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Biomedical subjects

Charles M Perou

Publications and source records attributed to Charles M Perou.

36 records · Page 2Linked to original sources
PubMed2005

Standardizing global gene expression analysis between laboratories and across platforms.

To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.

Gene Expression Profiling↗
PubMed2005

High reproducibility using sodium hydroxide-stripped long oligonucleotide DNA microarrays.

Recently, long oligonucleotide (60- to 70-mer) microarrays for two-color experiments have been developed and are gaining widespread use. In addition, when there is limited availability of mRNA from tissue sources, RNA amplification can and is being used to produce sufficient quantities of cRNA for microarray hybridization. Taking advantage of the selective degradation of RNA under alkaline conditions, we have developed a method to "strip" glass-based oligonucleotide microarrays that use fluorescent RNA in the hybridization, while leaving the DNA oligonucleotide probes intact and usable for a second experiment. Replicate microarray experiments conducted using stripped arrays showed high reproducibility, however, we found that arrays could only be stripped and reused once without compromising data quality. The intraclass correlation (ICC) between a virgin array and a stripped array hybridized with the same sample showed a range of 0.90-0.98, which is comparable to the ICC of two virgin arrays hybridized with the same sample. Using this method, once-stripped oligonucleotide microarrays are usable, reliable, and help to reduce costs.

Breast Neoplasms↗
PubMed2004

Mutation of GATA3 in human breast tumors.

GATA3 is an essential transcription factor that was first identified as a regulator of immune cell function. In recent microarray analyses of human breast tumors, both normal breast luminal epithelium and estrogen receptor (ESR1)-positive tumors showed high expression of GATA3. We sequenced genomic DNA from 111 breast tumors and three breast-tumor-derived cell lines and identified somatic mutations of GATA3 in five tumors and the MCF-7 cell line. These mutations cluster in the vicinity of the highly conserved second zinc-finger that is required for DNA binding. In addition to these five, we identified using cDNA sequencing a unique mis-splicing variant that caused a frameshift mutation. One of the somatic mutations we identified was identical to a germline GATA3 mutation reported in two kindreds with HDR syndrome/OMIM #146255, which is an autosomal dominant syndrome caused by the haplo-insufficiency of GATA3. The ectopic expression of GATA3 in human 293T cells caused the induction of 73 genes including six cytokeratins, and inhibited cell line doubling times. These data suggest that GATA3 is involved in growth control and the maintenance of the differentiated state in epithelial cells, and that GATA3 variants may contribute to tumorigenesis in ESR1-positive breast tumors.

Amino Acid Sequence↗
PubMed2004

A custom microarray platform for analysis of microRNA gene expression.

MicroRNAs are short, noncoding RNA transcripts that post-transcriptionally regulate gene expression. Several hundred microRNA genes have been identified in Caenorhabditis elegans, Drosophila, plants and mammals. MicroRNAs have been linked to developmental processes in C. elegans, plants and humans and to cell growth and apoptosis in Drosophila. A major impediment in the study of microRNA function is the lack of quantitative expression profiling methods. To close this technological gap, we have designed dual-channel microarrays that monitor expression levels of 124 mammalian microRNAs. Using these tools, we observed distinct patterns of expression among adult mouse tissues and embryonic stem cells. Expression profiles of staged embryos demonstrate temporal regulation of a large class of microRNAs, including members of the let-7 family. This microarray technology enables comprehensive investigation of microRNA expression, and furthers our understanding of this class of recently discovered noncoding RNAs.

Animals↗
PubMed2004

Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma.

PURPOSE: Expression profiling studies classified breast carcinomas into estrogen receptor (ER)+/luminal, normal breast-like, HER2 overexpressing, and basal-like groups, with the latter two associated with poor outcomes. Currently, there exist clinical assays that identify ER+/luminal and HER2-overexpressing tumors, and we sought to develop a clinical assay for breast basal-like tumors. EXPERIMENTAL DESIGN: To identify an immunohistochemical profile for breast basal-like tumors, we collected a series of known basal-like tumors and tested them for protein patterns that are characteristic of this subtype. Next, we examined the significance of these protein patterns using tissue microarrays and evaluated the prognostic significance of these findings. RESULTS: Using a panel of 21 basal-like tumors, which was determined using gene expression profiles, we saw that this subtype was typically immunohistochemically negative for estrogen receptor and HER2 but positive for basal cytokeratins, HER1, and/or c-KIT. Using breast carcinoma tissue microarrays representing 930 patients with 17.4-year mean follow-up, basal cytokeratin expression was associated with low disease-specific survival. HER1 expression was observed in 54% of cases positive for basal cytokeratins (versus 11% of negative cases) and was associated with poor survival independent of nodal status and size. c-KIT expression was more common in basal-like tumors than in other breast cancers but did not influence prognosis. CONCLUSIONS: A panel of four antibodies (ER, HER1, HER2, and cytokeratin 5/6) can accurately identify basal-like tumors using standard available clinical tools and shows high specificity. These studies show that many basal-like tumors express HER1, which suggests candidate drugs for evaluation in these patients.

Biomarkers, Tumor↗
PubMed2004

Statistical modeling for selecting housekeeper genes.

There is a need for statistical methods to identify genes that have minimal variation in expression across a variety of experimental conditions. These 'housekeeper' genes are widely employed as controls for quantification of test genes using gel analysis and real-time RT-PCR. Using real-time quantitative RT-PCR, we analyzed 80 primary breast tumors for variation in expression of six putative housekeeper genes (MRPL19 (mitochondrial ribosomal protein L19), PSMC4 (proteasome (prosome, macropain) 26S subunit, ATPase, 4), SF3A1 (splicing factor 3a, subunit 1, 120 kDa), PUM1 (pumilio homolog 1 (Drosophila)), ACTB (actin, beta) and GAPD (glyceraldehyde-3-phosphate dehydrogenase)). We present appropriate models for selecting the best housekeepers to normalize quantitative data within a given tissue type (for example, breast cancer) and across different types of tissue samples.

ATPases Associated with Diverse Cellular Activitie↗
PubMed2004

Cell-type-specific responses to chemotherapeutics in breast cancer.

Recent microarray studies have identified distinct subtypes of breast tumors that arise from different cell types and that show statistically significant differences in patient outcome. To gain insight into these differences, we identified in vitro and in vivo changes in gene expression induced by chemotherapeutics. We treated two cell lines derived from basal epithelium (immortalized human mammary epithelial cells) and two lines derived from luminal epithelium (MCF-7 and ZR-75-1) with chemotherapeutics used in the treatment of breast cancer and assayed for changes in gene expression using DNA microarrays. Treatment doses for doxorubicin and 5-fluorouracil were selected to cause comparable cytotoxicity across all four cell lines. The dominant expression response in each of the cell lines was a general stress response; however, distinct expression patterns were observed. Both cell types induced DNA damage-response genes such as p21(waf1), but the response in the luminal cells showed higher fold changes and included more p53-regulated genes. Luminal cell lines repressed a large number of cell cycle-regulated genes and other genes involved in cellular proliferation, whereas the basal cell lines did not. Instead, the basal cell lines repressed genes that were involved in differentiation. These in vitro responses were compared with expression responses in breast tumors sampled before and after treatment with doxorubicin or 5-fluorouracil/mitomycin C. The in vivo data corroborated the cell-type-specific responses to chemotherapeutics observed in vitro, including the induction of p21(waf1). Similarities between in vivo and in vitro responses help to identify important response mechanisms to chemotherapeutics.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed2004

Universal Reference RNA as a standard for microarray experiments.

BACKGROUND: Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR), developed with the goal of providing hybridization signal at each microarray probe location (spot). Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. RESULTS: Human, mouse and rat URR (UHRR, UMRR and URRR, respectively) were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage). Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97). CONCLUSION: Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and laboratories.

Animals↗
PubMed2004

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.

Adult↗
PubMed2004

Adjustment of systematic microarray data biases.

MOTIVATION: Systematic differences due to experimental features of microarray experiments are present in most large microarray data sets. Many different experimental features can cause biases including different sources of RNA, different production lots of microarrays or different microarray platforms. These systematic effects present a substantial hurdle to the analysis of microarray data. RESULTS: We present here a new method for the identification and adjustment of systematic biases that are present within microarray data sets. Our approach is based on modern statistical discrimination methods and is shown to be very effective in removing systematic biases present in a previously published breast tumor cDNA microarray data set. The new method of 'Distance Weighted Discrimination (DWD)' is shown to be better than Support Vector Machines and Singular Value Decomposition for the adjustment of systematic microarray effects. In addition, it is shown to be of general use as a tool for the discrimination of systematic problems present in microarray data sets, including the merging of two breast tumor data sets completed on different microarray platforms. AVAILABILITY: Matlab software to perform DWD can be retrieved from https://genome.unc.edu/pubsup/dwd/

Algorithms↗
PubMed2004

Molecular classification of head and neck squamous cell carcinomas using patterns of gene expression.

The prognostication of head and neck squamous cell carcinoma (HNSCC) is largely based upon the tumor size and location and the presence of lymph node metastases. Here we show that gene expression patterns from 60 HNSCC samples assayed on cDNA microarrays allowed categorization of these tumors into four distinct subtypes. These subtypes showed statistically significant differences in recurrence-free survival and included a subtype with a possible EGFR-pathway signature, a mesenchymal-enriched subtype, a normal epithelium-like subtype, and a subtype with high levels of antioxidant enzymes. Supervised analyses to predict lymph node metastasis status were approximately 80% accurate when tumor subsite and pathological node status were considered simultaneously. This work represents an important step toward the identification of clinically significant biomarkers for HNSCC.

Adult↗
PubMed2004

Prediction of toxicant-specific gene expression signatures after chemotherapeutic treatment of breast cell lines.

Global gene expression profiling has demonstrated that the predominant cellular response to a range of toxicants is a general stress response. This stereotyped environmental stress response commonly includes repression of protein synthesis and cell-cycle-regulated genes and induction of DNA damage and oxidative stress-responsive genes. Our laboratory recently characterized the general stress response of breast cell lines derived from basal-like and luminal epithelium after treatment with doxorubicin (DOX) or 5-fluorouracil (5FU) and showed that each cell type has a distinct response. However, we expected that some of the expression changes induced by DOX and 5FU would be unique to each compound and might reflect the underlying mechanisms of action of these agents. Therefore, we employed supervised analyses (significance analysis of microarrays) to identify genes that showed differential expression between DOX-treated and 5FU-treated cell lines. We then used cross-validation analyses and identified genes that afforded high predictive accuracy in classifying samples into the two treatment classes. To test whether these gene lists had good predictive accuracy in an independent data set, we treated our panel of cell lines with etoposide, a compound mechanistically similar to DOX. We demonstrated that using expression patterns of 100 genes we were able to obtain 100% predictive accuracy in classifying the etoposide samples as being more similar in expression to DOX-treated than to 5FU-treated samples. These analyses also showed that toxicant-specific gene expression patterns, similar to general stress responses, vary according to cell type.

Antibiotics, Antineoplastic↗
PubMed2003

Repeated observation of breast tumor subtypes in independent gene expression data sets.

Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors were analyzed by hierarchical clustering based on patterns of expression of 534 "intrinsic" genes and shown to subdivide into one basal-like, one ERBB2-overexpressing, two luminal-like, and one normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. Similar cluster analyses of two published, independent data sets representing different patient cohorts from different laboratories, uncovered some of the same breast cancer subtypes. In the one data set that included information on time to development of distant metastasis, subtypes were associated with significant differences in this clinical feature. By including a group of tumors from BRCA1 carriers in the analysis, we found that this genotype predisposes to the basal tumor subtype. Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.

Breast Neoplasms↗
PubMed2002

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.

Breast Neoplasms↗
PubMed2002

Expression of cytokeratins 17 and 5 identifies a group of breast carcinomas with poor clinical outcome.

While several prognostic factors have been identified in breast carcinoma, the clinical outcome remains hard to predict for individual patients. Better predictive markers are needed to help guide difficult treatment decisions. In a previous study of 78 breast carcinoma specimens, we noted an association between poor clinical outcome and the expression of cytokeratin 17 and/or cytokeratin 5 mRNAs. Here we describe the results of immunohistochemistry studies using monoclonal antibodies against these markers to analyze more than 600 paraffin-embedded breast tumors in tissue microarrays. We found that expression of cytokeratin 17 and/or cytokeratin 5/6 in tumor cells was associated with a poor clinical outcome. Moreover, multivariate analysis showed that in node-negative breast carcinoma, expression of these cytokeratins was a prognostic factor independent of tumor size and tumor grade.

Animals↗
PubMed2002

Molecular portraits and the family tree of cancer.

The twenty-first century heralds a new era for the biological sciences and medicine. The tools of our time are allowing us to analyze complex genomes more comprehensively than ever before. A principal technology contributing to this explosion of information is the DNA microarray, which enables us to study genome-wide expression patterns in complex biological systems. Although the potential of microarrays is yet to be fully realized, these tools have shown great promise in deciphering complex diseases such as cancer. The early results are painting a detailed portrait of cancer that illustrates the individuality of each tumor and allows familial relationships to be recognized through the identification of cell types sharing common expression patterns.

DNA, Neoplasm↗
PubMed2002

Identification of genes periodically expressed in the human cell cycle and their expression in tumors.

The genome-wide program of gene expression during the cell division cycle in a human cancer cell line (HeLa) was characterized using cDNA microarrays. Transcripts of >850 genes showed periodic variation during the cell cycle. Hierarchical clustering of the expression patterns revealed coexpressed groups of previously well-characterized genes involved in essential cell cycle processes such as DNA replication, chromosome segregation, and cell adhesion along with genes of uncharacterized function. Most of the genes whose expression had previously been reported to correlate with the proliferative state of tumors were found herein also to be periodically expressed during the HeLa cell cycle. However, some of the genes periodically expressed in the HeLa cell cycle do not have a consistent correlation with tumor proliferation. Cell cycle-regulated transcripts of genes involved in fundamental processes such as DNA replication and chromosome segregation seem to be more highly expressed in proliferative tumors simply because they contain more cycling cells. The data in this report provide a comprehensive catalog of cell cycle regulated genes that can serve as a starting point for functional discovery. The full dataset is available at http://genome-www.stanford.edu/Human-CellCycle/HeLa/.

Cell Cycle↗