Ontology highlight
ABSTRACT:
PROVIDER: PRJNA899575 | ENA |
REPOSITORIES: ENA
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Project description:Natural flavonoid pectolinarigenin (PEC) was reported to alleviate tubulointerstitial fibrosis of unilateral ureteral obstruction (UUO) mice in our previous study. To further investigate nephroprotective effects of PEC in hyperuricemic nephropathy (HN), adenine and potassium oxonate induced HN mice and uric acid-treated mouse kidney epithelial (TCMK-1) cells were employed in the study. As a result, PEC significantly lowered serum uric acid level and restored hyperuricemia-related kidney injury in HN mice. Meanwhile, PEC alleviated inflammation, fibrosis and reduced adipokine FABP4 content in the kidneys of HN mice and uric acid-treated TCMK-1 cells. Mechanistically, PEC inhibited the TGF-β1 expression as well as the phosphorylation of transcription factor SMAD3 and STAT3 to regulate the corresponding inflammatory and fibrotic gene expression in kidney tissues. In conclusion, our results suggested that PEC could inhibit the activation of SMAD3 and STAT3 signaling to suppress inflammation and fibrosis, thereby alleviate HN in mice.
2022-02-18 | GSE190205 | GEO
Project description:Background and Objective: Hypertensive nephropathy (HN) requires a kidney biopsy as gold-standard for its diagnosis but histological findings are not entirely specific and lack specific prognostic markers. We aimed at defining prognostic candidate markers based on glomerular protein signatures. Method: We included adult patients (n=17) with an eGFR >30 ml/min/1.73m2 and proteinuria <3g/d from the Norwegian Kidney Biopsy Registry: stable patients (n=9) and subjects with HN progression (n=8) leading to end-stage renal disease (ESRD) within 20 years of follow-up. Glomerular cross-sections were microdissected from archival kidney biopsy sections and processed for protein extraction. Proteomic analyses were performed using Q-exactive HF mass spectrometer and relative glomerular protein abundance were compared between progressive vs non-progressive patients. Results: Amongst 1870 quality filtered proteins, we identified 58 proteins with an absolute fold change (FC)>1.5, p<0.05, including 17 proteins with absolute FC >2, indicative of HN progression (highest FC: Cadherin 16 and UDP-glucuronosyl-transferase 2B7). Hierarchical cluster and principal component analysis (PCA) with the 17 proteins showed clear separation of samples into HN progressors and non-progressors. Supervised classifier analysis (K nearest neighbour) identified a set of five proteins which classified 16/17 samples correctly. Applying Geneset Enrichment Analysis (GSEA), in general metabolic pathways were enriched in progressors, and structural cell pathways enriched in non-progressors. Pathway analysis identified Epithelial Adherens Junction Signaling as the most affected canonical pathway. The signature of HN progression is different from the respective signature of IgA progression. Conclusion: Glomerular proteomic profiling can be used to discriminate progressors from non-progressors in HN.
2023-05-23 | PXD026709 | Pride
Project description:We comparatively evaluated transcriptomes from renal biopsies obtained from patients with T2DN or HN, main causes of CKD, and control renal tissues (n=6 per group). RNA was extracted from formalin-fixed and paraffin-embedded kidney samples and processed for RNA sequencing. Principal component analysis effectively separated diseased and control tissues. Gene and protein expression profiles revealed that EMT-related markers were upregulated in both diseases. Moreover, activation of CD4 and CD lymphocytes, as well as upregulation of the complement system were also observed in both T2DN and HN. These data, suggesting partially common pathogenetic mechanisms, were largely confirmed by IHC analysis.
2023-12-01 | GSE166239 | GEO
Project description:Proliferative breast lesions, such as simple ductal hyperplasia (SH) and atypical ductal hyperplasia (ADH), are candidate precursors to ductal carcinoma in situ (DCIS) and invasive cancer. To better understand their relationship to more advanced disease, we used microdissection and DNA microarrays to profile the gene expression of patient-matched histologically normal (HN), ADH, and DCIS from 12 patients with ER+ sporadic breast cancer. SH were profiled from a subset of cases. We found 837 differentially expressed genes between DCIS-HN and 447 between ADH-HN, with >90% of the ADH-HN genes also present among the DCIS-HN genes. Only 61 genes were identified between ADH-DCIS. Expression differences were reproduced in an independent cohort of patient-matched lesions by qRT-PCR. Many breast cancer-related genes and pathways were dysregulated in ADH and maintained in DCIS. Particularly, cell adhesion and extracellular matrix (ECM) interactions were overrepresented. Focal adhesion was the top pathway in each gene set. We conclude that ADH and DCIS share highly similar gene expression and are distinct from HN. In contrast, SH appear more similar to HN. These data provide genetic evidence that ADH (but not SH) are often precursors to cancer and suggest cancer-related genetic changes, particularly adhesion and ECM pathways, are dysregulated prior to invasion and even before malignancy is apparent. These findings could lead to novel risk stratification, prevention, and treatment approaches. Patient-matched (HN, SH, ADH, DCIS) samples were isolated from within patients with ER+ sporadic breast cancers via laser capture microdissection. Use of patient-matched samples decreases between patient variations.
2009-09-08 | GSE16873 | GEO
Project description:Rice productivity relies heavily on nitrogen fertilization, and improving nitrogen use efficiency (NUE) is important for hybrid rice breeding. Reducing nitrogen inputs is the key to achieving sustainable rice production and reducing environmental problems. Here, we analyzed the genome-wide transcriptomic changes in microRNAs (miRNAs) in the indica rice restorer cultivar NH511 (Nanhui 511) under high (HN) and low nitrogen (LN) conditions. The results showed that NH511 is sensitive to nitrogen supplies and HN conditions promoted the growth its lateral roots at the seedling stage. Furthermore, we identified 483 known miRNAs and 128 novel miRNAs by small RNA sequencing in response to nitrogen in NH511. We also detected 100 differentially expressed genes (DEGs), including 75 upregulated and 25 downregulated DEGs, under HN conditions. Among these DEGs, 43 miRNAs that exhibited a 2-fold change in their expression were identified in response to HN conditions, including 28 upregulated and 15 downregulated genes. Additionally, some differentially expressed miRNAs were further validated by qPCR analysis, which showed that miR443, miR1861b, and miR166k-3p were upregulated, whereas miR395v and miR444b.1 were downregulated under HN conditions. Moreover, the degradomes of possible target genes for miR166k-3p and miR444b.1 and expression variations were analyzed by qPCR at different time points under HN conditions. Our findings revealed comprehensive expression profiles of miRNAs responsive to HN treatments in an indica rice restorer cultivar, which advances our understanding of the regulation of nitrogen signaling mediated by miRNAs and provides novel data for high-NUE hybrid rice cultivation.
2023-04-20 | GSE230023 | GEO
Project description:Gene expression in histologically normal epithelium from breast cancer patients and cancer-free prophylactic mastectomy patients share a similar profile Introduction: We hypothesized that gene expression in histologically normal epithelium (NlEpi) would differ in breast cancer patients (HN) compared to usual-risk controls undergoing reduction mammoplasty (RM), and that gene expression in NlEpi from cancer-free prophylactic mastectomies from high-risk women (PM), would resemble HN gene expression. Methods: We analyzed gene expression in 73 NlEpi samples microdissected from frozen tissue. In 42 cases, we used Affymetrix HU133A microarrays to compare gene expression in 18 RM vs 18 age-matched HN (9 ER+, 9 ER-) and 6 PM. Data were validated with qPCR in 31 independent NlEpi samples (8 RM, 17 HN, 6 PM). Results: 98 probesets (86 genes) were differentially expressed between RM and HN samples. Perfoming supervised hierarchical analysis with these 98 probesets, PM and HN samples clustered together, away from RM samples. qPCR validation of independent samples was high (84%) and uniform in RM vs HN, and lower (58%), but more heterogeneous, in RM vs PM. The 86 genes were implicated in many processes including transcription and the MAPK pathway. Conclusion: Gene expression differs between NlEpi of cancer cases and controls. The cancer cases' profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. We determined that 98 probesets significantly differed between reduction mammoplasty and histologically normal epithelium from breast cancer patients. We also found that the histologically normal epithelium from prophylactic mastectomy patients' gene expression was more similar to histologically normal epithelium from breast cancer patients' than to reduction mammoplasty patients' gene expression. These results demonstrate that gene expression differs between NlEpi of cancer cases and controls. The cancer cases’ profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes.
2010-06-01 | GSE20437 | GEO
Project description:Proliferative breast lesions, such as simple ductal hyperplasia (SH) and atypical ductal hyperplasia (ADH), are candidate precursors to ductal carcinoma in situ (DCIS) and invasive cancer. To better understand their relationship to more advanced disease, we used microdissection and DNA microarrays to profile the gene expression of patient-matched histologically normal (HN), ADH, and DCIS from 12 patients with ER+ sporadic breast cancer. SH were profiled from a subset of cases. We found 837 differentially expressed genes between DCIS-HN and 447 between ADH-HN, with >90% of the ADH-HN genes also present among the DCIS-HN genes. Only 61 genes were identified between ADH-DCIS. Expression differences were reproduced in an independent cohort of patient-matched lesions by qRT-PCR. Many breast cancer-related genes and pathways were dysregulated in ADH and maintained in DCIS. Particularly, cell adhesion and extracellular matrix (ECM) interactions were overrepresented. Focal adhesion was the top pathway in each gene set. We conclude that ADH and DCIS share highly similar gene expression and are distinct from HN. In contrast, SH appear more similar to HN. These data provide genetic evidence that ADH (but not SH) are often precursors to cancer and suggest cancer-related genetic changes, particularly adhesion and ECM pathways, are dysregulated prior to invasion and even before malignancy is apparent. These findings could lead to novel risk stratification, prevention, and treatment approaches. Patient-matched (HN, SH, ADH, DCIS) samples were isolated from within patients with ER+ sporadic breast cancers via laser capture microdissection. Use of patient-matched samples decreases between patient variations. Forty total samples were analyzed via Affymetrix U133A. Patient age ranged from 48-92. Case numbers correspond to individual patients. Each sample is identified by case number, histologic lesion and corresponding microarray ID.
2009-09-08 | E-GEOD-16873 | biostudies-arrayexpress
Project description:Mardinoglu2015 - Tissue-specific genome-scale
metabolic network - Kidney cortex
This model is described in the article:
The gut microbiota modulates
host amino acid and glutathione metabolism in mice.
Mardinoglu A, Shoaie S, Bergentall
M, Ghaffari P, Zhang C, Larsson E, Bäckhed F, Nielsen
J.
Mol. Syst. Biol. 2015; 11(10):
834
Abstract:
The gut microbiota has been proposed as an environmental
factor that promotes the progression of metabolic diseases.
Here, we investigated how the gut microbiota modulates the
global metabolic differences in duodenum, jejunum, ileum,
colon, liver, and two white adipose tissue depots obtained from
conventionally raised (CONV-R) and germ-free (GF) mice using
gene expression data and tissue-specific genome-scale metabolic
models (GEMs). We created a generic mouse metabolic reaction
(MMR) GEM, reconstructed 28 tissue-specific GEMs based on
proteomics data, and manually curated GEMs for small intestine,
colon, liver, and adipose tissues. We used these functional
models to determine the global metabolic differences between
CONV-R and GF mice. Based on gene expression data, we found
that the gut microbiota affects the host amino acid (AA)
metabolism, which leads to modifications in glutathione
metabolism. To validate our predictions, we measured the level
of AAs and N-acetylated AAs in the hepatic portal vein of
CONV-R and GF mice. Finally, we simulated the metabolic
differences between the small intestine of the CONV-R and GF
mice accounting for the content of the diet and relative gene
expression differences. Our analyses revealed that the gut
microbiota influences host amino acid and glutathione
metabolism in mice.
This model is hosted on
BioModels Database
and identified by:
MODEL1509220012.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2015-11-04 | MODEL1509220012 | BioModels
Project description:Mardinoglu2015 - Tissue-specific genome-scale
metabolic network - Kidney medulla
This model is described in the article:
The gut microbiota modulates
host amino acid and glutathione metabolism in mice.
Mardinoglu A, Shoaie S, Bergentall
M, Ghaffari P, Zhang C, Larsson E, Bäckhed F, Nielsen
J.
Mol. Syst. Biol. 2015; 11(10):
834
Abstract:
The gut microbiota has been proposed as an environmental
factor that promotes the progression of metabolic diseases.
Here, we investigated how the gut microbiota modulates the
global metabolic differences in duodenum, jejunum, ileum,
colon, liver, and two white adipose tissue depots obtained from
conventionally raised (CONV-R) and germ-free (GF) mice using
gene expression data and tissue-specific genome-scale metabolic
models (GEMs). We created a generic mouse metabolic reaction
(MMR) GEM, reconstructed 28 tissue-specific GEMs based on
proteomics data, and manually curated GEMs for small intestine,
colon, liver, and adipose tissues. We used these functional
models to determine the global metabolic differences between
CONV-R and GF mice. Based on gene expression data, we found
that the gut microbiota affects the host amino acid (AA)
metabolism, which leads to modifications in glutathione
metabolism. To validate our predictions, we measured the level
of AAs and N-acetylated AAs in the hepatic portal vein of
CONV-R and GF mice. Finally, we simulated the metabolic
differences between the small intestine of the CONV-R and GF
mice accounting for the content of the diet and relative gene
expression differences. Our analyses revealed that the gut
microbiota influences host amino acid and glutathione
metabolism in mice.
This model is hosted on
BioModels Database
and identified by:
MODEL1509220008.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2015-11-04 | MODEL1509220008 | BioModels
Project description:Mutation in the huntingtin (HTT) gene causes Huntington’s disease. Wild type Htt is essential for development as Htt knockout mice die at day E7.5. Increasing evidence suggests mutant Htt may alter neurogenesis and development of striatal neurons resulting in neuronal loss. Using mouse embryonic stem cells (mESCs), we examined the role of Htt in neural differentiation. We found Htt-null (HN) mESCs inefficient in generating neural stem cells. In contrast differentiation into progenitors of mesoderm and endoderm lineages was not affected. To investigate the basis for the lack of neural differentiation, we carried out gene expression profiling by RNA-seq to examine if genes involved in neural differentiation were dysregulated in HN mESCs.
2017-01-03 | GSE92905 | GEO