Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gene expression anlaysis of laser-capture microdissected tumor and stroma from triple negative breast cancer

ABSTRACT: LCM was perfomed on adjacent tumor and stromal cells to identify differentially expressed genes in triple negative breast cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE81838 | GEO | 2016/07/01

SECONDARY ACCESSION(S): PRJNA322670

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Gene expression anlaysis of laser-capture microdissected tumor and stroma from triple negative breast cancer

Project description:LCM was perfomed on adjacent tumor and stromal cells to identify differentially expressed genes in triple negative breast cancer. To determine differences in tumor and adjacent stromal tissue, laser-capture microdissction was perfomed on 10 triple negative breast cancer specimans to isolate tumor and stromal cells for gene expression analysis. RNA was isolated from captured cells and hybridized to affymetrix gene expression microarrays.

2016-07-01 | E-GEOD-81838 | biostudies-arrayexpress

Laser-capture microdissected invasive micropapillary carcinomas of the breast

Project description:The purpose of this study was to identify differentially expressed genes in laser-capture microdissected (LCM) invasive mammary carcinomas (IMCs).

2011-04-25 | GSE28821 | GEO

Laser-capture microdissected invasive micropapillary carcinomas of the breast

Project description:The purpose of this study was to identify differentially expressed genes in laser-capture microdissected (LCM) invasive mammary carcinomas (IMCs). Invasive mammary carcinoma of the breast surgical resection specimens were laser capture microdissected for RNA extraction and hybridization to Affymetrix microarrays.

2011-04-25 | E-GEOD-28821 | biostudies-arrayexpress

Transcriptomic Analysis of Laser Capture Microdissected Tumors of Pancreatic Ductal Adenocarcinoma

Project description:In this study, we performed laser capture microdissection (LCM) of PDAC samples to define their cancer- and stroma-specific molecular subtypes and identify a prognostic gene expression signature for short-term and long-term survival. LCM and RNA-seq analysis of cancer and adjacent stroma of 19 treatment-naïve PDAC tumors were performed. Gene expression signatures were tested for their robustness in a large independent validation set. An RNA in situ hybridization (RNA-ISH) assay with pooled probes for genes associated with disease-free survival (DFS) was developed to probe 111 PDAC tumor samples. Gene expression profiling identified four subtypes of cancer cells (C1-C4) and three subtypes of cancer-adjacent stroma (S1-S3). These stroma-specific subtypes were associated with DFS (p=5.55E-07), with S1 associated with better prognoses when paired with C1 and C2. Thirteen genes were found to be predominantly expressed in cancer cells and corresponded with DFS in a validation using existing RNA-seq datasets. A second validation on an independent cohort of patients using RNA-ISH probes to six of these prognostic genes demonstrated significant association with overall survival (median 17 versus 25 months; p<0.02). Our results identified specific signatures from the epithelial and the stroma components of PDAC, which add clarity to the nature of PDAC molecular subtypes and may help predict survival.

2021-06-30 | GSE164665 | GEO

Gene expression from laser capture microdissected pancreatic cancer epithelium and stroma

Project description:This study used laser capture microdissection to obtain paired tumor epithelium and stroma RNA samples from human pancreatic ductal adenocarcinoma (PDA) frozen sections. Libraries were prepared using the Nugen Ovation RNA-Seq System V2 and sequenced to a depth of 30 million 100bp single-end reads. These data were used to model compartment-specific gene expression density on a genome-wide scale and build an algorithm for transcriptional devonvolution (ADVOCATE). RNA sequencing of macrodissected bulk PDA sections was performed on 15 samples in order to systematically compare TruSeq and NuGEN RNA-Seq libraries and (ii) correlate histopathological and molecular assessment of tumor composition.

2018-11-27 | GSE93326 | GEO

Expression Profiles of Rats Treated with Clofibric Acid: Comparison of Whole and Laser Capture Microdissected Liver

Project description:This is an evaluation of the impact of the successive steps of LCM procedure on gene expression profiling by comparing profiles from LCM samples to those obtained with non-microdissected liver samples collected after a one month CLO treatment in the rat. We showed that the H&E staining used for identifying PP-foci and the laser microdissection itself do not impact on RNA quality. Keywords = Microdissection Keywords = Clofibric Acid Keywords: other

2003-12-03 | GSE691 | GEO

Epigenetic analysis of laser capture microdissected fetal epithelia.

Project description: Not available

| S-EPMC4356551 | biostudies-literature

Gene expression of invasive lobular carcinoma tumor epithelium and tumor stroma isolated by laser-capture microdissection

Project description:We used laser-capture microdissection (LCM) to separate tumor epithelium (TE) from stroma (TS) in 23 ILC samples. Gene expression analysis was used to identify genes that are enriched in the stroma of ILC, but not IDC or normal breast.

2022-04-01 | GSE148398 | GEO

Proteomic profiling of stromal reprogramming in canine simple mammary carcinomas using laser-capture microdissected FFPE tissue

Project description:Cancer-associated stroma (CAS) profoundly influences development and progression of tumours including mammary carcinoma (mCA). Spontaneous canine simple mCA represent relevant models of human mCA, notably also with respect to CAS reprogramming. While transcriptomic changes in CAS of mCA are well described, it remains unclear to what extent these differences translate to the protein level. Therefore, we sought to gain insight into the proteomic changes in CAS and compare them with transcriptomic changes in the same tissue. To this end, we analysed CAS and matched normal stroma isolated by laser-capture microdissection (LCM) by LC-MS/MS in a cohort of 14 Formalin-fixed paraffin embedded (FFPE) canine mCAs that we had previously characterized using LCM-RNAseq. Our results reveal clear differences in protein abundance between CAS and normal stroma, which are characterised by changes in the extracellular matrix, the cytoskeleton, and cytokines such as TNF. While the proteomics-based analysis of LCM-FFPE tissue detects fewer targets than RNAseq, the protein and RNA levels show a decent degree of correlation, especially for the most deregulated targets. Moreover, the results from both approaches reveal a comparable picture with regards to pathway activation. Finally, we validate transcriptomic upregulation of LTBP2, IGFBP2, COL6A5, POSTN, FN1, COL4A1, COL12A1, PLOD2, COL4A2, and IGFBP7 in CAS on the protein level and demonstrate their adverse prognostic value for human breast cancer. Given the relevance of canine mCA as model for the human disease, our analysis substantiates these targets as disease-promoting stromal components with implications for breast cancer in both humans and dogs.

2021-03-30 | PXD023023 | Pride

Exome-capture RNAseq of microdissected FFPE human breast cancer cells, cancer-associated fibroblasts, and surrounding tumor-infiltrating lymphocytes

Project description:Here we describe the development of a robust method for RNA extraction and exome-capture RNA-sequencing of laser-capture microdissected (LCM) tumor cells (TC) and stromal immune cells (TIL) based on their morphology. We applied this method on seven tumor specimens and microbiopsies of triple-negative breast cancers (TNBC) stored in FFPE blocks. Together, we showed that combining LCM and RNA-sequencing on archived FFPE blocks is feasible and allows spatial transcriptional characterization of the tumor microenvironment.

2021-10-31 | E-MTAB-8760 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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