Searching for differentially expressed gene combinations

We propose 'CorScor', a novel approach for identifying gene pairs with joint differential expression. This is defined as a situation with good phenotype discrimination in the bivariate, but not in the two marginal distributions. CorScor can be used to detect phenotype-related dependencies and interactions among genes. Our easily interpretable approach is scalable to current microarray dimensions and yields promising results on several cancer-gene-expression datasets

The Integrative Correlation Coefficient: a Measure of Cross-study Reproducibility for Gene Expressionea Array Data

Multi-study analysis adds value to microarray experiments. However, because of significant technical differences between microarray platforms, and because of differences in study design, it can be difficult to combine data. We have developed a statistical measure of reproducibility that can be applied to individual genes, measured in two different studies. This statistic, which we call the Integrative Correlation Coefficient or Correlation of Correlations, borrows strength across many genes to estimate the strength of the relationship between expression values in the two studies

Nuclear genes involved in mitochondria-to-nucleus communication in breast cancer cells

BACKGROUND: The interaction of nuclear and mitochondrial genes is an essential feature in maintenance of normal cellular function. Of 82 structural subunits that make up the oxidative phosphorylation system in the mitochondria, mitochondrial DNA (mtDNA) encodes 13 subunits and rest of the subunits are encoded by nuclear DNA. Mutations in mitochondrial genes encoding the 13 subunits have been reported in a variety of cancers. However, little is known about the nuclear response to impairment of mitochondrial function in human cells. RESULTS: We isolated a Rho(0) (devoid of mtDNA) derivative of a breast cancer cell line. Our study suggests that depletion of mtDNA results in oxidative stress, causing increased lipid peroxidation in breast cancer cells. Using a cDNA microarray we compared differences in the nuclear gene expression profile between a breast cancer cell line (parental Rho(+)) and its Rho(0) derivative impaired in mitochondrial function. Expression of several nuclear genes involved in cell signaling, cell architecture, energy metabolism, cell growth, apoptosis including general transcription factor TFIIH, v-maf, AML1, was induced in Rho(0) cells. Expression of several genes was also down regulated. These include phospholipase C, agouti related protein, PKC gamma, protein tyrosine phosphatase C, phosphodiestarase 1A (cell signaling), PIBF1, cytochrome p450, (metabolism) and cyclin dependent kinase inhibitor p19, and GAP43 (cell growth and differentiation). CONCLUSIONS: Mitochondrial impairment in breast cancer cells results in altered expression of nuclear genes involved in signaling, cellular architecture, metabolism, cell growth and differentiation, and apoptosis. These genes may mediate the cross talk between mitochondria and the nucleus

Cross-study Validation and Combined Analysis of Gene Expression Microarray Data

Investigations of transcript levels on a genomic scale using hybridization-based arrays led to formidable advances in our understanding of the biology of many human illnesses. At the same time, these investigations have generated controversy, because of the probabilistic nature of the conclusions, and the surfacing of noticeable discrepancies between the results of studies addressing the same biological question. In this article we present simple and effective data analysis and visualization tools for gauging the degree to which the finding of one study are reproduced by others, and for integrating multiple studies in a single analysis. We describe these approaches in the context of studies of breast cancer, and illustrate that it is possible to identify a substantial, biologically relevant subset of the human genome within which hybridization results are reproducible. The subset generally varies with the platforms used, the tissues studied, and the populations being sampled. Despite important differences, it is also possible to develop simple expression measures that allow comparison across platforms, studies, labs and populations. Important biological signal is often preserved or enhanced. Cross-study validation and combination of microarray results requires careful, but not overly complex, statistical thinking, and can become a routine component of genomic analysis

Electron paramagnetic resonance evidence that cellular oxygen toxicity is caused by the generation of superoxide and hydroxyl free radicals

AbstractCells require molecular oxygen for the generation of energy through mitochondrial oxidative phosphorylation; however, high concentrations of oxygen are toxic and can cause cell death. A number of different mechanisms have been proposed to cause cellular oxygen toxicity. One hypothesis is that reactive oxygen free radicals may be generated; however free radical generation in hyperoxic cells has never been directly measured and the mechanism of this radical generation is unknown. In order to determine if cellular oxygen toxicity is free radical mediated, we applied electron paramagnetic resonance, EPR, spectroscopy using the spin trap 5,5′-dimethyl-1-pyrroline-N-oxide, DMPO, to measure free radical generation in hyperoxic pulmonary endothelial cells. Cells in air did not give rise to any detectable signal. However, cells exposed to 100% O2 for 30 min exhibited a prominent signal of trapped hydroxyl radical, DMPO-OH, while cell free buffer did not give rise to any detectable radical generation. This cellular radical generation was demonstrated to be derived from the superoxide radical since the observed signal was totally quenched by superoxide dismutase, but not by equal concentrations of the denatured enzyme. It was confirmed that the hydroxyl radical was generated since in the presence of ethanol the CH3·CH(OH) radical was formed. Loss of cell viability as measured by uptake of trypan blue dye was observed paralleling the measured free radical generation. Thus, superoxide and hydroxyl radicals are generated in hyperoxic pulmonary endothelial cells and this appears to be an important mechanism of cellular oxygen toxicity

OPTIMIZED CROSS-STUDY ANALYSIS OF MICROARRAY-BASED PREDICTORS

Background: Microarray-based gene expression analysis is widely used in cancer research to discover molecular signatures for cancer classification and prediction. In addition to numerous independent profiling projects, a number of investigators have analyzed multiple published data sets for purposes of cross-study validation. However, the diverse microarray platforms and technical approaches make direct comparisons across studies difficult, and without means to identify aberrant data patterns, less than optimal. To address this issue, we previously developed an integrative correlation approach to systematically address agreement of gene expression measurements across studies, providing a basis for cross-study validation analysis. Here we generalize this methodology to provide a metric for evaluating the overall efficacy of preprocessing and cross-referencing, and explore optimal combinations of filtering and cross-referencing strategies. We operate in the context of validating prognostic breast cancer gene expression signatures on data reported by three different groups, each using a different platform. Results: To evaluate overall cross-platform reproducibility in the context of a specific prediction problem, we suggest integrative association, that is the cross-study correlation of gene-specific measure of association with the phenotype predicted. Specifically, in this paper we use the correlation among the Cox proportional hazard coefficients for association of gene expression to relapse free survival (RFS). Gene filtering by integrative correlation to select reproducible genes emerged as the key factor to increase the integrative association, while alternative methods of gene cross-referencing and gene filtering proved only to modestly improve the overall reproducibility. Patient selection was another major factor affecting the validation process. In particular, in one of the studies considered, gene expression association with RFS varied across subsets of patients that differ by their ascertainment criteria. One of the subsets proved to be highly consistent with other studies, while others showed significantly lower consistency. Third, as expected, use of cluster-specific mean expression profiles in the Cox model yielded more generalizable results than expression data from individual genes. Finally, by using our approach we were able to validate the association between the breast cancer molecular classes proposed by Sorlie et al. and RFS. Conclusions: This paper provides a simple, practical and comprehensive technique for measuring consistency of molecular classification results across microarray platforms, without requiring subjective judgments about membership of samples in putative clusters. This methodology will be of value in consistently typing breast and other cancers across different studies and platforms in the future. Although the tumor subtypes considered here have been previously validated by their proponents, this is the first independent validation, and the first to include the Affymetrix platform

Initial Results from the Variable Intensity Sonic Boom Propagation Database

An extensive sonic boom propagation database with low- to normal-intensity booms (overpressures of 0.08 lbf/sq ft to 2.20 lbf/sq ft) was collected for propagation code validation, and initial results and flight research techniques are presented. Several arrays of microphones were used, including a 10 m tall tower to measure shock wave directionality and the effect of height above ground on acoustic level. A sailplane was employed to measure sonic booms above and within the atmospheric turbulent boundary layer, and the sailplane was positioned to intercept the shock waves between the supersonic airplane and the ground sensors. Sailplane and ground-level sonic boom recordings were used to generate atmospheric turbulence filter functions showing excellent agreement with ground measurements. The sonic boom prediction software PCBoom4 was employed as a preflight planning tool using preflight weather data. The measured data of shock wave directionality, arrival time, and overpressure gave excellent agreement with the PCBoom4-calculated results using the measured aircraft and atmospheric data as inputs. C-weighted acoustic levels generally decreased with increasing height above the ground. A-weighted and perceived levels usually were at a minimum for a height where the elevated microphone pressure rise time history was the straightest, which is a result of incident and ground-reflected shock waves interacting

Enhanced autoantigen expression in regenerating muscle cells in idiopathic inflammatory myopathy

Unique autoantibody specificities are strongly associated with distinct clinical phenotypes, making autoantibodies useful for diagnosis and prognosis. To investigate the mechanisms underlying this striking association, we examined autoantigen expression in normal muscle and in muscle from patients with autoimmune myositis. Although myositis autoantigens are expressed at very low levels in control muscle, they are found at high levels in myositis muscle. Furthermore, increased autoantigen expression correlates with differentiation state, such that myositis autoantigen expression is increased in cells that have features of regenerating muscle cells. Consistent with this, we found that cultured myoblasts express high levels of autoantigens, which are strikingly down-regulated as cells differentiate into myotubes in vitro. These data strongly implicate regenerating muscle cells rather than mature myotubes as the source of ongoing antigen supply in autoimmune myositis. Myositis autoantigen expression is also markedly increased in several cancers known to be associated with autoimmune myositis, but not in their related normal tissues, demonstrating that tumor cells and undifferentiated myoblasts are antigenically similar. We propose that in cancer-associated myositis, an autoimmune response directed against cancer cross-reacts with regenerating muscle cells, enabling a feed-forward loop of tissue damage and antigen selection. Regulating pathways of antigen expression may provide unrecognized therapeutic opportunities in autoimmune diseases

Tumor and serum DNA methylation in women receiving preoperative chemotherapy with or without vorinostat in TBCRC008

BACKGROUND: Methylated gene markers have shown promise in predicting breast cancer outcomes and treatment response. We evaluated whether baseline and changes in tissue and serum methylation levels would predict pathological complete response (pCR) in patients with HER2-negative early breast cancer undergoing preoperative chemotherapy. METHODS: The TBCRC008 trial investigated pCR following 12 weeks of preoperative carboplatin and albumin-bound paclitaxel + vorinostat/placebo (n = 62). We measured methylation of a 10-gene panel by quantitative multiplex methylation-specific polymerase chain reaction and expressed results as cumulative methylation index (CMI). We evaluated association between CMI level [baseline, day 15 (D15), and change] and pCR using univariate and multivariable logistic regression models controlling for treatment and hormone receptor (HR) status, and performed exploratory subgroup analyses. RESULTS: In univariate analysis, one log unit increase in tissue CMI levels at D15 was associated with 40% lower chance of obtaining pCR (odds ratio, OR 0.60, 95% CI 0.37-0.97; p = 0.037). Subgroup analyses suggested a significant association between tissue D15 CMI levels and pCR in vorinostat-treated [OR 0.44 (0.20, 0.93), p = 0.03], but not placebo-treated patients. CONCLUSION: In this study investigating the predictive roles of tissue and serum CMI levels in patients with early breast cancer for the first time, we demonstrate that high D15 tissue CMI levels may predict poor response. Larger studies and improved analytical procedures to detect methylated gene markers in early stage breast cancer are needed. TBCRC008 is registered on ClinicalTrials.gov (NCT00616967)