like/triple-negative breast cancers.

MYC amplification and TERT expression in breast tumor progression

The complex roles of genomic instability, MYC oncogene amplification, activation of telomerase, and p53 function still remain to be fully described in breast tumors. MYC stimulates the telomerase catalytic subunit, TERT, which interacts with p53. Oncogene MYC amplification analysis was performed on 27 paraffin-embedded breast tumor samples by fluorescence in situ hybridization, selected on the basis of chromosomal instability. TERT immunostaining was performed on a larger group of breast tumor sections. All tumor samples were analyzed for TP53 mutation, genomic index, S-phase fraction, and pathological stages. Amplification of MYC was detected in 16 of 27 tumors (59%) and found to be associated with TNM stages I and II (P = 0.018), genomic index > 1.5 (P = 0.033), and S-phase fraction > 5% (P = 0.020). No association was found between MYC amplification and TERT immunostaining or TP53 mutations. Analysis of TERT in 103 primary breast tumors showed > 50% nuclei immunostaining in 58% of cases. High TERT immunostaining associated with genomic index > 1.5 (P = 0.017), high S-phase fraction (P = 0.056), and TP53 mutations (P = 0.030). No association was found between TERT staining and TNM stages. This study supports early involvement of MYC amplification in breast tumor progression. Both MYC amplification and TERT expression appear to be associated with high genomic instability and proliferation. TERT association with TP53 mutations indicates that TERT activity is downregulated by functional p53 protein in breast tumors.

MYC amplification in breast cancer: a chromogenic in situ hybridisation study

AIMS

To analyse the correlation between MYC amplification and various clinicopathological features and outcome in a cohort of 245 patients with invasive breast carcinoma treated with surgery followed by anthracycline-based chemotherapy. Given the high prevalence of MYC amplification in tumours of BRCA1 mutation carriers and the similarities between these and sporadic "basal-like" carcinomas, the prevalence of MYC amplification in "basal-like" breast carcinomas was investigated.

METHODS

MYC gene copy number was assessed on tissue microarrays containing duplicate cores of 245 invasive breast carcinomas by means of chromogenic in situ hybridisation using SpotLight C-MYC amplification probe and chromosome 8 centromeric probe (CEP8). Signals were evaluated at 400x magnification; 30 morphologically unequivocal neoplastic cells in each core were counted for the presence of the gene and CEP8 probes.

RESULTS

Amplification was defined as a MYC:CEP8 ratio >2. Signals for both MYC and CEP8 were assessable in 196/245 (80%) tumours. MYC amplification was found in 19/196 cases (9.7%) and was not associated with tumour size, histological grade, positivity for oestrogen receptor, progesterone receptor, HER2, epidermal growth factor, cytokeratins 14, 5/6 and 17, MIB1 or p53. Only 4% of basal-like carcinomas showed MYC amplification, compared to 8.75% and 10.7% of luminal and HER2 tumours respectively. On univariate analysis, MYC amplification displayed a significant association with shorter metastasis-free and overall survival and proved to be an independent prognostic factor on multivariate survival analysis.

CONCLUSION

MYC amplification is not associated with "basal-like" phenotype and proved to be an independent prognostic factor for breast cancer patients treated with anthracycline-based chemotherapy.

Optical transillumination spectroscopy to quantify parenchymal tissue density: an indicator for breast cancer risk

Mammographic screening for early detection of breast cancer has proven valuable in improving breast cancer survival. However, breast cancer incidence is still increasing, and thus preventative oncology needs to receive more attention, with the goal of identifying women with increased risk of developing breast cancer in the future and offering them risk reduction interventions. Mammogram derived parenchymal density pattern has been shown by various authors to provide a high odds ratio for breast cancer. Near-infrared optical transillumination spectroscopy was employed to determine physiological properties of the breast tissue to quantify differences in women with low or high breast cancer risk. Specifically in this study, women who had a recent mammogram underwent examination of their breast tissue by optical transillumination spectroscopy. Areas of adipose and glandular tissues which give rise to mammographic density patterns also have characteristic optical transillumination spectra. Correlation between optical transillumination spectroscopy and mammographic density pattern was established using partial least squares analysis. Results show that predicted tissue density based on optical transillumination spectroscopy correlates with mammographic observed tissue density, with a Spearman Rank correlation coefficient of 0.72. This suggests that optical transillumination spectroscopy may be a promising tool to quantify and monitor changes in breast cancer risk.

c-myc amplification is associated with HER2 amplification and closely linked with cell proliferation in tissue microarray of nonselected breast cancers

C-myc and HER2 amplification were analyzed on 214 consecutive breast cancers by fluorescence in situ hybridization using tissue microarray technology. The frequencies of amplification were 15.4% (33/214) and 23.3% (49/210), respectively. c- myc amplification was significantly associated with HER2 amplification ( P < .001) and closely linked with cell proliferative activity, measured by Ki67 labeling index ( P = .010). In univariate survival analysis, lymph node status, tumor size, and histological grade were significant prognostic factors, but in multivariate analysis, lymph node status was the only significant factor. Patient survival did not differ according to c- myc amplification status, and c- myc amplification showed no significant correlation with clinicopathologic features of the tumors. A strong correlation between c- myc and HER2 amplification and proliferative activity indicates a biological link between these genes in breast cancer cell.

Classification of breast tissue density by optical transillumination spectroscopy: optical and physiological effects governing predictive value

Preventive oncology is in need of a risk assessment technique that can identify individuals at high risk for breast cancer and has the ability to monitor the efficacy of a risk reducing intervention. Optical transillumination spectroscopy (OTS) gives information about breast tissue composition and tissue density. OTS is noninvasive and in contrast to mammography, uses nonionizing radiation. It is safe and can be used frequently on younger women, potentially permitting early risk detection and thus increasing the time available for risk reduction interventions to assert their influence. Before OTS can be used as a risk assessment and/or monitoring technique, its predictive ability needs to be demonstrated and maximized through the construction of various mathematical models relating OTS and breast tissue density, and hence, risk. To establish a correlation between OTS and mammographic density principal components analysis (PCA), using risk classification, is calculated. The PCA scores are presented in three-dimensional cluster plots and a plane of differentiation that separates the high and low tissue densities is used to calculate the predictive value. Stratification of PCA for measurement position on the breast in cranial-caudal projection is introduced. Analysis of PCA scores as a function of the volunteer's age and body mass index (BMI) is examined. A small but significant correlation between the component scores and age or BMI is noted but the correlation is dependent on the tissue density category examined. Correction of the component scores for age and BMI is not recommended, since a priori knowledge of a woman's breast tissue density is required. Stratification for the center and distal measurement positions provide a predictive value for OTS above 96%.

Intracellular patterns of Her-2/neu, ras, and ploidy abnormalities in primary human breast cancers predict postoperative clinical disease-free survival

PURPOSE

In an earlier study, the presence of aneuploidy, Her-2/neu overexpression, and ras overexpression in the same cells (triple-positive cells) was of prognostic significance (P < 0.015) in 91 patients with localized breast cancer (median follow up, 32 months). Here, we present results involving a larger group of patients with longer follow-up.

EXPERIMENTAL DESIGN

Fixed cell suspensions prepared from primary tumors of 189 patients with early breast cancer were studied prospectively by multiparameter flow cytometry. Correlated intracellular fluorescence-based measurements of cell DNA content and Her-2/neu and ras protein were obtained on each of >2000 cells in each tumor. Intracellular combinations of abnormalities in these measurements were correlated with subsequent patient disease-free survival (DFS). Median time on study was 54 months (range, 7-128 months).

RESULTS

DFS of patients with > or = 5% triple-positive tumor cells was shorter than those who did not meet this criterion (P = 0.004). The difference remained statistically significant after accounting for nodal status, tumor size, and each of the component abnormalities (P = 0.006). Node-negative patients whose tumors had fewer than 2 abnormalities/cell had an especially favorable clinical course, with a 5-year DFS of 96% (lower confidence bound, 86%).

CONCLUSIONS

Patterns of accumulated intracellular molecular abnormalities in cells of primary human breast cancers are predictive for subsequent DFS independently of the abnormalities themselves taken individually.

Non-ionizing near-infrared radiation transillumination spectroscopy for breast tissue density and assessment of breast cancer risk

There is increasing attention to prevention as a means to reduce cancer incidence. Prevention interventions or therapies in turn rely on risk assessment programs to identify those women most likely to benefit from education and lifestyle changes. These programs are usually based either on interviews to identify ethnic, genetic, and lifestyle factors contributing to risk or on physical examination of the breast. For the latter it has been shown that the parenchymal density pattern observed in X-ray mammography can be used to assess an individual's risk. Extensive areas of dense, glandular tissue that are relatively radio-opaque are associated with higher breast cancer risk, with an odds ratio of 4 to 6 compared with women in whom the breast density is low owing to an abundance of adipose tissue. Near-infrared optical transillumination spectroscopy has been used previously to investigate the physiological properties of breast tissue. In this study, women were recruited who underwent recently X-ray mammography. The tissue density was assessed by a radiologist. The women then underwent optical transillumination spectroscopy, for which an instrument was developed that delivered visible and near-infrared light to the breast. After being transmitted through the breast craniocaudally in one of four quadrants, the spectrum from 625 to 1050 nm was measured. The spectra were used as input to a Principal Component Analysis (PCA) that used the corresponding mammographic density as the reference standard. The study group consisted of 92 women aged 39 to 72 years. Without further stratification for age, menopausal status, or measurement position, the PCA numerical model predicted the radiological assessment of tissue density in the mid 80% to low 90%.

MYC Is Amplified in BRCA1-Associated Breast Cancers

PURPOSE

Germ-line mutations in the BRCA1 tumor suppressor gene predispose to early onset breast cancers with a distinct phenotype characterized by high tumor grade, aneuploidy, high proliferation rate, and estrogen receptor-negativity. The molecular mechanisms and cooperative oncogenes contributing to multistep tumor progression in cells lacking BRCA1 are not well defined. To examine whether C-MYC (MYC), a transforming oncogene associated with genetic instability, contributes to multistep tumor progression in BRCA1-associated breast cancer, we have analyzed tumors from women with hereditary BRCA1-mutated and sporadic breast cancers.

EXPERIMENTAL DESIGN

We performed fluorescence in situ hybridization using a MYC:CEP8 assay on formalin-fixed paraffin-embedded tumor tissues from 40 women with known deleterious germ-line BRCA1 mutations and 62 sporadic cases, including 20 cases with hypermethylation of the BRCA1 gene promoter.

RESULTS

We observed a MYC:CEP8 amplification ratio >/=2 in 21 of 40 (53%) BRCA1-mutated tumors compared with 14 of 62 (23%) sporadic tumors (P = 0.003). Of the 14 sporadic cases with MYC amplification, 8 (57%) were BRCA1-methylated. In total, MYC amplification was found in a significantly higher proportion of tumors with BRCA1 dysfunction (29 of 60, 48% versus 6 of 42, 14%; P = 0.0003). In a multivariable regression model controlling for age, tumor size, and estrogen receptor status, BRCA1-mutated tumors demonstrated significantly greater mean MYC:CEP8 ratio than sporadic tumors (P = 0.02).

CONCLUSIONS

Our data indicate that MYC oncogene amplification contributes to tumor progression in BRCA1-associated breast cancers. Thus, we conclude that the aggressive histopathological features of BRCA1-associated tumors are in part due to dysregulated MYC activity.

A simple and reliable pretreatment protocol facilitates fluorescent in situ hybridisation on tissue microarrays of paraffin wax embedded tumour samples

AIMS

To describe a robust pretreatment protocol for preparing paraffin wax embedded tissues on tissue microarrays for fluorescence in situ hybridisation (FISH). The newly developed pretreatment protocol described here was compared with the commonly used sodium thiocyanate based protocol and two different heating methods used in standard antigen unmasking protocols for immunohistochemistry (pressure cooking and microwaving in citrate acid buffer).

METHODS

Dewaxed tissue sections were incubated in 10mM citric acid buffer at 80 degrees C for 30 minutes to two hours, followed by a short pepsin digestion (1-5 mg/ml). Pretreated tissues were co-denatured with DNA probes at 80 degrees C for 10 minutes, followed by hybridisation at 37 degrees C for 48-72 hours.

RESULTS

The three protocols using citrate acid buffer produced FISH signals with superior signal to noise ratios compared with sodium thiocyanate pretreatment. Most importantly, the best tissue attachment was achieved using the newly developed pretreatment protocol: on tissue microarrays less than 1% of cores were lost. To date, a total of 30 probes have been successfully hybridised on to breast tissue and multi-tissue microarrays.

CONCLUSION

This pretreatment protocol is easy, reproducible, and facilitates FISH on tissue microarrays, with potential for widespread application in cancer research.

Molecular evolutionary patterns in breast cancer

Geno-phenotypic patterns of pre-invasive and invasive lobular breast cancers and infiltrating ductal carcinomas of low, intermediate, and high grade are reviewed. One of the main differences between lobular breast cancers and ductal carcinomas is the presence of inactivating E-cadherin gene mutations in lobular breast cancers. In many other respects, lobular breast cancers and low-grade ductal carcinomas exhibit similar geno-phenotypic profiles. The development of p53 dysfunction may be a hallmark of infiltrating ductal cancers of intermediate and high grade. Sequential Her-2/neu and ras abnormalities define a subset of aggressive high-grade tumors, and the development of Rb dysfunction may define a separate subset of aggressive ductal cancers. Based on these observations, a branching molecular evolutionary model for the development and progression of breast cancer is proposed.

c-myc, not her-2/neu, can predict the prognosis of breast cancer patients: how novel, how accurate, and how significant?

The predictive and prognostic implication of oncogene amplification in breast cancer has received great attention in the past two decades. her-2/neu and c-myc are two oncogenes that are frequently amplified and overexpressed in breast carcinomas. Despite the extensive data on these oncogenes, their prognostic and predictive impact on breast cancer patients remains controversial. Schlotter and colleagues have recently suggested that c-myc, and not her-2/neu, could predict the recurrence and mortality of patients with node-negative breast carcinomas. Regardless of the promising results, caution should be exercised in the interpretation of data from studies assessing gene amplification without in situ analysis. We address the novelty, accuracy and clinical significance of the study by Schlotter and colleagues.

The cancer connection: BRCA1 and BRCA2 tumor suppression in mice and humans

BRCA1 and BRCA2 mutations are estimated to be responsible for the great majority of familial breast and ovarian cancers. Much progress has been made toward the understanding of the function of these proteins through genetic, biochemical, and structural studies. The embryonic lethality encountered in the knockout mouse initially hindered the development of mouse models aimed at studying tumor suppression. However, mice that harbor hypomorphic Brca1 and Brca2 alleles and cre-mediated tissue-specific deletions for Brca1 and Brca2 have been generated. Mice deficient for either Brca1 or Brca2 sustain a wide range of carcinoma and mammary epithelium deleted for Brca1 or Brca2 is highly susceptible to mammary tumorigenesis. Mammary (and other) tumors occur at long latency as compared to oncogene-induced mouse tumors. p53 deficiency is highly cooperative with both Brca1 and Brca2 in promoting tumorigenesis. Analysis of Brca1-associated mammary tumors reveals significant similarities to BRCA1-associated breast cancer in regard to high tumor grade, hormone receptor negativity, a high incidence of p53 mutations and genetic instability.

The myc oncogene: MarvelouslY Complex

The activated product of the myc oncogene deregulates both cell growth and death check points and, in a permissive environment, rapidly accelerates the affected clone through the carcinogenic process. Advances in understanding the molecular mechanism of Myc action are highlighted in this review. With the revolutionary developments in molecular diagnostic technology, we have witnessed an unprecedented advance in detecting activated myc in its deregulated, oncogenic form in primary human cancers. These improvements provide new opportunities to appreciate the tumor subtypes harboring deregulated Myc expression, to identify the essential cooperating lesions, and to realize the therapeutic potential of targeting Myc. Knowledge of both the breadth and depth of the numerous biological activities controlled by Myc has also been an area of progress. Myc is a multifunctional protein that can regulate cell cycle, cell growth, differentiation, apoptosis, transformation, genomic instability, and angiogenesis. New insights into Myc's role in regulating these diverse activities are discussed. In addition, breakthroughs in understanding Myc as a regulator of gene transcription have revealed multiple mechanisms of Myc activation and repression of target genes. Moreover, the number of reported Myc regulated genes has expanded in the past few years, inspiring a need to focus on classifying and segregating bona fide targets. Finally, the identity of Myc-binding proteins has been difficult, yet has exploded in the past few years with a plethora of novel interactors. Their characterization and potential impact on Myc function are discussed. The rapidity and magnitude of recent progress in the Myc field strongly suggests that this marvelously complex molecule will soon be unmasked.

Emerging technology and future developments in flow cytometry

The authors' view of the future of flow cytometry is based on a belief that the single most important aspect flow cytometry offers to the investigator is high-speed interrogation of correlated measurements on a cell-by-cell basis. Over the next several years, an enormous increase in the capabilities of cytometry in general, and flow cytometry in particular, is likely to occur. A brief description of some of those capabilities is the subject of this article.