Gene expression signatures but not cell cycle checkpoint functions distinguish AT carriers from normal individuals and AT patients
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE45850 | GEO | 2013/04/09
SECONDARY ACCESSION(S): PRJNA196502
REPOSITORIES: GEO
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Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2013-04-09 | E-GEOD-45850 | biostudies-arrayexpress
Project description:Ataxia telangiectasia (AT) is a rare autosomal recessive disease caused by mutations in the ataxia telangiectasia-mutated gene (ATM). AT carriers with one mutant ATM allele are usually not severely affected although they carry an increased risk of developing cancer. There has not been an easy and reliable diagnostic method to identify AT carriers. Cell cycle checkpoint functions upon ionizing radiation (IR)-induced DNA damage and gene expression signatures were analyzed in the current study to test for differential responses in human lymphoblastoid cell lines with different ATM genotypes. While both dose- and time-dependent G1 and G2 checkpoint functions were highly attenuated in ATM-/- cell lines, these functions were preserved in ATM+/- cell lines equivalent to ATM+/+ cell lines. However, gene expression signatures at both baseline (consisting of 203 probes) and post-IR treatment (consisting of 126 probes) were able to distinguish ATM+/- cell lines from ATM+/+ and ATM-/- cell lines. Gene ontology (GO) and pathway analysis of the genes in the baseline signature indicate that ATM function-related categories, DNA metabolism, cell cycle, cell death control, and the p53 signaling pathway, were overrepresented. The same analyses of the genes in the IR-responsive signature revealed that biological categories including response to DNA damage stimulus, p53 signaling, and cell cycle pathways were overrepresented, which again confirmed involvement of ATM functions. The results indicate that AT carriers who have unaffected G1 and G2 checkpoint functions can be distinguished from normal individuals and AT patients by expression signatures of genes related to ATM functions.
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Project description:Epigenetic regulation of gene enhancer elements is important for establishing and maintaining the identity of cells. Gene enhancer elements are thought to exist in either active or poised states distinguishable by chromatin features, but a complete understanding of the regulation of enhancers is lacking. Here, by using mouse embryonic stem cells and their differentiated derivatives, as well as terminally differentiated cells, we report the coexistence of multiple, defined classes of enhancers that serve distinct cellular functions. Specifically, we found that active enhancers can be subclassified based on varying levels of H3K4me1, H3K27ac, and H3K36me3 and the pSer2/5 forms of RNA polymerase II. The abundance of these histone modifications positively correlates with the expression of associated genes and cellular functions consistent with the identity of the cell type. Poised enhancers can also be subclassified based on presence or absence of H3K27me3 and H3K9me3, conservation, genomic location, expression levels of associated genes, and predicted function of associated genes. These findings not only refine the repertoire of histone modifications at both active and poised gene enhancer elements but also raise the possibility that enhancers associated with distinct cellular functions are partitioned based on specific combinations of histone modifications.
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Project description:Aberrant gene expression analysis between peripheral blood mononuclear cell (PBMC) samples from healthy individuals and patients with chronic hepatitis B carriers and HCC were identified using Affymetrix gene arrays.
2014-06-04 | GSE58208 | GEO
Project description:Aberrant gene expression analysis between peripheral blood mononuclear cell (PBMC) samples from healthy individuals and patients with chronic hepatitis B carriers and HCC were identified using Affymetrix gene arrays.M-BM- Peripheral blood mononuclear cell (PBMC) from healthy individuals, patients with patients with chronic hepatitis B carriers and HCC were isolated and total RNA was extracted for Affymetrix gene microarray analysis.
2014-06-04 | E-GEOD-58208 | biostudies-arrayexpress
Project description:ContextAlzheimer's disease (AD) is usually only diagnosed many years after pathology begins. Earlier detection would allow emerging interventions to have a greater chance to preserve healthy brain function. A rare form of Alzheimer's disease, caused by autosomal-dominant mutations, affects carriers with 100% certainty and at a younger age specific to their mutation. Studying families with these mutations allows a unique investigation of the temporal sequence of biomarker changes in Alzheimer's disease.ObjectiveTo determine whether the pupil flash response (PFR), previously reported to be altered in sporadic Alzheimer's disease, is different in pre-symptomatic mutation carriers.DesignResearchers blinded to participant mutation status collected pupil response data from cognitively normal participants in the Dominantly Inherited Alzheimer's Network (DIAN) Study during 2010-2011.SettingThe pupil response was examined at the McCusker Alzheimer's Research Foundation in Perth, Western Australia.ParticipantsParticipants were from a single family harboring an Amyloid-Beta Precursor Protein genetic mutation (APPGlu693Gln). Six carriers and six non-carriers were available for pupil testing (age 43.0±8.3 years old, 2 males and 10 females, 4 with hypertension).Main outcome measurePupil response parameter comparison between mutation carriers and non-carriers.Results75% recovery time was longer in mutation carriers (p<0.0003, ROC AUC 1.000, Sensitivity 100%, Specificity 100%) and percentage recovery 3.5 seconds after stimulus was less in mutation carriers (p<0.006, ROC AUC 1.000, Sensitivity 100%, Specificity 100%).ConclusionsPFR changes occur pre-symptomatically in autosomal dominant AD mutation carriers, supporting further investigation of PFR for early detection of AD.
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Project description:Objective: The intestinal microbiome is associated with various autoimmune diseases. Regional difference is the main influencing factor of intestinal microbial difference. This study aimed to identify the differences in fecal microbiome between autoimmune hepatitis (AIH) patients and healthy controls (HCs) in Central China, and to validate the efficacy of fecal microbiome as a diagnostic tool for AIH. Design: We collected 115 fecal samples from AIH patients (N = 37) and HCs (N = 78) in Central China and performed gene sequencing. Fecal microbiomes were characterized and microbial markers for AIH were identified. Results: Fecal microbial diversity showed a downward trend in AIH compared with HCs. Fecal microbial communities significantly differed between both groups. At the phylum level, Verrucomicrobia abundance was significantly increased, while Lentisphaerae and Synergistetes were significantly decreased in the AIH patients vs. the HCs. Compared to the HCs, 15 genera, including Veillonella, Faecalibacterium, and Akkermansia, were enriched, while 19 genera, such as Pseudobutyrivibrio, Lachnospira, and Ruminococcaceae, were decreased in the AIH patients. Ten genera, including Veillonella, Faecalibacterium, and Akkermansia, predominated in the AIH patients. Five microbial biomarkers were deemed optimal diagnostic tools for AIH. The probability of disease was significantly increased in AIH group vs. HCs, achieving 83.25% value of area under the curve. Conclusion: We present the characteristics of AIH patients in Central China for the first time. Five microbial biomarkers, including Lachnospiraceae, Veillonella, Bacteroides, Roseburia, and Ruminococcaceae, achieved a high potential distinguishing AIH patients from HCs.
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Project description:PurposeCancer cells often have deficiencies in cell-cycle control mechanisms and could be dependent on specific cell-cycle checkpoints to maintain viability. Because of the documented role of KRAS in driving replication stress, we targeted the checkpoint governing DNA replication using CHK1 kinase inhibitors in pancreatic ductal adenocarcinoma (PDAC) models and examined mechanisms of resistance.Experimental designSingle-agent efficacy of CHK1 inhibition was investigated in established and primary PDAC lines. Drug screening was performed to identify cooperative agents. In vitro and in vivo studies were employed to interrogate combination treatment efficacy and mechanisms of resistance.ResultsMany PDAC models evade single-agent inhibition through mechanisms that allow S-phase progression with CHK1 inhibited. Gene expression analysis revealed FOXM1 as a potential marker of CHK1 sensitivity and defined a form of pancreatic cancer with poor prognosis. Drug screen analysis identified WEE1 as a cooperative agent with CHK1 and was effective in cell culture. In vivo experiments validated the combination efficacy; however, resistance could evolve. Resistance was due to selection of a stable subclone from the original PDX tumor, which harbored high baseline replication stress. In vitro analysis revealed that gemcitabine could eliminate viability in the resistant models. The triplet regimen of gemcitabine, CHK1, and WEE1 inhibition provided strong disease control in all xenograft models interrogated.ConclusionsThese results demonstrate the therapeutic resiliency of pancreatic cancer and indicate that coordinately targeting cell-cycle checkpoints in concert with chemotherapy could be particularly efficacious.
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Project description:We have validated differences in DNA methylation levels of candidate genes previously reported to discriminate between normal colon mucosa of patients with colon cancer and normal colon mucosa of individuals without cancer. Here, we report that CpG sites in 16 of the 30 candidate genes selected show significant differences in mean methylation level in normal colon mucosa of 24 patients with cancer and 24 controls. A support vector machine trained on these data and data for an additional 66 CpGs yielded an 18-gene signature, composed of ten of the validated candidate genes plus eight additional candidates. This model exhibited 96% sensitivity and 100% specificity in a 40-sample training set and classified all eight samples in the test set correctly. Moreover, we found a moderate-strong correlation (Pearson coefficients r = 0.253-0.722) between methylation levels in colon mucosa and methylation levels in peripheral blood for seven of the 18 genes in the support vector model. These seven genes, alone, classified 44 of the 48 patients in the validation set correctly and five CpGs selected from only two of the seven genes classified 41 of the 48 patients in the discovery set correctly. These results suggest that methylation biomarkers may be developed that will, at minimum, serve as useful objective and quantitative diagnostic complements to colonoscopy as a cancer-screening tool. These data also suggest that it may be possible to monitor biomarker methylation levels in tissues collected much less invasively than by colonoscopy.
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Project description:Defects in DNA damage responses may underlie genetic instability and malignant progression in melanoma. Cultures of normal human melanocytes (NHMs) and melanoma lines were analyzed to determine whether global patterns of gene expression could predict the efficacy of DNA damage cell cycle checkpoints that arrest growth and suppress genetic instability. NHMs displayed effective G1 and G2 checkpoint responses to ionizing radiation-induced DNA damage. A majority of melanoma cell lines (11/16) displayed significant quantitative defects in one or both checkpoints. Melanomas with B-RAF mutations as a class displayed a significant defect in DNA damage G2 checkpoint function. In contrast the epithelial-like subtype of melanomas with wild-type N-RAS and B-RAF alleles displayed an effective G2 checkpoint but a significant defect in G1 checkpoint function. RNA expression profiling revealed that melanoma lines with defects in the DNA damage G1 checkpoint displayed reduced expression of p53 transcriptional targets, such as CDKN1A and DDB2, and enhanced expression of proliferation-associated genes, such as CDC7 and GEMININ. A Bayesian analysis tool was more accurate than significance analysis of microarrays for predicting checkpoint function using a leave-one-out method. The results suggest that defects in DNA damage checkpoints may be recognized in melanomas through analysis of gene expression.
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