Jonathan R. Pollack

Molecular portraits of human breast tumours

Human breast tumours are diverse in their natural history and in their responsiveness to treatments. Variation in transcriptional programs accounts for much of the biological diversity of human cells and tumours. In each cell, signal transduction and regulatory systems transduce information from the cells identity to its environmental status, thereby controlling the level of expression of every gene in the genome. Here we have characterized variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals, using complementary DNA microarrays representing 8,102 human genes. These patterns provided a distinctive molecular portrait of each tumour. Twenty of the tumours were sampled twice, before and after a 16-week course of doxorubicin chemotherapy, and two tumours were paired with a lymph node metastasis from the same patient. Gene expression patterns in two tumour samples from the same individual were almost always more similar to each other than either was to any other sample. Sets of co-expressed genes were identified for which variation in messenger RNA levels could be related to specific features of physiological variation. The tumours could be classified into subtypes distinguished by pervasive differences in their gene expression patterns.

Genome-wide analysis of DNA copy-number changes using cDNA microarrays

Gene amplifications and deletions frequently contribute to tumorigenesis. Characterization of these DNA copy-number changes is important for both the basic understanding of cancer and its diagnosis. Comparative genomic hybridization (CGH) was developed to survey DNA copy-number variations across a whole genome. With CGH, differentially labelled test and reference genomic DNAs are co-hybridized to normal metaphase chromosomes, and fluorescence ratios along the length of chromosomes provide a cytogenetic representation of DNA copy-number variation. CGH, however, has a limited (~20 Mb) mapping resolution, and higher-resolution techniques, such as fluorescence in situ hybridization (FISH), are prohibitively labour-intensive on a genomic scale. Array-based CGH, in which fluorescence ratios at arrayed DNA elements provide a locus-by-locus measure of DNA copy-number variation, represents another means of achieving increased mapping resolution. Published array CGH methods have relied on large genomic clone (for example BAC) array targets and have covered only a small fraction of the human genome. cDNAs representing over 30,000 radiation-hybrid (RH)–mapped human genes provide an alternative and readily available genomic resource for mapping DNA copy-number changes. Although cDNA microarrays have been used extensively to characterize variation in human gene expression, human genomic DNA is a far more complex mixture than the mRNA representation of human cells. Therefore, analysis of DNA copy-number variation using cDNA microarrays would require a sensitivity of detection an order of magnitude greater than has been routinely reported. We describe here a cDNA microarray-based CGH method, and its application to DNA copy-number variation analysis in breast cancer cell lines and tumours. Using this assay, we were able to identify gene amplifications and deletions genome-wide and with high resolution, and compare alterations in DNA copy number and gene expression.

Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors

Genomic DNA copy number alterations are key genetic events in the development and progression of human cancers. Here we report a genome-wide microarray comparative genomic hybridization (array CGH) analysis of DNA copy number variation in a series of primary human breast tumors. We have profiled DNA copy number alteration across 6,691 mapped human genes, in 44 predominantly advanced, primary breast tumors and 10 breast cancer cell lines. While the overall patterns of DNA amplification and deletion corroborate previous cytogenetic studies, the high-resolution (gene-by-gene) mapping of amplicon boundaries and the quantitative analysis of amplicon shape provide significant improvement in the localization of candidate oncogenes. Parallel microarray measurements of mRNA levels reveal the remarkable degree to which variation in gene copy number contributes to variation in gene expression in tumor cells. Specifically, we find that 62% of highly amplified genes show moderately or highly elevated expression, that DNA copy number influences gene expression across a wide range of DNA copy number alterations (deletion, low-, mid- and high-level amplification), that on average, a 2-fold change in DNA copy number is associated with a corresponding 1.5-fold change in mRNA levels, and that overall, at least 12% of all the variation in gene expression among the breast tumors is directly attributable to underlying variation in gene copy number. These findings provide evidence that widespread DNA copy number alteration can lead directly to global deregulation of gene expression, which may contribute to the development or progression of cancer.

Genome-wide analysis of DNA copy number variation in breast cancer using DNA microarrays

Gene amplifications and deletions frequently have pathogenetic roles in cancer. 30,000 radiation-hybrid mapped cDNAs provide a genomic resource to map these lesions with high resolution. We developed a cDNA microarray-based comparative genomic hybridisation method for analysing DNA copy number changes across thousands of genes simultaneously. Using this procedure, we could reliably detect DNA copy number alterations of twofold or less. In breast cancer cell lines, we have mapped regions of DNA copy number variation at high resolution, revealing previously unrecognised genomic amplifications and deletions, and new complexities of amplicon structure. Recurrent regions of DNA amplification, which may harbour novel oncogenes, were readily identified. Alterations of DNA copy number and gene expression could be compared and correlated in parallel analyses. We have now collected genome-wide DNA copy number information on a set of 9 breast cancer cell lines and over 35 primary breast tumours. For the breast tumours, DNA copy number information is being compared and correlated with data already collected on p53 status, microarray gene expression profiles, and treatment response and clinical outcome. The results of this analysis will be presented.

Molecular characterisation of soft tissue tumours: a gene expression study

BACKGROUND Soft-tissue tumours are derived from mesenchymal cells such as fibroblasts, muscle cells, or adipocytes, but for many such tumours the histogenesis is controversial. We aimed to start molecular characterisation of these rare neoplasms and to do a genome-wide search for new diagnostic markers. METHODS We analysed gene-expression patterns of 41 soft-tissue tumours with spotted cDNA microarrays. After removal of errors introduced by use of different microarray batches, the expression patterns of 5520 genes that were well defined were used to separate tumours into discrete groups by hierarchical clustering and singular value decomposition. FINDINGS Synovial sarcomas, gastrointestinal stromal tumours, neural tumours, and a subset of the leiomyosarcomas, showed strikingly distinct gene-expression patterns. Other tumour categories--malignant fibrous histiocytoma, liposarcoma, and the remaining leiomyosarcomas--shared molecular profiles that were not predicted by histological features or immunohistochemistry. Strong expression of known genes, such as KIT in gastrointestinal stromal tumours, was noted within gene sets that distinguished the different sarcomas. However, many uncharacterised genes also contributed to the distinction between tumour types. INTERPRETATION These results suggest a new method for classification of soft-tissue tumours, which could improve on the method based on histological findings. Large numbers of uncharacterised genes contributed to distinctions between the tumours, and some of these could be useful markers for diagnosis, have prognostic significance, or prove possible targets for treatment.

Molecular Profiling of Breast Cancer Cell Lines Defines Relevant Tumor Models and Provides a Resource for Cancer Gene Discovery

Background Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes–luminal A, luminal B, ERBB2-associated, basal-like and normal-like–with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Methods Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Findings Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem/progenitor-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 multi-copy deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Conclusions Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, cancer stem cell biology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes.

Distinct Patterns of DNA Copy Number Alteration Are Associated with Different Clinicopathological Features and Gene-Expression Subtypes of Breast Cancer

Breast cancer is a leading cause of cancer‐death among women, where the clinicopathological features of tumors are used to prognosticate and guide therapy. DNA copy number alterations (CNAs), which occur frequently in breast cancer and define key pathogenetic events, are also potentially useful prognostic or predictive factors. Here, we report a genome‐wide array‐based comparative genomic hybridization (array CGH) survey of CNAs in 89 breast tumors from a patient cohort with locally advanced disease. Statistical analysis links distinct cytoband loci harboring CNAs to specific clinicopathological parameters, including tumor grade, estrogen receptor status, presence of TP53 mutation, and overall survival. Notably, distinct spectra of CNAs also underlie the different subtypes of breast cancer recently defined by expression‐profiling, implying these subtypes develop along distinct genetic pathways. In addition, higher numbers of gains/losses are associated with the “basal‐like” tumor subtype, while high‐level DNA amplification is more frequent in “luminal‐B” subtype tumors, suggesting also that distinct mechanisms of genomic instability might underlie their pathogenesis. The identified CNAs may provide a basis for improved patient prognostication, as well as a starting point to define important genes to further our understanding of the pathobiology of breast cancer. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045‐2257/suppmat.

A transcriptional response to Wnt protein in human embryonic carcinoma cells

BackgroundWnt signaling is implicated in many developmental decisions, including stem cell control, as well as in cancer. There are relatively few target genes known of the Wnt pathway.ResultsWe have identified target genes of Wnt signaling using microarray technology and human embryonic carcinoma cells stimulated with active Wnt protein. The ~50 genes upregulated early after Wnt addition include the previously known Wnt targets Cyclin D1, MYC, ID2 and βTRCP. The newly identified targets, which include MSX1, MSX2, Nucleophosmin, Follistatin, TLE/Groucho, Ubc4/5E2, CBP/P300, Frizzled and REST/NRSF, have important implications for understanding the roles of Wnts in development and cancer. The protein synthesis inhibitor cycloheximide blocks induction by Wnt, consistent with a requirement for newly synthesized β-catenin protein prior to target gene activation. The promoters of nearly all the target genes we identified have putative TCF binding sites, and we show that the TCF binding site is required for induction of Follistatin. Several of the target genes have a cooperative response to a combination of Wnt and BMP.ConclusionsWnt signaling activates genes that promote stem cell fate and inhibit cellular differentiation and regulates a remarkable number of genes involved in its own signaling system.

MYC stimulates EZH2 expression by repression of its negative regulator miR-26a

The MYC oncogene, which is commonly mutated/amplified in tumors, represents an important regulator of cell growth because of its ability to induce both proliferation and apoptosis. Recent evidence links MYC to altered miRNA expression, thereby suggesting that MYC-regulated miRNAs might contribute to tumorigenesis. To further analyze the impact of MYC-regulated miRNAs, we investigated a murine lymphoma model harboring the MYC transgene in a Tet-off system to control its expression. Microarray-based miRNA expression profiling revealed both known and novel MYC targets. Among the miRNAs repressed by MYC, we identified the potential tumor suppressor miR-26a, which possessed the ability to attenuate proliferation in MYC-dependent cells. Interestingly, miR-26a was also found to be deregulated in primary human Burkitt lymphoma samples, thereby probably being of clinical relevance. Although today only few miRNA targets have been identified in human disease, we could show that ectopic expression of miR-26a influenced cell cycle progression by targeting the bona fide oncogene EZH2, a Polycomb protein and global regulator of gene expression yet unknown to be regulated by miRNAs. Thus, in addition to directly targeting protein-coding genes, MYC modulates genes important to oncogenesis via deregulation of miRNAs, thereby vitally contributing to MYC-induced lymphomagenesis.

Genomic Profiling Reveals Alternative Genetic Pathways of Prostate Tumorigenesis

Prostate cancer is clinically heterogeneous, ranging from indolent to lethal disease. Expression profiling previously defined three subtypes of prostate cancer, one (subtype-1) linked to clinically favorable behavior, and the others (subtypes-2 and -3) linked with a more aggressive form of the disease. To explore disease heterogeneity at the genomic level, we carried out array-based comparative genomic hybridization (array CGH) on 64 prostate tumor specimens, including 55 primary tumors and 9 pelvic lymph node metastases. Unsupervised cluster analysis of DNA copy number alterations (CNA) identified recurrent aberrations, including a 6q15-deletion group associated with subtype-1 gene expression patterns and decreased tumor recurrence. Supervised analysis further disclosed distinct patterns of CNA among gene-expression subtypes, where subtype-1 tumors exhibited characteristic deletions at 5q21 and 6q15, and subtype-2 cases harbored deletions at 8p21 (NKX3-1) and 21q22 (resulting in TMPRSS2-ERG fusion). Lymph node metastases, predominantly subtype-3, displayed overall higher frequencies of CNA, and in particular gains at 8q24 (MYC) and 16p13, and loss at 10q23 (PTEN) and 16q23. Our findings reveal that prostate cancers develop via a limited number of alternative preferred genetic pathways. The resultant molecular genetic subtypes provide a new framework for investigating prostate cancer biology and explain in part the clinical heterogeneity of the disease.