Proteomic
Ontology highlight
ABSTRACT:
TISSUE(S): ['liver']
SUBMITTER: Jing Zhong
PROVIDER: OEX00021153 | NODE | 2023-01-03
REPOSITORIES: NODE
Similar Datasets
Project description:Purpose: There is a need for point-of-care diagnostics for future mass casualty events involving radiation exposure. The development of radiation exposure and dose prediction algorithms for biodosimetry is needed for screening of large populations during these scenarios, and exploration of the potential effects which sex, age, genetic heterogeneity, and physiological comorbidities may have on the utility of biodosimetry diagnostics is needed. In the current study, proteomic profiling was used to examine sex specific differences in age matched C57BL6 mice on the blood proteome following radiation exposure and the usefulness of development and application of biodosimetry algorithms using both male and female samples. Methods: C57BL6 male and female mice between 9-11 weeks of age received a single total body radiation exposure of either 2, 4 or 8 Gy with plasma collection at days 1, 3 and 7 post-irradiation. Plasma was then screened using the SomaScan v4.1 assay for ~7000 protein analytes. A subset panel of protein biomarkers demonstrated significant (FDR<0.05 and |logFC|>0.2) changes in expression following radiation exposure. All proteins were used for feature selection to build predictive models of radiation exposure using different sample and sex specific cohorts. Both binary (prediction of any radiation exposure) and multidose (prediction of specific radiation dose) model series were developed using either female and male samples combined or only female or only male samples. The binary series (Models 1, 2 and 3) and multidose series (Models 4, 5 and 6) series included female/male combined, female only and male only respectively. Results: Detectable values were obtained for all ~7000 proteins included in the SomaScan assay for all samples. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. Overall predictive accuracies in the binary model series was ~100% at the model training level and when tested with fresh samples 97.9% for Model 1(Female and Male) and 100% for Model 2 (Female only) and Model 3 (Male only). When sex specific Models’ 2 and 3 were tested with the opposite sex, the overall predictive accuracy rate dropped to 62.5% for Model 2 and remained 100% for Model 3. The overall predictive accuracy rate in the multidose model series was 100% for all models at the model training level and when tested with fresh samples 83.3%, 75% and 83.3% for Multidose Models 4-6 respectively. When sex specific Models’ 5 (Female only) and Model 6 (Male only) were tested with the opposite sex the overall predictive accuracy rate dropped to 52.1% and 68.8% respectively. Conclusion: These models represent novel predictive panels of radiation responsive proteomic biomarkers and illustrate the utility and necessity of considering sex specific differences in development of radiation biodosimetry prediction algorithms. As sex specific differences were observed in this study, and as use of point-of-care radiation diagnostics in future mass casualty settings will necessarily include persons of both sexes, consideration of sex specific variation is essential to ensure these diagnostic tools have practical utility in the field.
2024-05-11 | GSE267131 | GEO
Project description:We have correlated transciptomics, proteomics and toponomics analyses of hippocampus tissue of inbred C57/BL6 mice to analyse the interrelationship of expressed genes and proteins at different levels of organization. We find that transcriptome and proteome levels of function are highly conserved between different mice, while the topological organization (the toponome) of protein clusters in synapses of the hippocampus is highly individual, with only few interindividual overlaps (0.15 %). In striking contrast, the overall spatial patterns of individual synaptic states, defined by protein clusters, have boundaries within a strict and non-individual spatial frame of the total synaptic network. The findings are the first to provide insight in the systems biology of gene expression on transcriptome, proteome and toponome levels of function in the same brain subregion. The approach may lay the ground for designing studies of neurodegeneration in mouse models and human brains. Experiment Overall Design: 4 biological replicates, all wild type
2008-06-19 | E-GEOD-8239 | biostudies-arrayexpress
Project description:Quercetin has been shown to act as an anti-carcinogen in experimental colorectal cancer (CRC). The aim of the present study was to characterise transcriptome and proteome changes occurring in the distal colon mucosa of rats supplemented with 10 g quercetin/kg diet for 11 weeks. Transcriptome data analysed with Gene Set Enrichment Analysis showed that quercetin significantly downregulated the potentially oncogenic mitogen-activated protein kinase (Mapk) pathway. In addition, quercetin enhanced expression of tumor suppressor genes, including Pten, Tp53 and Msh2, and of cell cycle inhibitors, including Mutyh. Furthermore, dietary quercetin enhanced genes involved in phase I and II metabolism, including Fmo5, Ephx1, Ephx2 and Gpx2. Quercetin increased PPARα target genes, and concomitantly enhanced expression genes in volved in of mitochondrial fatty acid degradation. Proteomics performed in the same samples revealed 33 affected proteins, of which 4 glycolysis enzymes and 3 heatshock proteins were decreased. A proteome-transcriptome comparison showed a low correlation, but both pointed out towards altered energy metabolism. In conclusion, transcriptomics combined with proteomics showed that dietary quercetin evoked changes contrary to those found in colorectal carcinogenesis. These tumor-protective mechanisms were associated with a shift in energy production pathways, pointing at decreased glycolysis in the cytoplasm towards increased fatty acid degradation in the mitochondria. Experiment Overall Design: After an 11-week diet, rats fed quercetin or the control diet were sacrificed and fold changes in gene expression were detemined as quercetin (n=4) vs. control (n=4)
2008-06-15 | E-GEOD-7479 | biostudies-arrayexpress
Project description:The effect of rasagiline or MPTP on midbrain protein expression profile Keywords: repeat sample
2004-12-01 | GSE1857 | GEO
Project description:Eccrine sweat gland is an exocrine gland that is involved in the secretion of sweat for control of temperature. Malfunction of the sweat glands can result in disorders such as miliaria, hyperhidrosis and bromhidrosis. In addition, lack of reabsorption of Cl- ions from reabsorptive duct of eccrine sweat gland is a major feature of cystic fibrosis. Understanding the proteome of eccrine sweat glands is important for understanding the physiology of sweat formation. In spite of this, no systematic transcriptome or proteome analysis of eccrine sweat glands has yet been reported. To this end, we isolated eccrine sweat glands by microdissecting them from human skin and performed both RNA-seq and proteome analysis. In total, ~138,000 transcripts and ~6,100 proteins were identified. The proteome data showed the enrichment in protein digestion/absorption and salivary secretion, while the transcriptome data did not show any enrichment for a specific pathway. This study also enabled us to confirm 2 missing proteins. Integrating RNA-seq and proteomic data allowed us to identify 7 peptides from 5 novel genes. Most of the novel proteins were from short open reading frames (sORFs) suggesting that many sORFs still remain to be annotated in the human genome. The peptides mapping to the missing or novel proteins were validated by analyzing synthetic peptides. This study provides the first integrated analysis of the transcriptome and proteome of the human eccrine sweat gland and should become an invaluable resource to biomedical research community for studying sweat glands in physiology and disease.
2018-07-31 | GSE117885 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE30721: Profiling proteome-scale antibody responses to M. tuberculosis proteins in sera of macaques infected with M. tuberculosis GSE30722: Profiling proteome-scale antibody responses to M. tuberculosis proteins in TB suspect's sera Refer to individual Series
2012-07-05 | E-GEOD-31368 | biostudies-arrayexpress
Project description:For proteome 48 fractions in each TMT set.
2019-12-17 | OEX00001703 | NODE
Project description:The long-standing view of 'immortal germ line versus mortal soma' poses a fundamental question in biology concerning how oocytes age in molecular terms. A mainstream hypothesis is that maternal aging of oocytes has its roots in gene transcription. Investigating the proteins resulting from mRNA translation would reveal how far the levels of functionally available proteins correlate with mRNAs, and would offer novel insight into the changes oocytes undergo during maternal aging. Gene ontology semantic analysis reveals the high similarity of the detected proteome (2,324 proteins) to the transcriptome (22,334 mRNAs), though not all proteins have a cognate mRNA. Concerning their dynamics, 4-fold changes of abundance are more frequent in the proteome (3%) than the transcriptome (0.05%), with correlation. Whereas proteins associated with the nucleus (e.g. structural maintenance of chromosomes, spindle-assembly checkpoints) are largely represented among those that change in oocytes during maternal aging; proteins associated with oxidative stress/damage (e.g. superoxide dismutase) are infrequent. These quantitative alterations are either impoverishing or enriching. Using gene ontology analysis, these alterations do not relate in any simple way to the classic signature of aging known from somatic tissues. We conclude that proteome analysis of mouse oocytes may not be surrogated with transcriptome analysis, given the lack of correlation. Furthermore, we conclude that the classic features of aging may not be transposed from somatic tissues to oocytes in a one-to-one fashion. Overall, there is more to the maternal aging of oocytes than mere cellular deterioration exemplified by the notorious increase of meiotic aneuploidy. Three pools of 20 zona-enclosed B6C3F1 oocytes from each age group were subjected for experiment.
2014-04-15 | E-GEOD-42959 | biostudies-arrayexpress
Project description:A sensitive assay to identify biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. In this study, we have conducted a prospective sample collection and retrospective blinded validation (PRoBE design) to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer. The Affymetrix HG U133 Plus 2.0 Array and 2D-DIGE were used to profile transcriptomes and proteomes in saliva supernatants respectively. Significant variations of salivary transcriptomic and proteomic profiles were observed between breast cancer patients and healthy controls. Eleven transcriptomic biomarker candidates and two proteomic biomarker candidates were selected for a preclinical validation using an independent sample set. Transcriptomic biomarkers were validated by RT-qPCR and proteomic biomarkers were validated by quantitative protein immunoblot. Eight mRNA biomarkers and one protein biomarker have been validated for breast cancer detection, yielding ROC-plot AUC values between 0.665 and 0.959. This report provides proof of concept of salivary biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers’ discriminatory power paves the way for a PRoBE-design definitive validation study. Keywords: Salivary biomarker, Breast cancer, Early detection, Salivary transcriptome, Salivary proteome
2010-02-11 | GSE20266 | GEO
Project description:Clinical heterogeneity of hepatocellular carcinoma (HCC) reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of HCC. Using reverse phase protein arrays (RPPA) technologies, we analyzed protein expression profiling data from HCC patients, uncovered mesenchymal subtype, and identified gene expression signature associated with mesenchymal phenotype of HCC.
2024-01-01 | GSE199141 | GEO