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James D Brenton

Publications and source records attributed to James D Brenton.

18 recordsLinked to original sources
PubMed2007

Genomic analysis of the 8p11-12 amplicon in familial breast cancer.

Amplification of 8p11-12 has been recurrently reported in sporadic breast cancer. These studies define a complex molecular structure with a set of minimal amplified regions, and different putative oncogenes that show a strong correlation between amplification and over-expression such as ZNF703/FLJ14299, SPFH2/C8orf2, BRF2 and RAB11FIP. However, none of these studies were carried out on familial breast malignancies. We have studied the incidence, molecular features and clinical value of this amplification in familial breast tumors associated with BRCA1, BRCA2 and non-BRCA1/2 gene mutations. We detected 9 out of 80 familial tumors with this amplicon by chromosomal comparative genomic hybridization. Next, we used a high-resolution comparative genomic hybridization array covering the 8p11-12 region to characterize this chromosomal region. This approach allowed us to define 2 cores of common amplification that largely overlap with those reported in sporadic tumors. Our findings confirm the molecular complexity of this chromosomal region and indicate that this genomic event is a common alteration in breast cancer, present not only in sporadic but also in familial tumors. Finally, we found correlation between the 8p11-12 amplification and proliferation (Ki-67) and cyclin E expression, which further proves in familial tumors the poor prognosis association previously reported in sporadic breast cancer.

Adult↗
PubMed2006

A consensus prognostic gene expression classifier for ER positive breast cancer.

BACKGROUND: A consensus prognostic gene expression classifier is still elusive in heterogeneous diseases such as breast cancer. RESULTS: Here we perform a combined analysis of three major breast cancer microarray data sets to hone in on a universally valid prognostic molecular classifier in estrogen receptor (ER) positive tumors. Using a recently developed robust measure of prognostic separation, we further validate the prognostic classifier in three external independent cohorts, confirming the validity of our molecular classifier in a total of 877 ER positive samples. Furthermore, we find that molecular classifiers may not outperform classical prognostic indices but that they can be used in hybrid molecular-pathological classification schemes to improve prognostic separation. CONCLUSION: The prognostic molecular classifier presented here is the first to be valid in over 877 ER positive breast cancer samples and across three different microarray platforms. Larger multi-institutional studies will be needed to fully determine the added prognostic value of molecular classifiers when combined with standard prognostic factors.

Breast Neoplasms↗
PubMed2006

MMASS: an optimized array-based method for assessing CpG island methylation.

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation.

Cell Line, Tumor↗
PubMed2006

Metabolic consequences of p300 gene deletion in human colon cancer cells.

Metabolite profiling using (1)H nuclear magnetic resonance (NMR) spectroscopy was used to investigate the metabolic changes associated with deletion of the gene for the transcriptional coactivator p300 in the human colon carcinoma cell line HCT116. Multivariate statistical methods were used to distinguish between metabolite patterns that were dependent on cell growth conditions and those that were specifically associated with loss of p300 function. In the absence of serum, wild-type cells showed slower growth, which was accompanied by a marked decrease in phosphocholine concentration, which was not observed in otherwise isogenic cell lines lacking p300. In the presence of serum, several metabolites were identified as being significantly different between the two cell types, including glutamate and glutamine, a nicotinamide-related compound and glycerophosphocholine (GPC). However, in the absence of serum, these metabolites, with the exception of GPC, were not significantly different, leading us to conclude that most of these changes were context dependent. Transcript profiling, using DNA microarrays, showed changes in the levels of transcripts for several enzymes involved in choline metabolism, which might explain the change in GPC concentration. Localized in vivo (1)H NMR measurements on the tumors formed following s.c. implantation of these cells into mice showed an increase in the intensity of the peak from choline-containing compounds in the p300(-) tumors. These data show that NMR-based metabolite profiling has sufficient sensitivity to identify the metabolic consequences of p300 gene deletion in tumor cells in vitro and in vivo.

Animals↗
PubMed2006

Differential expression of selected histone modifier genes in human solid cancers.

BACKGROUND: Post-translational modification of histones resulting in chromatin remodelling plays a key role in the regulation of gene expression. Here we report characteristic patterns of expression of 12 members of 3 classes of chromatin modifier genes in 6 different cancer types: histone acetyltransferases (HATs)- EP300, CREBBP, and PCAF; histone deacetylases (HDACs)- HDAC1, HDAC2, HDAC4, HDAC5, HDAC7A, and SIRT1; and histone methyltransferases (HMTs)- SUV39H1and SUV39H2. Expression of each gene in 225 samples (135 primary tumours, 47 cancer cell lines, and 43 normal tissues) was analysedby QRT-PCR, normalized with 8 housekeeping genes, and given as a ratio by comparison with a universal reference RNA. RESULTS: This involved a total of 13,000 PCR assays allowing for rigorous analysis by fitting a linear regression model to the data. Mutation analysis of HDAC1, HDAC2, SUV39H1, and SUV39H2 revealed only two out of 181 cancer samples (both cell lines) with significant coding-sequence alterations. Supervised analysis and Independent Component Analysis showed that expression of many of these genes was able to discriminate tumour samples from their normal counterparts. Clustering based on the normalized expression ratios of the 12 genes also showed that most samples were grouped according to tissue type. Using a linear discriminant classifier and internal cross-validation revealed that with as few as 5 of the 12 genes, SIRT1, CREBBP, HDAC7A, HDAC5 and PCAF, most samples were correctly assigned. CONCLUSION: The expression patterns of HATs, HDACs, and HMTs suggest these genes are important in neoplastic transformation and have characteristic patterns of expression depending on tissue of origin, with implications for potential clinical application.

Breast Neoplasms↗
PubMed2005

Molecular classification and molecular forecasting of breast cancer: ready for clinical application?

Profiling breast cancer with expression arrays has become common, and it has been suggested that the results from early studies will lead to understanding of the molecular differences between clinical cases and allow individualization of care. We critically review two main applications of expression profiling; studies unraveling novel breast cancer classifications and those that aim to identify novel markers for prediction of clinical outcome. Breast cancer may now be subclassified into luminal, basal, and HER2 subtypes with distinct differences in prognosis and response to therapy. However, profiling studies to identify predictive markers have suffered from methodologic problems that prevent general application of their results. Future work will need to reanalyze existing microarray data sets to identify more representative sets of candidate genes for use as prognostic signatures and will need to take into account the new knowledge of molecular subtypes of breast cancer when assessing predictive effects.

Biomarkers, Tumor↗
PubMed2005

A 1 Mb minimal amplicon at 8p11-12 in breast cancer identifies new candidate oncogenes.

Amplification of 8p11-12 is a well-known alteration in human breast cancers but the driving oncogene has not been identified. We have developed a high-resolution comparative genomic hybridization array covering 8p11-12 and analysed 33 primary breast tumors, 20 primary ovarian tumors and 27 breast cancer cell lines. Expression analysis of the genes in the region was carried out by using real-time quantitative PCR and/or oligo-microarray profiling. In all, 24% (8/33) of the breast tumors, 5% (1/20) of the ovary tumors and 15% (4/27) of the cell lines showed 8p11-12 amplification. We identified a 1 Mb segment of common amplification that excludes previously proposed candidate genes. Some of the amplified genes did not show overexpression, whereas for others, overexpression was not specifically attributable to amplification. The genes FLJ14299, C8orf2, BRF2 and RAB11FIP, map within the 8p11-12 minimal amplicon, two have a putative function consistent with an oncogenic role, these four genes showed a strong correlation between amplification and overexpression and are therefore the best candidate driver oncogenes at 8p12.

Breast Neoplasms↗
PubMed2005

A variational Bayesian mixture modelling framework for cluster analysis of gene-expression data.

MOTIVATION: Accurate subcategorization of tumour types through gene-expression profiling requires analytical techniques that estimate the number of categories or clusters rigorously and reliably. Parametric mixture modelling provides a natural setting to address this problem. RESULTS: We compare a criterion for model selection that is derived from a variational Bayesian framework with a popular alternative based on the Bayesian information criterion. Using simulated data, we show that the variational Bayesian method is more accurate in finding the true number of clusters in situations that are relevant to current and future microarray studies. We also compare the two criteria using freely available tumour microarray datasets and show that the variational Bayesian method is more sensitive to capturing biologically relevant structure.

Algorithms↗
PubMed2005

Microarrays and breast cancer clinical studies: forgetting what we have not yet learnt.

This review takes a sceptical view of the impact of breast cancer studies that have used microarrays to identify predictors of clinical outcome. In addition to discussing general pitfalls of microarray experiments, we also critically review the key breast cancer studies to highlight methodological problems in cohort selection, statistical analysis, validation of results and reporting of raw data. We conclude that the optimum use of microarrays in clinical studies requires further optimisation and standardisation of methodology and reporting, together with improvements in clinical study design.

Breast Neoplasms↗
PubMed2005

The External RNA Controls Consortium: a progress report.

Standard controls and best practice guidelines advance acceptance of data from research, preclinical and clinical laboratories by providing a means for evaluating data quality. The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.

Animals↗
PubMed2005

Optimal amounts of fluorescent dye improve expression microarray results in tumor specimens.

Expression microarrays have great potential for clinical use but variability of the results represents a challenge for reliable practical application. The amount of fluorescent dye used in microarray experiments is a significant source of variability that has not been systematically studied. Here we demonstrate that the quantity of Cy3 dye affects microarray results performed on tumor specimens. Signal-to-noise ratios and coefficients of variation are significantly improved by increasing Cy3 to 150-180 pmol, but any further increase does not improve the data. In conclusion, optimal amounts of dye reduce variability and improve reliability of expression microarray experiments.

Carbocyanines↗
PubMed2004

Microarray segmentation methods significantly influence data precision.

Little consideration has been given to the effect of different segmentation methods on the variability of data derived from microarray images. Previous work has suggested that the significant source of variability from microarray image analysis is from estimation of local background. In this study, we used Analysis of Variance (ANOVA) models to investigate the effect of methods of segmentation on the precision of measurements obtained from replicate microarray experiments. We used four different methods of spot segmentation (adaptive, fixed circle, histogram and GenePix) to analyse a total number of 156 172 spots from 12 microarray experiments. Using a two-way ANOVA model and the coefficient of repeatability, we show that the method of segmentation significantly affects the precision of the microarray data. The histogram method gave the lowest variability across replicate spots compared to other methods, and had the lowest pixel-to-pixel variability within spots. This effect on precision was independent of background subtraction. We show that these findings have direct, practical implications as the variability in precision between the four methods resulted in different numbers of genes being identified as differentially expressed. Segmentation method is an important source of variability in microarray data that directly affects precision and the identification of differentially expressed genes.

Algorithms↗
PubMed2004

Expression microarray reproducibility is improved by optimising purification steps in RNA amplification and labelling.

BACKGROUND: Expression microarrays have evolved into a powerful tool with great potential for clinical application and therefore reliability of data is essential. RNA amplification is used when the amount of starting material is scarce, as is frequently the case with clinical samples. Purification steps are critical in RNA amplification and labelling protocols, and there is a lack of sufficient data to validate and optimise the process. RESULTS: Here the purification steps involved in the protocol for indirect labelling of amplified RNA are evaluated and the experimentally determined best method for each step with respect to yield, purity, size distribution of the transcripts, and dye coupling is used to generate targets tested in replicate hybridisations. DNase treatment of diluted total RNA samples followed by phenol extraction is the optimal way to remove genomic DNA contamination. Purification of double-stranded cDNA is best achieved by phenol extraction followed by isopropanol precipitation at room temperature. Extraction with guanidinium-phenol and Lithium Chloride precipitation are the optimal methods for purification of amplified RNA and labelled aRNA respectively. CONCLUSION: This protocol provides targets that generate highly reproducible microarray data with good representation of transcripts across the size spectrum and a coefficient of repeatability significantly better than that reported previously.

Carbocyanines↗
PubMed2002

Constitutive p38HOG mitogen-activated protein kinase activation induces permanent cell cycle arrest and senescence.

Cellular senescence, initially observed during subculturing of normal diploid fibroblasts, can also be induced by chronic exposure to cellular stress, such as UV light, oxidative stress, or DNA damaging agents. Here we demonstrate that stable expression of an activated form of MKK6 (MKK6EE), a direct activator of the stress-induced p38(HOG) mitogen-activated protein kinase pathway, is sufficient for inducing features of senescence including a flattened, vacuolated, and irregular morphology, staining for acidic beta-galactosidase, and accumulation of age-associated pigments. Consistent with the senescent phenotype, p38(HOG) activation induces a G(1) cell cycle arrest, which is permanent and irreversible after 4 days. MKK6EE also induces biochemical features of senescence in a p38-dependent manner, including enhanced expression of p21(CIP), a cyclin-dependent kinase inhibitor. Microarray analysis of MKK6EE cells showed a pattern of gene expression noted previously in Werner Syndrome and senescent fibroblasts. These results define p38(HOG) as an intracellular pathway that activates a senescence checkpoint in tumor cells and may play a role in Ras- or stress-induced senescence.

Calcium-Calmodulin-Dependent Protein Kinases↗
PubMed2002

Parallel analysis of sporadic primary ovarian carcinomas by spectral karyotyping, comparative genomic hybridization, and expression microarrays.

Analysis of ovarian carcinomas has shown that karyotypes are often highly abnormal and cannot be identified with certainty by conventional cytogenetic methods. In this study, 17 tumors derived from 13 patients were analyzed by a combination of spectral karyotyping (SKY), comparative genomic hybridization (CGH), and expression microarrays. Within the study group, a total of 396 chromosomal rearrangements could be identified by SKY and CGH analysis. When the distribution of aberrations was normalized with respect to relative genomic length, chromosomes 3, 8, 11, 17, and 21 had the highest frequencies. Parallel microarray expression studies of 1718 human cDNAs were used to analyze expression profiles and to determine whether correlating gene expression with chromosomal rearrangement would identify smaller subsets of differentially expressed genes. Within the entire set of samples, microarray expression analysis grouped together poorly differentiated tumors irrespective of histological subtype. For three patients, a comparison between genomic alterations and gene expression pattern was performed on samples of primary and metastatic tumors. Their common origin was demonstrated by the close relationship of both the SKY and CGH karyotypes and the observed profiles of gene expression. In agreement with the pattern of genomic imbalance observed for chromosome 3 in ovarian cancer, the relative expression profile with respect to a normal ovary exhibited a contiguous pattern of reduced expression of genes mapping to the 3p25.5-3p21.31 and increased expression of genes from 3q13.33-3q28. This study demonstrates that SKY, CGH, and microarray analysis can in combination identify significantly smaller subsets of differentially expressed genes for future studies.

Adult↗
PubMed2002

Novel conserved elements upstream of the H19 gene are transcribed and act as mesodermal enhancers.

The reciprocally imprinted H19 and Igf2 genes form a co-ordinately regulated 130 kb unit in the mouse controlled by widely dispersed enhancers, epigenetically modified silencers and an imprinting control region (ICR). Comparative human and mouse genomic sequencing between H19 and Igf2 revealed two novel regions of strong homology upstream of the ICR termed H19 upstream conserved regions (HUCs). Mouse HUC1 and HUC2 act as potent enhancers capable of driving expression of an H19 reporter gene in a range of mesodermal tissues. Intriguingly, the HUC sequences are also transcribed bi-allelically in mouse and human, but their expression pattern in neural and endodermal tissues in day 13.5 embryos is distinct from their enhancer function. The location of the HUC mesodermal enhancers upstream of the ICR and H19, and their capacity for interaction with both H19 and Igf2 requires critical re-evaluation of the cis-regulation of imprinted gene expression of H19 and Igf2 in a range of mesodermal tissues. We propose that these novel sequences interact with the ICR at H19 and the epigenetically regulated silencer at differentially methylated region 1 (DMR1) of Igf2.

Animals↗