Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gene expression profile of microdissected mucinous cystic neoplasms of the pancreas

ABSTRACT: Gene expression profile of laser-capture microdissected epithelium component of 6 mucinous cystic neoplasms of the pancreas were included in the study. The expression arrays were generated with Affymetrix HU133A gene chips (18,462 genes/EST transcripts).

ORGANISM(S): Homo sapiens

SUBMITTER: Intidhar Labidi-Galy

PROVIDER: E-MTAB-6853 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Publications

Characterization of gene expression in mucinous cystic neoplasms of the pancreas using oligonucleotide microarrays.

Fukushima Noriyoshi N Sato Norihiro N Prasad Nijaguna N Leach Steven D SD Hruban Ralph H RH Goggins Michael M

Oncogene 20041201 56

Mucinous cystic neoplasms (MCNs) of the pancreas are uncommon neoplasms usually located in the body or tail of the pancreas and usually in females (>90% of cases). Clinically, they are often misdiagnosed as non-neoplastic pseudocysts leading to failed opportunities for curative resection. To better understand the biology of MCNs and to identify markers of the disease, we performed global gene expression profiling of MCNs using oligonucleotide microarrays. Using laser capture microdissection appl ...[more]

PMID: 15489895

Similar Datasets

miRNAs in ovarian cancer: A systems approach (mRNA data)

Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. We report the results of a systems analysis of miRNA regulation in ovarian cancer. We found that 33 miRNAs are up-regulated and 9 down-regulated in CEPI relative to OSE (p<0.01, ≥2 fold change). Of these, 12 were previously annotated miRNAs (Sanger miRBase) of which 9 are up-regulated and 3 are down-regulated in CEPI relative to OSE. Current models predict that changes in levels of miRNAs will be inversely correlated with changes in the levels of targeted mRNAs due to miRNA regulation. This predicted inverse correlation held for only ~9% of predicted target mRNAs. Computational analyses indicate the unexpected low inverse correlation may be at least partially explained by variation in the number of miRNA binding sites within the 3’ UTRs of targeted mRNAs and by miRNA-mediated changes in levels of transcription factors that can exert overriding trans-regulatory controls on target loci. mRNAs were collected from three laser captured microdissected ovarian cancer epithelial (CEPI) samples. The mRNA expression pattern was compared with five healthy ovarian surface epithelia samples as controls using the Affymetrix U133 Plus 2.0 3' expression array.

2011-07-28 | E-GEOD-23391 | biostudies-arrayexpress

miRNAs in ovarian cancer: A systems approach (miRNA data)

Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. We report the results of a systems analysis of miRNA regulation in ovarian cancer. We found that 33 miRNAs are up-regulated and 9 down-regulated in CEPI relative to OSE (p<0.01, ≥2 fold change). Of these, 12 were previously annotated miRNAs (Sanger miRBase) of which 9 are up-regulated and 3 are down-regulated in CEPI relative to OSE. Current models predict that changes in levels of miRNAs will be inversely correlated with changes in the levels of targeted mRNAs due to miRNA regulation. This predicted inverse correlation held for only ~9% of predicted target mRNAs. Computational analyses indicate the unexpected low inverse correlation may be at least partially explained by variation in the number of miRNA binding sites within the 3’ UTRs of targeted mRNAs and by miRNA-mediated changes in levels of transcription factors that can exert overriding trans-regulatory controls on target loci. miRNAs were collected from three laser captured microdissected ovarian cancer epithelial (CEPI) samples. The miRNA expression pattern was compared with three healthy ovarian surface epithelia samples as controls using a custom-manufactured Affymetrix GeneChip® array.

2011-07-28 | E-GEOD-23383 | biostudies-arrayexpress

miRNAs in ovarian cancer: A systems approach

Project description:This SuperSeries is composed of the following subset Series: GSE23383: miRNAs in ovarian cancer: A systems approach (miRNA data) GSE23391: miRNAs in ovarian cancer: A systems approach (mRNA data) GSE27431: miRNAs in ovarian cancer: A systems approach (MAS5, plier, GCRMA) Refer to individual Series

2011-07-28 | E-GEOD-23392 | biostudies-arrayexpress

Transcription profiling of microdissected global and orbital layers of the rectus extraocular muscle (EOM) from adult Sprague-Dawley rats

Project description:Adult rat global and orbital layers of rectal extraocular muscles microdissected using Arcturus Pixcell II LCM are gene profiled here using affymetrix rat RAE230A gene chip. www.med.upenn.edu/cellbio/faculty/rubinstein/; www.uphs.upenn.edu/pmi/members/khurana/lab%20page.htm

2007-10-31 | E-GEOD-1374 | biostudies-arrayexpress

Transcription profiling of human endothelial cells and pericytes from endometriotic nodules and control endometrial and myometrial tissue to identify specific markers of rectovaginal endometriotic nodule vasculature

Project description:To identify specific markers of rectovaginal endometriotic nodule vasculature, highly enriched preparations of vascular endothelial cells and pericytes were obtained from endometriotic nodules and control endometrial and myometrial tissue by laser capture microdissection (LCM), and gene expression profiles were screened by microarray analysis. Of the 18,400 transcripts on the arrays, 734 were significantly overexpressed in vessels from fibromuscular tissue and 923 in vessels from stromal tissue of endometriotic nodules, compared to vessels dissected from control tissues. The most frequently expressed transcripts included known endothelial cell-associated genes, as well as transcripts with little or no previous association with vascular cells. The higher expression in blood vessels was further corroborated by immunohistochemical staining of 6 potential markers, 5 of which showed strong expression in pericytes. The most promising marker was matrix Gla protein, which was found to be present in both glandular epithelial cells and vascular endothelial cells of endometriotic lesions, while it was barely expressed at all in normal endometrium.

2007-09-30 | E-MEXP-1251 | biostudies-arrayexpress

The naked endosperm genes encode duplicate ID domain transcription factors required for maize endosperm differentiation

Project description:The objective of the current study is to unravel the gene regulatory networks controlled by the nkd genes during maize endosperm development. We compared wild type (B73) vs. nkd mutant (introgressed into B73 background) transcriptomes in aleurone vs. starchy endosperm cell types captured by laser capture microdissection technology. We performed RNA seq analysis of mid-mature (15DAP) endosperm in two cell types [aleurone (A) and starchy endosperm (S)] of wild type B73 (B) and nkd mutant (N) kernels with three independent biological replicates.

2015-01-28 | E-GEOD-61057 | biostudies-arrayexpress

A window into disease: Protein signatures of remodeled airways in transplanted lungs with Bronchiolitis Obliterans Syndrome

Project description:Background: Bronchiolitis obliterans syndrome (BOS), the most common form of chronic lung allograft dysfunction (CLAD), is the major limitation to long-term survival after lung transplantation. The patho-anatomical correlate is progressive, fibrotic occlusion of the small airways, so-called obliterative bronchiolitis (OB) –lesions, ultimately leading to organ failure. The molecular composition of these lesions is unknown. Methods: By combining laser-capture microdissection (LCM) and optimized sample preparation protocols for mass spectrometry (MS) we analyzed end-stage OB-lesions identified in explanted lungs from four end-stage BOS patients. Immunohistochemistry and immunofluorescence were used to follow selected proteins of interest on the tissue level. Results: We established protein signatures for in total 15 OB-lesions. A set of 12 proteins identified in all lesions included both distinct structural proteins (collagen type IV and VI) and cellular components (actins, vimentin, tryptase). Each respective lesion exhibited a unique composition of proteins (on average n=66), thereby mirroring the histomorphological variation of the lesions. Conclusions: Even though being distinct and focal pathologic events, OB-lesions showed considerable variations in their protein content, most likely reflecting different disease pathways. Combining spatial information and advanced protein identification, this study provides molecular and morphological insights essential for a better understanding of the development of chronic rejection after lung transplantation.

2021-05-19 | PXD014171 | Pride

Expression data from LCM captured prostate cancer cells

Project description:The prostate represents a complex mix of cell types and there is a need to analyze distinct cell populations to better understand their potential interactions. This study of cell-type specific gene expression patterns will contribute to understanding of how tumor epithelial cells may be affected by adjacent interstitial stromal cells within the tumor microenvirnonment. LCM and microarray analysis were used to identify gene expression patterns in prostate cancer epithelial and interstitial stromal cell populations. More than 500 genes whose expression levels were significantly different in epithelial cells versus adjacent stromal tissue were identified. Several chemokines and growth factors were more highly expressed in prostate cancer stromal cells while several transcription factors and receptors were more highly expressed in epithelial cells. Five micron serial sections from three different intermediate grade prostate tumors were provided. One section from each had been stained by hematoxylin and eosin and the tumor areas marked for identification. To obtain RNA from 2 different tissue types (glandular epithelium and interstitial stroma) tumor areas observed to have abundant cells of interest were identified. Tumor epithelium and adjacent stromal tissue were collected separately from each slide. We sought to obtain similar populations of cells of each tissue type, so to that end, we examined each slide and and marked areas to direct the laser capture. Approximately 1,000 cells were captured per cap and RNA was extracted and hybridized to Affymetrix microarrays as recommended by manufacturer.

2010-04-10 | E-GEOD-20758 | biostudies-arrayexpress

Microarray of pancreatic cancer and healthy tissue

Project description:Gene expression analyses of pancreatic adenocarcinoma and adjacent ductal epithelia from the same patient using bulk vs LCM dissected samples. Our results indicate that laser capture microdissection (LCM) is necessary to identify differentially expressed genes that discriminate between PDAC and healthy pancreatic ductal tissue. Pancreatic tissues were collected at time of surgery and snap frozen in liquid nitrogen for RNA extraction and Affymetrix GeneChip Expression analyses.

2014-12-31 | E-GEOD-27890 | biostudies-arrayexpress

Tryptic peptide imaging of an urothelial cancer tissue cohort

Project description:Analysis of a clinical urothelial cancer cohort for their spatial tryptic peptide composition in two different tissue types, tumor and stroma, and two tumor subtypes, muscle-infiltrating and non muscle-infiltrating tumors.

2021-06-04 | PXD026459 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data