Renal fibrosis mRNA classifier: validation in experimental lithium-induced interstitial fibrosis in the rat kidney
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ABSTRACT:
ORGANISM(S): Rattus norvegicus
PROVIDER: GSE83610 | GEO | 2017/02/08
SECONDARY ACCESSION(S): PRJNA326499
REPOSITORIES: GEO
Similar Datasets
Project description:Purpose: The goal of this study is to understand the role of co-administred amiloride. This was derived through RNAseq of kidney cortex and determining differential genes in response to lithium, lithium+amiloride and control at 14 days, 28 days and 6 months. Methods: RNAseq of kidney cortex treated with either lithium alone, lithium+amiloride or control. Deseq2 was performed using contrast argument with Wald test to identify significant differentially expression genes at each time point individually. Result & Conclusion: Co-administration with amiloride at all time points contributed in the reduction of inflammation and fibrosis caused by lithium.
2022-08-31 | GSE178950 | GEO
Project description:Accurate diagnosis of fibrosis is of paramount clinical importance. A human fibrosis classifier based on metzincins and related genes (MARGS) was described previously. In this investigation, expression changes of MARGS genes were explored and evaluated to examine whether the MARGS-based algorithm has any diagnostic value in a rat model of lithium nephropathy. Male Wistar rats (n = 12) were divided into 2 groups (n = 6). One group was given a diet containing lithium (40 mmol/kg food for 7 days, followed by 60mmol/kg food for the rest of the experimental period), while a control group (n = 6) was fed a normal diet. After six months, animals were sacrificed and the renal cortex and medulla of both kidneys removed for analysis. Gene expression changes were analysed using 24 GeneChip® Affymetrix Rat Exon 1.0 ST arrays. Statistically relevant genes (p-value<0.05, fold change>1.5, t-test) were further examined. Matrix metalloproteinase-2 (MMP2), CD44, and nephroblastoma overexpressed gene (NOV) were overexpressed in the medulla and cortex of lithium-fed rats compared to the control group. TGF?2 was overrepresented in the cortex of lithium-fed animals 1.5-fold, and 1.3-fold in the medulla of the same animals. In Gene Set Enrichment Analysis (GSEA), both the medulla and cortex of lithium-fed animals showed an enrichment of the MARGS, TGF? network, and extracellular matrix (ECM) gene sets, while the cortex expression signature was enriched in additional fibrosis-related-genes and the medulla was also enriched in immune response pathways. Importantly, the MARGS-based fibrosis classifier was able to classify all samples correctly. Immunohistochemistry and qPCR confirmed the up-regulation of NOV, CD44, and TGF?2. The MARGS classifier represents a cross-organ and cross-species classifier of fibrotic conditions and may help to design a test to diagnose and to monitor fibrosis. The results also provide evidence for a common pathway in the pathogenesis of fibrosis.
| S-EPMC5176284 | biostudies-literature
Project description:Effects of amiloride in lithium induced kidney interstitial fibrosis
| PRJNA741543 | ENA
Project description:Investigation of lithium effects in rat neural stem cells exposed to irradiation to mimic cranial radiotherapy in children. We investigated whether lithium is involved in halting or even preventing gene expression regulation in the model system.
2019-10-01 | E-MTAB-7238 | biostudies-arrayexpress
Project description:Renal fibrosis mRNA classifier: validation in experimental lithium-induced interstitial fibrosis in the rat kidney
| PRJNA326499 | ENA
Project description:Purpose: Lithium salts, used for treatment of bipolar disorder, frequently induce nephrogenic diabetes insipidus (NDI), limiting therapeutic success. NDI is associated with loss of expression of the molecular water channel, aquaporin-2, in the renal collecting duct (CD). Here, we use the methods of systems biology in a well-established rat model of lithium-induced NDI to identify signaling pathways activated at the onset of polyuria. Methods: We carried out RNA-sequencing in cortical CDs microdissected from rats treated with lithium for 12-72 hours (vs. time controls). Administration of anti-inflammatory doses of dexamethasone to lithium-treated rats countered the loss of aquaporin-2 protein. Protein mass spectrometry in microdissected cortical CDs provided corroborative evidence, but also identified decreased abundance of several anti-oxidant proteins. Cortical thick ascending limbs of Henle were also microdissected for RNA-Seq at 72 hrs. We carried out RNA-Seq for 2-3 CCD sample per rat (1 lithium-treated rat versus 1 control at 12, 24, 36 hrs). Results and conclusion: Integration of new data with prior data about lithium effects at a molecular level leads to a signaling model in which lithium increases ERK activation leading to induction of NF-κB signaling and an inflammatory-like response that represses Aqp2 gene transcription.
2019-04-04 | GSE116760 | GEO
Project description:Background: With the incidence of papillary thyroid carcinoma rising worldwide, the decision about lobectomy versus total thyroidectomy will become relevant for an increasing number of patients. There exists no reliable biomarker for metastatic potential or tendency of recurrence that could assist in the risk stratification of patients. Objective: To develop a gene expression classifier for metastatic potential by measuring RNA expression in the primary tumor at the time of cancer surgery. Further, to investigate the ability of the gene expression classifier to identify metastatic and recurrent cases. Method: Genome-wide expression analyses. The development cohort consisted of freshly frozen tissues from 38 patients collected between the years 1986 and 2009. Validation was performed on a consecutive cohort of formalin fixated paraffin embedded surgical tissue specimens from 183 patients treated at Odense and Aarhus University Hospitals. Results: A 17 gene classifier (ADAMTS1, ANTXR1, C7, CXCL12, EBF1, FBLN2, FOSL2, GGT5, GPR124, JAM3, LRIG1, NDRG1, PRRX1, ROBO1, SORL1, TCF4, and ZEB1) was identified based on the expression values of these genes in the groups with and without metastasis in the development cohort. The 17 gene classifier for regional and/or distant metastasis identified was tested against the clinical status in the validation cohort. Sensitivity was 51.6% (95% CI 41.2%-61.8) and specificity 61.6 % (95% CI 50.5%-71.9%). Further, the Kaplan-Meyer method was used to estimate whether the classifier was useful as a prognostic marker for recurrences. Log-rank testing failed to identify any significance (p=0.32). Conclusion: A 17 gene classifier for metastatic potential was developed, and the results showed a clear biological difference between groups. However, through validation, the prognostic significance of this classifier could not be shown in identifying metastatic cases or in the ability of dichotomizing patients according to risk of recurrence after primary treatment.
2015-01-20 | GSE65074 | GEO
Project description:Background: With the incidence of papillary thyroid carcinoma rising worldwide, the decision about lobectomy versus total thyroidectomy will become relevant for an increasing number of patients. There exists no reliable biomarker for metastatic potential or tendency of recurrence that could assist in the risk stratification of patients. Objective: To develop a gene expression classifier for metastatic potential by measuring RNA expression in the primary tumor at the time of cancer surgery. Further, to investigate the ability of the gene expression classifier to identify metastatic and recurrent cases. Method: Genome-wide expression analyses. The development cohort consisted of freshly frozen tissues from 38 patients collected between the years 1986 and 2009. Validation was performed on a consecutive cohort of formalin fixated paraffin embedded surgical tissue specimens from 183 patients treated at Odense and Aarhus University Hospitals. Results: A 17 gene classifier (ADAMTS1, ANTXR1, C7, CXCL12, EBF1, FBLN2, FOSL2, GGT5, GPR124, JAM3, LRIG1, NDRG1, PRRX1, ROBO1, SORL1, TCF4, and ZEB1) was identified based on the expression values of these genes in the groups with and without metastasis in the development cohort. The 17 gene classifier for regional and/or distant metastasis identified was tested against the clinical status in the validation cohort. Sensitivity was 51.6% (95% CI 41.2%-61.8) and specificity 61.6 % (95% CI 50.5%-71.9%). Further, the Kaplan-Meyer method was used to estimate whether the classifier was useful as a prognostic marker for recurrences. Log-rank testing failed to identify any significance (p=0.32). Conclusion: A 17 gene classifier for metastatic potential was developed, and the results showed a clear biological difference between groups. However, through validation, the prognostic significance of this classifier could not be shown in identifying metastatic cases or in the ability of dichotomizing patients according to risk of recurrence after primary treatment. 38 patients with papillary thyroid carcinoma from a consecutive cohort of patients, no replicates
2015-01-20 | E-GEOD-65074 | biostudies-arrayexpress
Project description:Purpose: We sought to develop and evaluate a diagnostic classifier of UC subtype with the goal of accurate classification from clinically available specimens. Methods: Tumor samples from 52 patients with high-grade UC were profiled for BASE47 genes concurrently by RNAseq as well as NanoString. After design and technical validation of a BASE47 NanoString probeset, results from the RNAseq and NanoString were used to translate diagnostic criteria to the Nanostring platform. Evaluation of repeatability and accuracy was performed to derive a final Nanostring based classifier. Diagnostic classification resulting from the NanoString BASE47 classifier was validated on an independent dataset (n=63). The training and validation datasets accurately classified 87% and 93% of samples, respectively. Results: We have derived a NanoString-platform BASE47 classifier that accurately predicts basal-like and luminal-like subtypes in high grade urothelial cancer. We have further validated our new NanoString BASE47 classifier on an independent dataset and confirmed high accuracy when compared with our original Transcriptome BASE47 classifier. Conclusions: The NanoString BASE47 classifier provides a faster turnaround time, a lower cost per sample to process, and maintains the accuracy of the original subtype classifier for better clinical implementation.
2020-11-03 | GSE160693 | GEO
Project description:Sodium valproate (VPA) and lithium are mood stabilizers, widely prescribed in the treatment of bipolar disorder, and yet the precise modes of therapeutic action for these drugs are not fully understood. After exposure of the rat serotonergic cell line RN46A to VPA, RNA-sequencing (RNA-Seq) analysis showed widespread changes in gene expression but no changes with lithium. Analysis by multiple pipelines revealed that as many as 230 genes were significantly upregulated and 72 genes were significantly downregulated in response to VPA exposure.
2020-03-07 | GSE146493 | GEO