Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcription profiling of human tumor and stroma from breast catured by LCM of inflammatory and non inflammatory breast cancers

ABSTRACT: Tumor epithelium and surrounding stromal cells were isolated using laser capture microdissection of human breast cancer to examine differences in gene expression based on tissue types from inflammatory and non-inflammatory breast cancer Experiment Overall Design: We applied LCM to obtain samples enriched in tumor epithelium and stroma from 15 IBC and 35 non-IBC cases to study the relative contribution of each component to the IBC phenotype and to patient survival.

ORGANISM(S): Homo sapiens

SUBMITTER: Boersma BJ

PROVIDER: S-ECPF-GEOD-5847 | biostudies-other | 2008 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

Transcription profiling of human tumor and stroma from breast catured by LCM of inflammatory and non inflammatory breast cancers

Project description:Tumor epithelium and surrounding stromal cells were isolated using laser capture microdissection of human breast cancer to examine differences in gene expression based on tissue types from inflammatory and non-inflammatory breast cancer Experiment Overall Design: We applied LCM to obtain samples enriched in tumor epithelium and stroma from 15 IBC and 35 non-IBC cases to study the relative contribution of each component to the IBC phenotype and to patient survival.

2008-06-14 | E-GEOD-5847 | biostudies-arrayexpress

Transcription profiling of human breast cancers

Project description:Signatures of Oncogenic Pathway Deregulation in Human Cancers. The ability to define cancer subtypes, recurrence of disease, and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Such data is also of substantial importance to the analysis of cellular signaling pathways central to the oncogenic process. With this focus, we have developed a series of gene expression signatures that reliably reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumors, and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumor sub-types. Clustering tumors based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Furthermore, predictions of pathway deregulation in cancer cell lines are shown to coincide with sensitivity to therapeutic agents that target components of the pathway, underscoring the potential for such pathway prediction to guide the use of targeted therapeutics. Experiment Overall Design: RNA was extracted from frozen tissue of primary breast tumors for gene array analysis.

| S-ECPF-GEOD-3143 | biostudies-other

Transcription profiling of human tumor-associated stroma derived from primary clinical breast cancer samples

Project description:Tumor-associated breast stroma was laser-capture microdissected from IDC breast cancer cases. The goal of the study was to characterize the heterogeneity of breast tumor-assocaited stroma and identify gene expression signatures predictive of clinical outcome. Experiment Overall Design: Common reference design, 53 samples, with dye-swap replicates. Some samples replicated three or four times, a total of 111 arrays.

| S-ECPF-GEOD-9014 | biostudies-other

Transcription profiling of human breast cancers (30)

Project description:We used microarrays to profile 30 human primary breast tumors and determine global gene expression patterns and molecular subtypes Experiment Overall Design: RNA from SNAP frozen human tumor biopsies was analyzed on Affymetrix mircroarrays

| S-ECPF-GEOD-12763 | biostudies-other

Transcription profiling of human breast cancers and lung metastatis

Project description:Validation of lung metastasis signature (LMS) and its association with risk of developing lung metastasis and with primary tumor size. Experiment Overall Design: 58 tumor samples

| S-ECPF-GEOD-5327 | biostudies-other

Transcription profiling of human male and female breast cancers

Project description:Gene expression profiling of male and female breast cancer samples

| S-ECPF-TABM-810 | biostudies-other

Transcription profiling of human breast tumor microvessels

Project description:Molecular Characterization of Human Breast Tumor Microvessels Experiment Overall Design: LCM & Microarrays

| S-ECPF-GEOD-7413 | biostudies-other

Transcription profiling of human breast tumor subtypes

Project description:Experiments that were used to make the "intrinsic" gene list from.

| S-ECPF-SMDB-2227 | biostudies-other

Inflammatory versus non-inflammatory breast cancers

Project description:Inflammatory versus non-inflammatory breast cancers

| PRJNA437146 | ENA

Inflammatory versus non-inflammatory breast cancers

Project description:Inflammatory Breast Cancer (IBC) is the most aggressive form of breast carcinoma characterized by the rapid onset of inflammatory signs. The molecular fingerprint for this rare, severe and unique clinical entity is still not elucidated. The goal of the present work was to detect both gene expression levels and alternate RNA splice variants specific to IBC. Experimental Design: In order to identify differentially expressed genes and splicing events, we performed splice-sensitive array profiling using Affymetrix Exon Array and quantitative RT-PCR analyses in a large series of 177 IBC compared to 183 non-IBC. We also assessed the prognostic value of the identified candidate genes and splice variants. Results: A 5-splice signature (HSPA8, RPL10, RPL4, DIDO1 and EVL) was able to distinguish IBC from non-IBC tumors (p<10-7). This splice signature was associated with poor metastasis-free survival (MFS) in hormone receptor-negative non-IBC (p=0.02), whereas it had no prognostic value in IBC patients. A PAM analysis of deregulated genes in IBC compared to non-IBC identified a 10-gene signature highly predictive of IBC phenotype and conferring a poor prognosis in non-IBC. The most up-regulated genes in IBC were 3 hemoglobin genes able to highly discriminate IBC from non IBC (p<10-4). In epithelial breast tumor cells, Hb protein expression was confirmed by immunohistochemistry. Conclusions: IBC has a specific spliced transcript profile that deserves further functional studies. Above all, IBC is characterized by hemoglobin genes overexpression, a fact that may lead to increased tumor progression. If confirmed, hemoglobins may serve as therapeutic targets.

2021-01-04 | GSE111477 | GEO

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