Largest Fold Change Research Articles

2,3,7,8-Tetrachlorodibenzo-p-dioxin induces a proteomic pattern that defines cleft palate formation in mice

ObjectiveTo identify the differential protein pattern in 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) induced cleft palates using a proteomic approach. MethodsAt gestation day (GD) 12, TCDD (64g/kg; n=30) or corn oil control (n=30) was given to time-pregnant C57BL/6J mice by gavage. The anatomical, histological, proteomic changes in the palates of the fetal mice were studied on GD18. Total protein was extracted from the palate tissue and examined by 2-dimensional gel electrophoresis (2-DE). Spots differentially expressed between the two groups were selected for analysis by matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS). The proteins were identified by data searching in the Mascot database. ResultsIn TCDD group, the incidence of cleft palate was 100%. Ten differential protein spots with the largest fold change were selected for further identification by mass spectrometry, 7 showed significantly higher volumes and 3 showed significantly lower volumes in TCDD palates than the control palates (all p<0.05). Peroxiredoxin-1 were robustly up-regulated in the cleft palate group, as well proteins linked to energy metabolism, cell migration, and apoptosis. ConclusionsPeroxiredoxin-1 protein may be associated with cleft palate in mice induced by TCDD. The embryo mouse palate tissues energy metabolism cells migration/apoptosis related proteins have the disorder.

Abstract 2956: High throughput RNAi screening of synthetic lethal genes interacting with the common TP53 mutation R175H

Abstract The R175H mutation of p53 which account for approximately 6% of the missense mutations of identified in human cancer is one of the most common mutations, and cancer cells with this mutation stably express the R175H protein in the nucleus. Targeting R175H overexpressing cells by synthetic lethality is one of the extremely effective strategies for cancer therapy. To identify the synthetic lethal gene interacting with R175H, we conducted high throughput screening using a tetracycline-inducible R175H expression system in SF126 cells and comprehensive shRNA library carried by lentivirus. We identified 906 candidate gene suppressions that may lead to accelerated cell growth inhibition in the presence of R175H (p&amp;lt;0.05, n=3). Among these, we selected 50 genes (21 genes from the group with the smallest p-values, 20 genes from the group with the largest fold change, and 9 genes reproduced by different siRNA sequences) for further validation testing. By transfection of siRNA of these candidate genes into five R175H expressing cell lines and four TP53-null cell lines, we selected five candidate genes that significantly lead R175H expressing cells to strong cell growth inhibition. Inhibitor of differentiation 1 (ID1) was one of the five candidate genes, and its suppression by siRNA resulted in the acceleration of growth inhibition in cell lines expressing endogenous R175H; however, this was not observed in TP53-null cell lines. The transient expression of R175H in TP53-null cell lines (PC3) and suppression of ID1 and/or TP53 R175H in cell lines with endogenous R175H revealed that cell growth inhibition by ID1 suppression depended on the expression of R175H, and not that of other common p53 mutants (e.g., R273H). Flow cytometric analysis exhibited that ID1 suppression resulted in G1 arrest, and the arrest was accelerated by the expression of R175H. In conclusion, ID1 is a synthetic lethal gene that interacts with R175H and is considered to be a novel molecular target for cancer therapy in R175H expressing cells. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2956. doi:1538-7445.AM2012-2956

Abstract 4204: Gene expression changes of DNA repair genes in lymphocytes of breast cancer patients

Abstract Breast cancer is the most commonly diagnosed cancer among women in Puerto Rico. Previous studies have shown that dysregulation of DNA repair genes expression is important for carcinogenesis. However, most of the studies have focused on measuring DNA repair gene expression levels in tumor samples. Our preliminary studies had shown that women with decreased DNA repair capacity (DRC) are at increased risk of breast cancer. We hypothesized that changes in DRC levels may be partly explained by changes in gene expression of DNA repair genes. Our objective was to assess the contribution of the expression levels of 43 DNA repair and damage response genes in lymphocytes of breast cancer cases and controls of Puerto Rican origin. We measured the gene expression profile of 43 DNA repair genes in lymphocytes of 6 breast cancer cases with low DRC and 10 controls with high DRC using a custom SuperArray (SABiosciences). Of the 43 genes analyzed through the SuperArray, XPC, CETN2 and CCNH showed the largest fold-changes. To validate the results, we used a TaqMan-based gene expression assay in lymphocytes of 30 breast cancer cases and 30 controls. Our results showed that breast cancer cases had a 3.4x less XPC expression (p=0.002) and 2.2x less CCNH expression (p=0.01) than controls. Validation of the CETN2 SuperArray results is underway. In conclusion, we found that the XPC gene and CCNH were expressed less in breast cancer cases than in controls. Understanding the gene expression changes that occur prior to tumor development is an important step towards enhancing cancer prevention and detection strategies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4204. doi:1538-7445.AM2012-4204

NSI and NSMT: usages of MS/MS fragment ion intensity for sensitive differential proteome detection and accurate protein fold change calculation in relative label-free proteome quantification

Although widely applied in the label-free quantification of proteomics, spectral count (SC)-based abundance measurements suffer from the narrow dynamic range of attainable ratios, leading to the serious underestimation of true protein abundance fold changes, especially when studying biological samples that exhibit very large fold changes in protein expression. MS/MS fragment ion intensity, as an alternative to SC, has recently gained acceptance as the abundance feature of protein in label-free proteomic studies. Herein, we implemented two formats of MS/MS fragment ion intensity, Spectral Index (SI) and Summed MS/MS TIC (SMT), to alleviate this particular deficiency arising from SC. Both were in forms of replacing SC in the Normalized Spectral Abundance Factor (NSAF) formula, resulting in two algorithms, abbreviated as NSI and NSMT, respectively. The necessity of the normalization process was validated using a publicly available dataset. Furthermore, when applied to another well characterized benchmark dataset, both NSI and NSMT showed improved overall accuracy over NSAF for the relative quantification of proteomes. Hereinto, NSI enabled the sensitive detection of differentially expressed proteins, while NSMT ensured accurate calculation for protein abundance fold change. Therefore, the selective use of both algorithms might facilitate the screening and quantification of potential biomarkers on the proteome scale.

Identification of early target genes of aflatoxin B1 in human hepatocytes, inter-individual variability and comparison with other genotoxic compounds

Gene expression profiling has recently emerged as a promising approach to identify early target genes and discriminate genotoxic carcinogens from non-genotoxic carcinogens and non-carcinogens. However, early gene changes induced by genotoxic compounds in human liver remain largely unknown. Primary human hepatocytes and differentiated HepaRG cells were exposed to aflatoxin B1 (AFB1) that induces DNA damage following enzyme-mediated bioactivation. Gene expression profile changes induced by a 24 h exposure of these hepatocyte models to 0.05 and 0.25 μM AFB1 were analyzed by using oligonucleotide pangenomic microarrays. The main altered signaling pathway was the p53 pathway and related functions such as cell cycle, apoptosis and DNA repair. Direct involvement of the p53 protein in response to AFB1 was verified by using siRNA directed against p53. Among the 83 well-annotated genes commonly modulated in two pools of three human hepatocyte populations and HepaRG cells, several genes were identified as altered by AFB1 for the first time. In addition, a subset of 10 AFB1-altered genes, selected upon basis of their function or tumor suppressor role, was tested in four human hepatocyte populations and in response to other chemicals. Although they exhibited large variable inter-donor fold-changes, several of these genes, particularly FHIT, BCAS3 and SMYD3, were found to be altered by various direct and other indirect genotoxic compounds and unaffected by non-genotoxic compounds. Overall, this comprehensive analysis of early gene expression changes induced by AFB1 in human hepatocytes identified a gene subset that included several genes representing potential biomarkers of genotoxic compounds.

Reporting FDR analogous confidence intervals for the log fold change of differentially expressed genes

BackgroundGene expression experiments are common in molecular biology, for example in order to identify genes which play a certain role in a specified biological framework. For that purpose expression levels of several thousand genes are measured simultaneously using DNA microarrays. Comparing two distinct groups of tissue samples to detect those genes which are differentially expressed one statistical test per gene is performed, and resulting p-values are adjusted to control the false discovery rate. In addition, the expression change of each gene is quantified by some effect measure, typically the log fold change. In certain cases, however, a gene with a significant p-value can have a rather small fold change while in other cases a non-significant gene can have a rather large fold change. The biological relevance of the change of gene expression can be more intuitively judged by a fold change then merely by a p-value. Therefore, confidence intervals for the log fold change which accompany the adjusted p-values are desirable.ResultsIn a new approach, we employ an existing algorithm for adjusting confidence intervals in the case of high-dimensional data and apply it to a widely used linear model for microarray data. Furthermore, we adopt a concept of different relevance categories for effects in clinical trials to assess biological relevance of genes in microarray experiments. In a brief simulation study the properties of the adjusting algorithm are maintained when being combined with the linear model for microarray data. In two cancer data sets the adjusted confidence intervals can indicate significance of large fold changes and distinguish them from other large but non-significant fold changes. Adjusting of confidence intervals also corrects the assessment of biological relevance.ConclusionsOur new combination approach and the categorization of fold changes facilitates the selection of genes in microarray experiments and helps to interpret their biological relevance.

Kinetic modeling sheds light on the mode of action of recombinant factor VIIa on thrombin generation

IntroductionThe therapeutic potential of a hemostatic agent can be assessed by investigating its effects on the quantitative parameters of thrombin generation. For recombinant activated factor VII (rFVIIa) ― a promising hemostasis-inducing biologic ― experimental studies addressing its effects on thrombin generation yielded disparate results. To elucidate the inherent ability of rFVIIa to modulate thrombin production, it is necessary to identify rFVIIa-induced effects that are compatible with the available biochemical knowledge about thrombin generation mechanisms. Materials and MethodsThe existing body of knowledge about coagulation biochemistry can be rigorously represented by a computational model that incorporates the known reactions and parameter values constituting the biochemical network. We used a thoroughly validated numerical model to generate activated factor VII (FVIIa) titration curves in the cases of normal blood composition, hemophilia A and B blood, blood lacking factor VII, blood lacking tissue factor pathway inhibitor, and diluted blood. We utilized the generated curves to perform systematic fold-change analyses for five quantitative parameters characterizing thrombin accumulation. ResultsThe largest fold changes induced by increasing FVIIa concentration were observed for clotting time, thrombin peak time, and maximum slope of the thrombin curve. By contrast, thrombin peak height was much less affected by FVIIa titrations, and the area under the thrombin curve stayed practically unchanged. Comparisons with experimental data demonstrated that the computationally derived patterns can be observed in vitro. ConclusionsrFVIIa modulates thrombin generation primarily by accelerating the process, without significantly affecting the total amount of generated thrombin.

Finding Interesting Genes Using Reliability in Various Gene Expression Models

Most statistical methods for finding interesting genes are focusing on the summary values with large fold-changes or large variations. Very few methods consider the probe level data. We developed a new measure to detect reliability that incorporates the probe level data. This reliability measure is useful for exploring the microarray data without ignoring the probe level data. It is easy to calculate, and it can be used for all the other statistical methods as a good guideline to find real differentially expressed genes. Instead of filtering out genes before the analysis, we use whole genes in the analysis and make decisions with new reliability measures.

Quantitative Power Doppler Ultrasonography Is a Sensitive Measure of Metacarpophalangeal Joint Synovial Vascularity in Rheumatoid Arthritis and Declines Significantly Following a 2-week Course of Oral Low-dose Corticosteroids

To investigate the stability over 2 weeks of ultrasonographic assessments of synovial thickness and vascularity in all 10 metacarpophalangeal joints of subjects with rheumatoid arthritis (RA) with a range of disease activities as measured by the validated Disease Activity Score-28 joint score (DAS28-ESR). And in subjects with severe disease activity, to compare the sensitivity of these measurements, acute-phase markers, and vascular endothelial growth factor to change in response to 2 weeks of oral prednisolone (7.5 mg daily). A group of 38 subjects with RA were enrolled, 13 (mean DAS28 2.1), 14 (mean DAS28 5.2), and 11 (mean DAS28 5.7) meriting oral corticosteroid treatment. Synovial thickness and vascularity were assessed by ultrasonography at 3 timepoints. Images were ranked by semiquantitative scale. Vascularity was also measured by quantitative determination of the power Doppler area (PDA). In the whole RA cohort, baseline indices of synovial thickness and vascularity correlated with DAS28, as did PDA (r = 0.42, p < 0.05). In the RA groups on stable therapy, synovial thickness and vascularity showed little variation over 2 weeks. In the corticosteroid group, PDA had fold changes of -1.9-fold (p < 0.05) after 1 week and -2.2-fold (p < 0.05) after 2 weeks. These were the largest fold changes of all measured variables. Ultrasonographic measures can differentiate disease severity in RA correlating closely with DAS28. Quantitative power Doppler signal was significantly reduced within 1 week of oral prednisolone, a rapid kinetic suggesting that PDA may have value as a sensitive early marker of therapeutic response.

Primary mutations selected in vitro with raltegravir confer large fold changes in susceptibility to first-generation integrase inhibitors, but minor fold changes to inhibitors with second-generation resistance profiles

Emergence of resistance to raltegravir reduces its treatment efficacy in HIV-1-infected patients. To delineate the effect of resistance mutations on viral susceptibility to integrase inhibitors, in vitro resistance selections with raltegravir and with MK-2048, an integrase inhibitor with a second-generation-like resistance profile, were performed. Mutation Q148R arose in four out of six raltegravir-selected resistant viruses. In addition, mutations Q148K and N155H were selected. In the same time frame, no mutations were selected with MK-2048. Q148H/K/R and N155H conferred resistance to raltegravir, but only minor changes in susceptibility to MK-2048. V54I, a previously unreported mutation, selected with raltegravir, was identified as a possible compensation mutation. Mechanisms by which N155H, Q148H/K/R, Y143R and E92Q confer resistance are proposed based on a structural model of integrase. These data improve the understanding of resistance against raltegravir and cross-resistance to MK-2048 and other integrase inhibitors, which will aid in the discovery of second-generation integrase inhibitors.

Abstract LB-135: The transcriptome of p300 loss in MCF-7 cells

Abstract Introduction: p300 is a transcriptional co-activator that promotes gene transcription by acetylating DNA-binding factors and bridging them to the basal transcription machinery. Recent studies have revealed decreased levels of p300 in breast cancer cells, suggesting that p300 may be involved in the control of breast cancer growth and progression. Preliminary data from our laboratory also indicates that decreased p300 function promotes MCF-7 breast cancer cell proliferation in vitro and tumorigenesis in vivo. Methodology: In order to identify the effects of p300 loss on gene expression in breast cancer cells, microarray analysis was performed on total RNA from MCF-7 cells, stably transduced with lentiviruses expressing one of 3 p300 shRNAs or a non-silencing sequence. Silencing of p300 was &amp;gt; 50% in response to each of the shRNAs. Endogenous RNA was converted to cDNA using random primers and then to biotinylated cRNA for hybridization to human exonic evidence-based oligonucleotide microarrays (Ocean Ridge Biosciences, Palm Beach Gardens, FL). 877 genes were found to be differentially expressed in p300 knockdown MCF-7 cells compared to non-silenced controls. Differentially regulated genes were ranked according to the significance of change (p value &amp;lt; 0.0005) and compared to previously reported data in the Oncomine database, for both directionality (up versus down-regulation) and positive correlation with decreased p300 levels. As an additional strategy we ranked the differentially expressed genes from our microarray with good level of significance (p&amp;lt;0.05) by fold change and repeated the comparative analysis with Oncomine as described above. Results: In our analysis, 877 genes were found to be differentially expressed out of which 27 genes were either significantly up-regulated or down-regulated. The rest of the gene expression levels found in the microarray analysis were not as highly significant as the top 27 genes. Among those 27 genes, four (SPAG7, OAS2, RARRES3, SERPINA6) showed highly significant (p&amp;lt;0.0005) increase in their expression and five genes (DHX9, EIF4G2, POLR2D, MCM6, CYP4F2) showed highly significant decrease. Among the genes with the largest fold changes, 10 (IFI27, IFI6, ATF-3, PIK3IP1, TNFAIP3, P8, RARRES3, FOS, IRF9, and RNF39) showed significantly increased expression and 8 were decreased (WNT3A, CAMK1, CENPH, DCTN1, CASC5, HSPA4, CDC25A, and CDKN2C). The second set of genes showed correlations with p300 levels as indicated in analyses of Oncomine data. Some of these genes may be contributing to epithelial to mesenchymal- transition (EMT) under p300 knock-down conditions. Conclusions: Our microarray analysis in MCF-7 cells with partial p300 loss has identified several key genes that are related to breast cancer growth. These genes may be important in mediating the function of p300 loss in tumorigenicity, and future studies will focus on the use of p300 or its downstream signaling components as therapeutic targets in breast cancer treatment. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-135.

ITRAQ-based quantitative analysis of protein mixtures with large fold change and dynamic range

Quantitation of changes in protein abundance is key to understanding the alterations that biological systems undergo and to discovering novel biomarkers. Currently, HPLC-MS/MS can be used to quantify changes in protein expression levels [Ong, S. E. and Mann, M., Nat. Chem. Biol. 2005, 1, 252-262]. Nevertheless, quantitative analysis of protein mixtures by HPLC-MS/MS is still hampered by the wide range of protein expression levels, the high dynamic range of protein concentrations and the lack of reliable quantitation algorithms [D'Ascenzo, M., et al. Brief. Funct. Genomic. Proteomic. 2008, 7, 127-135; Lin, W. T., et al., J. Proteome Res. 2006, 5, 2328-2338; Matthiesen, R., et al. J. Proteome Res. 2005, 4, 2338-2347; Yu, C. Y., et al. Nucleic Acids Res. 2007, 35, W707-W712]. In this context, we describe two different samples (4-protmix and 8-protmix) suitable for relative protein quantitation using iTRAQ. Using the 4-protmix, relative protein changes of up to 24-fold were measured. The 8-protmix allowed the quantitation of the relative protein changes in a mixture of proteins within the range of two orders of magnitude in concentration and ten-fold differences in relative abundance. We propose that the two samples are suited to test the iTRAQ quantitative proteomic workflow. We analyzed the iTRAQ samples with a LTQ Orbitrap using "higher energy collision-induced dissociation" fragmentation [Olsen, J. V., et al., Nat. Methods 2007, 4, 709-712] and quantified with Proteome Discoverer v.1.1 (Thermo Fisher Scientific). We believe that the presented protein mixtures will be useful to assess the performance of the iTRAQ-based quantitation proteomic strategy in any laboratory.

Human colon cancer profiles show differential microRNA expression depending on mismatch repair status and are characteristic of undifferentiated proliferative states

BackgroundColon cancer arises from the accumulation of multiple genetic and epigenetic alterations to normal colonic tissue. microRNAs (miRNAs) are small, non-coding regulatory RNAs that post-transcriptionally regulate gene expression. Differential miRNA expression in cancer versus normal tissue is a common event and may be pivotal for tumor onset and progression.MethodsTo identify miRNAs that are differentially expressed in tumors and tumor subtypes, we carried out highly sensitive expression profiling of 735 miRNAs on samples obtained from a statistically powerful set of tumors (n = 80) and normal colon tissue (n = 28) and validated a subset of this data by qRT-PCR.ResultsTumor specimens showed highly significant and large fold change differential expression of the levels of 39 miRNAs including miR-135b, miR-96, miR-182, miR-183, miR-1, and miR-133a, relative to normal colon tissue. Significant differences were also seen in 6 miRNAs including miR-31 and miR-592, in the direct comparison of tumors that were deficient or proficient for mismatch repair. Examination of the genomic regions containing differentially expressed miRNAs revealed that they were also differentially methylated in colon cancer at a far greater rate than would be expected by chance. A network of interactions between these miRNAs and genes associated with colon cancer provided evidence for the role of these miRNAs as oncogenes by attenuation of tumor suppressor genes.ConclusionColon tumors show differential expression of miRNAs depending on mismatch repair status. miRNA expression in colon tumors has an epigenetic component and altered expression that may reflect a reversion to regulatory programs characteristic of undifferentiated proliferative developmental states.

Human cell toxicogenomic analysis of bromoacetic acid: A regulated drinking water disinfection by‐product

The disinfection of drinking water is a major achievement in protecting the public health. However, current disinfection methods also generate disinfection by-products (DBPs). Many DBPs are cytotoxic, genotoxic, teratogenic, and carcinogenic and represent an important class of environmentally hazardous chemicals that may carry long-term human health implications. The objective of this research was to integrate in vitro toxicology with focused toxicogenomic analysis of the regulated DBP, bromoacetic acid (BAA) and to evaluate modulation of gene expression involved in DNA damage/repair and toxic responses, with nontransformed human cells. We generated transcriptome profiles for 168 genes with 30 min and 4 hr exposure times that did not induce acute cytotoxicity. Using qRT-PCR gene arrays, the levels of 25 transcripts were modulated to a statistically significant degree in response to a 30 min treatment with BAA (16 transcripts upregulated and nine downregulated). The largest changes were observed for RAD9A and BRCA1. The majority of the altered transcript profiles are genes involved in DNA repair, especially the repair of double strand DNA breaks, and in cell cycle regulation. With 4 hr of treatment the expression of 28 genes was modulated (12 upregulated and 16 downregulated); the largest fold changes were in HMOX1 and FMO1. This work represents the first nontransformed human cell toxicogenomic study with a regulated drinking water disinfection by-product. These data implicate double strand DNA breaks as a feature of BAA exposure. Future toxicogenomic studies of DBPs will further strengthen our limited knowledge in this growing area of drinking water research.

Exploratory analysis describing ultrasonic (US) evaluation of spleen size during peripheral blood progenitor cell (PBPC) mobilization by filgrastim in normal donors

7102 Background: Filgrastim is used to mobilize CD34+ cells into the peripheral blood that are collected by apheresis for allogeneic transplantation. We prospectively evaluated spleen size during PBPC mobilization Methods: Donors ≥18 yrs eligible to be PBPC donors per institutional guidelines enrolled. Splenic assessments were done before, during, and after PBPC mobilization. Filgrastim dose and schedule and leukapheresis (LK) procedures were per local practice. Spleen size by US was measured in 3 dimensions: longitudinal (craniocaudal), transverse, and diagonal (perpendicular to transverse). Splenic volume was estimated by taking the cross-product of 3 dimensions and multiplying by 0.52, approximating an ellipse volume. Stiff (ASH 2007) reported the primary endpoint, fold change from baseline in splenic volume during mobilization. Exploratory analyses, including a linear regression evaluating the effect of age and baseline spleen size on fold-change, were performed. Results: 309 enrolled, median age 44yrs, 56% male. Median fold volume change from baseline to first LK was 1.47, resolving to near baseline 1 week after last LK. No significant clinical sequelae, including splenic rupture, were reported. Older donors appeared to have the smallest baseline spleen volume and the largest fold change (table). Linear regression analyses indicated age was a significant predictor for both baseline spleen volume (p=0.0031) and spleen volume fold change from baseline at first LK (p=0.0499). Conclusions: During mobilization, spleen volume transiently increased from baseline to day of 1st LK and returned to near baseline 1 week after last LK. Older donors tended to have smaller baseline splenic volume and greater fold changes in spleen size. Preclinical models suggest decreasing hematopoietic stem cell homing after mobilization with aging (Morrison 1996; Wagers 2002), which could result in splenic accumulation of progenitor and stem cells. [Table: see text] [Table: see text]

Use of global gene expression patterns in mechanistic studies of oestrogen action in MCF7 human breast cancer cells

Over the years, the MCF7 human breast cancer cell line has provided a model system for the study of cellular and molecular mechanisms in oestrogen regulation of cell proliferation and in progression to oestrogen and antioestrogen independent growth. Global gene expression profiling has shown that oestrogen action in MCF7 cells involves the coordinated regulation of hundreds of genes across a wide range of functional groupings and that more genes are downregulated than upregulated. Adaptation to long-term oestrogen deprivation, which results in loss of oestrogen-responsive growth, involves alterations to gene patterns not only at early time points (0–4 weeks) but continuing through to later times (20–55 weeks), and even involves alterations to patterns of oestrogen-regulated gene expression. Only 48% of the genes which were regulated ≥2-fold by oestradiol in oestrogen-responsive cells retained this responsiveness after long-term oestrogen deprivation but other genes developed de novo oestrogen regulation. Long-term exposure to fulvestrant, which resulted in loss of growth inhibition by the antioestrogen, resulted in some very large fold changes in gene expression up to 10,000-fold. Comparison of gene profiles produced by environmental chemicals with oestrogenic properties showed that each ligand gave its own unique expression profile which suggests that environmental oestrogens entering the human breast may give rise to a more complex web of interference in cell function than simply mimicking oestrogen action at inappropriate times.

Discovery of Novel Biomarkers in Oral Submucous Fibrosis by Microarray Analysis

Oral submucous fibrosis (OSF) is a high-risk precancerous condition of the oral cavity. Areca nut chewing is its key etiologic factor, but the full pathogenesis is still obscure. In this study, microarray analysis was used to characterize the mRNA changes of 14,500 genes in four OSF and four normal buccal mucosa samples to identify novel biomarkers of OSF. Five candidate genes with the most differential changes were chosen for validation. The correlation between clinicopathologic variables of 66 OSF patients and the expression of each gene was assessed by immunohistochemistry. The microarray analysis showed that 661 genes were up-regulated (fold value >2) and 129 genes were down-regulated (fold value <0.5) in OSF (q < 0.01). The top three up-regulated genes [Loricrin, Cartilage oligomeric matrix protein (COMP), Cys-X-Cys ligand 9 (CXCL9)] with the largest fold changes and the top two down-regulated genes [keratin 19 (KRT19), cytochrome P450 3A5 (CYP 3A5)] with the most significantly differential changes in OSF were chosen as candidate biomarkers. In immunohistochemical results, the expression of Loricrin and COMP showed statistically significant association with histologic grade of OSF (P = 0.03 and 0.006, respectively). COMP was found to be overexpressed frequently in patients with the habit of areca nut chewing for more than 4 years (P = 0.002). CYP 3A5 was revealed an inverse correlation with histologic grade (P = 0.04). This pilot study showed that five novel genes might play important roles in the pathogenesis of OSF and may be clinically useful for early detection of OSF.

Authorʼs reply

To Dr. Xie: First, thank you for your questions and suggestions. I wish my following clarifications would provide sufficient answers to your questions. In the first question, you asked why the false discovery correction was not used for screening differentially expressed genes between parental cell line and chemo-resistant sublines. The following are our explanations. Firstly, statistical significance is just one of the three criteria for filtering genes. The expression level of genes may be more important, and fold change was used in most of microarray analysis up-to-date. For published articles concerning microarray analysis, few have included statistical significance as a criterion. In order to make result more convincing, we tried to use ANOVA to help to find difference. Secondly, for adequate statistical analysis, large sample size is suggested. But for microarray analysis, it is not practical because of high expense for each microarray. If more replication can be acquired, the more standard statistical analysis will be available. So let's hypothesize that false discovery correction was used and set cutoff of P <0.05, it would exclude 2370 genes which had large fold change between parental and resistant cell lines, and only several hundred genes which were judged to be of statistical significance would be screened. When these genes were filtered by fold change, a few differential genes would be acquired. In this way we would lose much important information. The last, our research targets were constructed cell lines, duplications were almost the same with each other, so we could try to draw conclusion from the limited samples and replications according to the criteria listed in the article. For further analysis, the samples from tumor tissue may be used and acquire large sample size, in that case, the method and parameters of statistical analysis will be modified. As to the second question, there were reports about the usage of leave-one-out cross validation.1,2 In our research, the leave-one-out cross validation was a method to validate the microarray analysis, the real-time PCR and western blot. All these experiments helped to validate our microarray. Because of limited samples used, large independent samples for external validation were not practical until now. But in our research we also analyzed an independent pancreatic cancer cell line, Aspc-1. The result showed that the filtered gene may be related with MDR. For the third question. The genes for real-time PCR were selected according to the following criteria: (1) genes must be selected from filtered result; (2) the expression value of genes must be greater than 100 (see normalization information), in case it can not be detected by PCR analysis; (3) genes with both known and unknown ESTs should be considered for further analysis. The genes for western blot were selected according to the following criteria: (1) available monoclonal or multiclonal antibody for detecting protein expression; (2) by bioinformatic analysis, related information in the internet is checked and the genes which will be used for further analysis are selected. As to the last question, we are continuing our studies on constructing and finding more pancreatic cancer resistant cell lines and culturing new pancreatic cell lines from specimens. When sufficient material becomes available, more advanced research that may also include animal model will be carried out. Thanks a lot.

Specific and common changes in Nicotiana benthamiana gene expression in response to infection by enveloped viruses

Microarrays derived from Solanum tuberosum expressed sequence tags were used to test the hypothesis that genetically distinct enveloped viruses elicit unique changes in Nicotiana benthamiana gene expression. The results of our study, which included Sonchus yellow net virus (SYNV), a plant rhabdovirus that replicates in the nucleus of infected cells, and Impatiens necrotic spot virus (INSV), a plant bunyavirus that replicates in the cytoplasm, were consistent with this hypothesis. Statistically significant changes (P< or =0.01) in the expression of 275, 2646 and 4165 genes were detected in response to INSV at 2, 4 and 5 days post-inoculation (d.p.i.), respectively. In contrast, 35, 665 and 1458 genes were expressed differentially in response to SYNV at 5, 11 and 14 d.p.i., respectively. The microarray results were verified by Northern hybridization using a subset of these genes as probes. Notably, INSV, but not SYNV, induced expression of small heat-shock protein genes to high levels. In contrast to SYNV, infection by INSV resulted in downregulation of all histone genes, of which the downregulation of histone 2b expression to very low levels was confirmed by Northern hybridization. The expression of a putative WRKY transcription factor at 11 d.p.i., but not at 5 or 14 d.p.i., in SYNV-infected tissue suggested that the temporal response to virus infection was identified readily using our experimental design. Overall, infection by INSV resulted in larger fold changes in host gene expression relative to infection by SYNV. Taken together, the present data demonstrate differential responses of a common host to two genetically distinct viruses.

Assessment of temporal biochemical and gene transcription changes in rat liver cytochrome P450: utility of real-time quantitative RT-PCR.

A conventional approach to assess cytochrome P450 (CYP) induction in preclinical animal models involves daily dosing for a least a week followed by Western blot and/or enzyme activity analysis. To evaluate the potential benefit of a third more specific and sensitive assay, real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), with the objective of reducing the duration of the conventional 1-week study, we simultaneously assessed gene expression by qRT-PCR along with Western blots and enzyme activity assays as a time course in an in vivo model. Rats were dosed daily for 8 days with model inducers of CYP1A, CYP2B, CYP3A, or CYP4A. Liver P450 levels were measured after 0.5, 1, 2, 4, and 8 days of dosing by qRT-PCR, Western blot, and enzyme activity. CYP1A, CYP3A, and CYP4A genes were maximally induced very rapidly (0.5-1 day), whereas the CYP2B gene was maximally induced after a lag time of 4 days. In all cases, fold changes in induction detected by qRT-PCR were greater than fold changes in protein levels and enzyme activities. Maximal persistent and larger fold changes observed by qRT-PCR either preceded or occurred simultaneously with maximal sustained fold changes in protein levels as measured by Western blots and enzyme activity assays. Our data show that qRT-PCR provides increased sensitivity and specificity over conventional assays and may be key information for reliable assessment of drug-related changes in CYP induction during the transition from discovery to toxicology studies.