Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA171564 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Gene expression profiling of pheochromocytoma (PCC)/paraganglioma (PGL) tumors
| PRJNA120361 | ENA
Project description:Pheochromocytoma (PCC) and paraganglioma (PGL) are neuroendocrine tumours arising in the adrenal medulla and paraganglia of the autonomous nervous system, respectively. Malignant PCC/PGL are mostly caused by germline mutations of SDHB, encoding a subunit of succinate dehydrogenase. Gene expression changes associated with SDHB inactivation were investigated in a two genetically defined murine cellular models. These models were generated by Cre-mediated recombination in spontaneously immortalized mouse chromaffin cells (imCCs) and adrenal fibroblasts (MAFs).
2015-11-04 | E-MTAB-3403 | biostudies-arrayexpress
Project description:Expression profiles of pheochromocytoma and paraganglioma
| PRJNA258323 | ENA
Project description:Pheochromocytoma (PCC) and paraganglioma (PGL) are rare neuroendocrine neoplasias of neural crest origin. They can be part of several syndromes, and their mRNA profile is dependent on genetic background, but questions related to clinical behavior or even main location remain unanswered. MicroRNAs are key modulators of target genes through translational repression, mRNA degradation, or both, and therefore they could resolve some of these issues. To determine the role microRNAs play in tumorigenesis and progression of PCC/PGL, as well as to identify microRNA biomarkers specifically related to different PCC/PGL genetic classes known so far, we characterized microRNA profiles in a large series of frozen tumors with germline mutations in SDHD, SDHB, VHL, RET, NF1, and TMEM127 genes through microarray analysis. We identified microRNA signatures specific to, as well as common among, the genetic classes of PCC/PGLs, and the best candidate microRNAs (miR-122, miR-126*, miR-129*, miR-133b, miR-137, miR-183, miR-210, miR-382, miR-488, miR-885-5p, and miR-96) were validated in an independent series of formalin-fixed paraffin-embedded PCC/PGL samples by qRT-PCR. MicroRNA-137, -96/183, and -143/145 expression in PCC/PGLs correlated inversely with the differentiation status of tumor cells. MicroRNA-210, -382, and -380 could modulate pseudohypoxic cellular response in VHL-deficient PCC/PGL. MicroRNA-193b, -365, and -424 were commonly downregulated among all genetic classes, suggesting their involvement in cell cycle control and differentiation. Herein, we demonstrate that PCC/PGLs have different microRNA profiles according to the underlying primary mutation, suggesting they could be used as specific biomarkers and add information on the etiology of these tumors.
2013-07-02 | GSE29742 | GEO
Project description:Cytogenetic analysis of 36 pheochromocytoma and four paraganglioma using high density arrays A series of 36 pheochromocytoma and four paraganglioma were analysed for genomic structural alterations using high density copy number arrays
2014-09-21 | E-GEOD-61594 | biostudies-arrayexpress
Project description:Until now, it is nearly impossible to diagnose malignancy of pheochromocytoma/paraganglioma with pathological examinations. The aim of the study is to find the genes which can be applied as a biomarker in the clinic to distinguish benign and malignant forms of pheochromocytoma/paraganglioma.
2014-08-17 | GSE60457 | GEO
Project description:Transcriptional analysis of 84 primary pheochromocytoma (PCC)/paraganglioma tumors. 84 samples (primary pheochromocytoma (PCC)/paraganglioma tumors) were hybridized onto a cDNA microarray in order to investigate possible heterogeneity within these tumors
2010-12-31 | E-GEOD-19422 | biostudies-arrayexpress
Project description:Pheochromocytoma (PCC) and paraganglioma (PGL) are rare neuroendocrine neoplasias of neural crest origin. They can be part of several syndromes, and their mRNA profile is dependent on genetic background, but questions related to clinical behavior or even main location remain unanswered. MicroRNAs are key modulators of target genes through translational repression, mRNA degradation, or both, and therefore they could resolve some of these issues. To determine the role microRNAs play in tumorigenesis and progression of PCC/PGL, as well as to identify microRNA biomarkers specifically related to different PCC/PGL genetic classes known so far, we characterized microRNA profiles in a large series of frozen tumors with germline mutations in SDHD, SDHB, VHL, RET, NF1, and TMEM127 genes through microarray analysis. We identified microRNA signatures specific to, as well as common among, the genetic classes of PCC/PGLs, and the best candidate microRNAs (miR-122, miR-126*, miR-129*, miR-133b, miR-137, miR-183, miR-210, miR-382, miR-488, miR-885-5p, and miR-96) were validated in an independent series of formalin-fixed paraffin-embedded PCC/PGL samples by qRT-PCR. MicroRNA-137, -96/183, and -143/145 expression in PCC/PGLs correlated inversely with the differentiation status of tumor cells. MicroRNA-210, -382, and -380 could modulate pseudohypoxic cellular response in VHL-deficient PCC/PGL. MicroRNA-193b, -365, and -424 were commonly downregulated among all genetic classes, suggesting their involvement in cell cycle control and differentiation. Herein, we demonstrate that PCC/PGLs have different microRNA profiles according to the underlying primary mutation, suggesting they could be used as specific biomarkers and add information on the etiology of these tumors. For this study, we employed the Agilent-019118 Human miRNA Microarray 2.0 G4470B (with Labeling kit: Agilent miRNA labeling reagent and Hybridization Kit, Cat # 5190-0408) to perform microRNA expression profiling on a large series of 54 fresh-frozen tissue samples, including a total of 48 genetically characterized pheochromocytomas (n=37) and paragangliomas (n=11) (8 SDHB-related tumors, 4 SDHD-related tumors, 14 Ret-related tumors, 12 VHL-related tumors, 4 NF1-related tumors, 3 TMEM127-related tumors, and 3 familial pheochromocytoma (FPCC) samples), and 6 normal adrenal medulla. Normalization of array data was performed applying the robust multiarray average (RMA) method using the AgiMicroRna package in Bioconductor. RMA normalization, by default, merges replicates of each probe and produces an Eset with a single value for each microRNA.
2013-07-02 | E-GEOD-29742 | biostudies-arrayexpress
Project description:Copy number profiles of pheochromocytoma and paraganglioma
| PRJNA258322 | ENA
Project description:Cytogenetic analysis of 36 pheochromocytoma and four paraganglioma using high density arrays
2014-09-21 | GSE61594 | GEO