Differential gene expression
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens (human)
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PROVIDER: S-BSST748 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:Interventions: Group 1: Quantitative Expression Analysis of the proteom and gene Expression of Primary Tumor, normal tissue, and metastases
Primary outcome(s): Disease associated Proteins and Genes
Study Design: Allocation: ; Masking: ; Control: ; Assignment: ; Study design purpose: basic science
| 2431957 | ecrin-mdr-crc
Project description:BackgroundBoth differential expression (DE) and differential co-expression (DC) analyses are appreciated as useful tools in understanding gene regulation related to complex diseases. The performance of integrating DE and DC, however, remains unexplored.ResultsIn this study, we proposed a novel analytical approach called DECODE (Differential Co-expression and Differential Expression) to integrate DC and DE analyses of gene expression data. DECODE allows one to study the combined features of DC and DE of each transcript between two conditions. By incorporating information of the dependency between DC and DE variables, two optimal thresholds for defining substantial change in expression and co-expression are systematically defined for each gene based on chi-square maximization. By using these thresholds, genes can be categorized into four groups with either high or low DC and DE characteristics. In this study, DECODE was applied to a large breast cancer microarray data set consisted of two thousand tumor samples. By identifying genes with high DE and high DC, we demonstrated that DECODE could improve the detection of some functional gene sets such as those related to immune system, metastasis, lipid and glucose metabolism. Further investigation on the identified genes and the associated functional pathways would provide an additional level of understanding of complex disease mechanism.ConclusionsBy complementing the recent DC and the traditional DE analyses, DECODE is a valuable methodology for investigating biological functions of genes exhibiting disease-associated DE and DC combined characteristics, which may not be easily revealed through DC or DE approach alone. DECODE is available at the Comprehensive R Archive Network (CRAN): http://cran.r-project.org/web/packages/decode/index.html .
| S-EPMC4449974 | biostudies-literature
Project description:Differential gene expression analysis using RNA sequencing (RNA-seq) data is a standard approach for making biological discoveries. Ongoing large-scale efforts to process and normalize publicly available gene expression data enable rapid and systematic reanalysis. While several powerful tools systematically process RNA-seq data, enabling their reanalysis, few resources systematically recompute differentially expressed genes (DEGs) generated from individual studies. We developed a robust differential expression analysis pipeline to recompute 3162 human DEG lists from The Cancer Genome Atlas, Genotype-Tissue Expression Consortium, and 142 studies within the Sequence Read Archive. After measuring the accuracy of the recomputed DEG lists, we built the Differential Expression Enrichment Tool (DEET), which enables users to interact with the recomputed DEG lists. DEET, available through CRAN and RShiny, systematically queries which of the recomputed DEG lists share similar genes, pathways, and TF targets to their own gene lists. DEET identifies relevant studies based on shared results with the user's gene lists, aiding in hypothesis generation and data-driven literature review.
| S-EPMC9869326 | biostudies-literature
Project description:Differential expression (DE) is commonly used to explore molecular mechanisms of biological conditions. While many studies report significant results between their groups of interest, the degree to which results are specific to the question at hand is not generally assessed, potentially leading to inaccurate interpretation. This could be particularly problematic for metaanalysis where replicability across datasets is taken as strong evidence for the existence of a specific, biologically relevant signal, but which instead may arise from recurrence of generic processes. To address this, we developed an approach to predict DE based on an analysis of over 600 studies. A predictor based on empirical prior probability of DE performs very well at this task (mean area under the receiver operating characteristic curve, ∼0.8), indicating that a large fraction of DE hit lists are nonspecific. In contrast, predictors based on attributes such as gene function, mutation rates, or network features perform poorly. Genes associated with sex, the extracellular matrix, the immune system, and stress responses are prominent within the "DE prior." In a series of control studies, we show that these patterns reflect shared biology rather than technical artifacts or ascertainment biases. Finally, we demonstrate the application of the DE prior to data interpretation in three use cases: (i) breast cancer subtyping, (ii) single-cell genomics of pancreatic islet cells, and (iii) metaanalysis of lung adenocarcinoma and renal transplant rejection transcriptomics. In all cases, we find hallmarks of generic DE, highlighting the need for nuanced interpretation of gene phenotypic associations.
| S-EPMC6442595 | biostudies-literature
Project description:ObjectiveCandidate genes that are associated with preeclampsia have not been described fully. We conducted microarray and confirmatory quantitative real time polymerase chain reaction studies to investigate global placental gene expression in preeclampsia.Study designRNA was extracted from placental samples that were collected from 18 preeclampsia cases and 18 normotensive control subjects. Oligonucleotide probes that represented 22,000 genes were used to measure gene expression in each sample. Differential gene expression was evaluated with the Student t test, fold change assessment, and significance analysis of microarrays. Functions and functional relationships of differentially expressed genes were evaluated.ResultsGenes (n = 58) that participated in immune system, inflammation, oxidative stress, signaling, growth, and development pathways were expressed differentially in preeclampsia. These genes included previously described candidate genes (such as leptin), potential candidate genes with related functions (such as CYP11A) and novel genes (such as CDKN1C).ConclusionExpression of genes (both candidate and novel) with diverse functions is associated with preeclampsia risk, which reflects the complex pathogenesis.
| S-EPMC2702488 | biostudies-literature
Project description:Amplified differential gene expression (ADGE) is a novel technique, designed to profile gene expression of the whole transcriptome or to compare expression of a set of genes between two samples. ADGE employs hybridization to quadratically amplify the ratio of an expressed gene between control and tester samples before displaying. The subtle structures of adapters and primers are designed for displaying the amplified ratio of an expressed gene between two samples. Four selective nucleotides at the 3' end of primers are used to increase PCR efficiency for targeted molecules and to improve detection of PCR products. Double PCR with the same pair of primers expands the detection range, especially for genes of low abundance. Integration of these steps makes ADGE sensitive and accurate. Application to drug resistant human tumor cell lines showed that ADGE accurately profiled expression levels for induced, repressed or unchanged genes. The qualitative expression patterns for ADGE were verified with RT-PCR.
| S-EPMC55467 | biostudies-literature
Project description:IntroductionThe goiter, a neglected heterogeneous molecular disease, remains a major indication for thyroidectomies in its endemic regions.ObjectivesThis study analyzed differential gene expression in surgical specimens diagnosed with multi nodular and compared the data to that of thyroid tissue without multinodular goiter from patients undergoing thyroidectomy in Manaus-AM, Brazil using RNA-seq technology.MethodologyThe transcriptome information of the surgical specimen fragments with and without multinodular goiter was accessed by Illumina HiSeq 2000 New Generation Sequencing (NGS) using the RNA-seq NEBNext® Ultra™ RNA Library Prep Kit for Illumina®-#E7530L protocol and differential gene expression analysis.ResultsDifferences were found between the gene expression profiles of the diseased tissues and those of the healthy control tissues; at least 70 genes were differentially expressed. The HOTS gene was expressed only in multinodular goiter tissues (p < 0.05).ConclusionThese results demonstrate that the gene expression profile of multinodular goiter is pro-tumoral and that HOTS can play a central role in multinodular goiter development.
| S-EPMC9122239 | biostudies-literature
Project description:BackgroundTherapies targeting the epidermal growth factor receptor (EGFR) result in a painful rash, the most common and debilitating toxicity among patients with non-small cell lung cancer (NSCLC) who take EGFR tyrosine kinase inhibitor (TKI) therapy; however, predicting the development and the severity of the rash is difficult.ObjectiveThe aim of this study was to examine how erlotinib-an EGFR TKI that NSCLC patients take to stop or slow tumor growth-altered the transcriptome of dermal fibroblasts.MethodsDermal fibroblasts (ATCC PCS-201-012) were seeded in cell culture flasks, grown under standard conditions, and transferred to cell culture dishes. Cells were treated once daily for 3 days with erlotinib 100 nM (n = 5), erlotinib 1 μM (n = 5), vehicle 1 μM (dimethyl sulfoxide) (n = 5), or no treatment (n = 5). Total RNA was extracted using a standard TRIzol method and hybridized using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Raw intensities generated from the arrays were normalized using a Robust Multiarray Average method and analyzed using analysis of variance in Limma R software. Differentially expressed genes were analyzed using Ingenuity Pathway Analysis to identify canonical or noncanonical signaling pathways enriched in this dataset.ResultsWe selected genes for investigation based on their potential role in wound healing (AQP3), rash development (CCL2), fibroblast activation (PALLD), cancer and cancer progression (GDF-15, SLC7A11, MMP12, and DIRAS3), and cell cycle control (CDC6). We were able to validate four of these genes by both Western blot analysis and quantitative polymerase chain reaction (MMP12, CCL2, CDC6, and SLC7A11).DiscussionIf found predictive of rash in future studies using patient samples, our findings may help to identify those at risk for severe rash so that (a) the dose of EGFR TKI therapy may be adjusted; (b) additional treatments for the rash can be developed; and/or (c) precise, patient-centered interventions can be developed so that patients with cancer can better self-manage their rash and adhere to EGFR TKI treatment.
| S-EPMC7580303 | biostudies-literature
Project description:Terminal erythroid differentiation in mammals is the process whereby nucleated precursor cells accumulate erythroid-specific proteins such as hemoglobin, undergo extensive cellular and nuclear remodeling, and ultimately shed their nuclei to form reticulocytes, which then become mature erythrocytes in the circulation. Little is known about the mechanisms that enable erythroblasts to undergo such a transformation. We hypothesized that genes involved in these mechanisms were likely expressed at restricted times during the differentiation process and used differential display reverse transcriptase polymerase chain reaction as a first step in identifying such genes. We identified three differentially expressed cDNAs that we termed late erythroblast (LEB) 1-3. None of these cDNAs were previously identified as being expressed in erythroblasts and their patterns of expression indicated they are likely to be involved in the differentiation process. LEB-1 cDNA was derived from the gene A330102K04Rik (approved gene symbol Apoll1), and shares homology with members of the apolipoprotein L family in humans. LEB-3 cDNA was derived from the novel gene D930015E06Rik, that has no known function. LEB-2 cDNA was derived from the gene ranBP16 (approved gene symbol Xpo7), a nuclear exportin. D930015E06Rik mRNA is also strongly expressed in the testis and was localized to a region of the seminiferous tubule where secondary spermatocytes and early spermatids are found, suggesting a role for D930015E06Rik in spermatogenesis as well as terminal erythroid differentiation. We have thus identified three genes not previously described as being expressed in erythroblasts that could be relevant in elucidating mechanisms involved in terminal erythroid differentiation.
| S-EPMC2205530 | biostudies-literature
Project description:Spermatogenesis is an essential precursor for successful sexual reproduction. Recently, there has been an expansion in the knowledge of the genes associated with particular stages of normal, physiological testicular development and pubertal activation. What has been lacking, however, is an understanding of those genes that are involved in specifically regulating sperm production, rather than in maturation and elaboration of the testis as an organ. By using the reversible (seasonal) fertility of the Syrian hamster as a model system, the authors sought to discover genes that are specifically involved in turning off sperm production and not involved in tissue specification and/or maturation. Using gene expression microarrays and in situ hybridization in hamsters and genetically infertile mice, the authors have identified a variety of known and novel factors involved in reversible, transcriptional, translational, and posttranslational control of testicular function, as well those involved in cell division and macromolecular metabolism. The novel genes uncovered could be potential targets for therapies against fertility disorders.
| S-EPMC3398136 | biostudies-literature