Browse
Submit Data
Databases
API
Help

Dataset Information

23 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcription profiling of human and mouse breast cancers to identify conserved breast tumour genes

ABSTRACT: The aim of our work was the comparison of human and mouse gene expression data and to identify a conserved breast tumor gene set. The results encourage the usefulness of transgenic mice as a model for human breast cancer formation and therapy. Experiment Overall Design: The aim of our work was to establish a database for breast cancer gene expression data in order to compare human and mouse breast cancer. We identified human and mouse homologues genes and compared the expression profile of 24 human breast tumors with six WAP-SVT/t breast tumors (WAP-SVT/t animals, line 8). Our studies confirmed the heterogeneity in gene expression of human as well as mouse breast cancer cells. However, 63 genes were found to be differentially expressed (upregulated: 40; downregulated: 23 genes) in at least 75% of the breast tumors of both species.

ORGANISM(S): Homo sapiens

SUBMITTER: Klein A

PROVIDER: S-ECPF-GEOD-6596 | biostudies-other | 2007 Aug

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

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 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 cancer metastasis to the brain to identify genes involved

Project description:Brain metastasis is one of the most feared complications of cancer and the most common intracranial malignancy in adults. Its underlying mechanisms remain unknown. From breast cancer patients with metastatic disease we isolated cell populations that aggressively colonize the brain. Transcriptomic analysis of these cells yielded overlapping gene sets whose expression is selectively associated with brain metastasis. The expression of seventeen of these genes in primary breast tumors is associated with brain relapse in breast cancer patients. Some of these genes are also associated with metastasis to lung but not to liver, bone or lymph nodes, providing a molecular basis for the long-observed clinical link between brain and lung metastasis. Among the functionally validated brain metastasis genes, the cyclooxygenase COX-2, the EGFR ligand HB-EGF, and the brain-specific α2-6 sialyltransferase ST6GALNAC5 mediate cancer cell passage through the blood-brain barrier. Other brain metastasis genes encode inflammatory factors and brain-specific proteolytic regulators, suggesting a multifaceted program for breast cancer colonization of the brain. Experiment Overall Design: Two different breast cancer cell lines, MDA-MB-231 and freshly isolated pleural effusion CN34 were used in this study. The MDA-MB-231 group contains three biological replicates of the parental, unselected population, and 4 brain metastatic isolates. CN34 contains 2 biological replicates of the parental, unselected population, and 4 brain metastatic isolates. In each case, the parental population was compared to the brain metastatic isolates to identify gene expression changes associated with the brain metastatic phenotype.

| S-ECPF-GEOD-12237 | 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 radiation associated breast cancers reveals distinct subtypes

Project description:BfHL's, spor zonder BfNHL's en BfHL4

| S-ECPF-NCMF-30 | biostudies-other

Transcription profiling by array of human breast cancers after treatment with tamoxifen

Project description:Purpose: A number of microarray studies have reported distinct molecular profiles of breast cancers (BC): basal-like, ErbB2-like and two to three luminal-like subtypes. These were associated with different clinical outcomes. However, although the basal and the ErbB2 subtypes are repeatedly recognized, identification of estrogen receptor (ER)-positive subtypes has been inconsistent. Refinement of their molecular definition is therefore needed. Materials and methods: We have previously reported a gene-expression grade index (GGI) which defines histological grade based on gene expression profiles. Using this algorithm, we assigned ER-positive BC to either high or low genomic grade subgroups and compared these to previously reported ER-positive molecular classifications. As further validation, we classified 666 ER-positive samples into subtypes and assessed their clinical outcome. Results: Two ER-positive molecular subgroups (high and low genomic grade) could be defined using the GGI. Despite tracking a single biological pathway, these were highly comparable to the previously described luminal A and B classification and significantly correlated to the risk groups produced using the 21-gene recurrence score. The two subtypes were associated with statistically distinct clinical outcome in both systemically untreated and tamoxifen-treated populations. Conclusions: The use of genomic grade can identify two clinically distinct ER-positive molecular subtypes in a simple and highly reproducible manner across multiple datasets. This study emphasizes the important role of proliferation-related genes in predicting prognosis in ER-positive BC. Experiment Overall Design: dataset of microarray experiments from primary breast tumors used to assess the reationship between GGI, molecular subtypes, and tamoxifen resistance. Experiment Overall Design: No replicate, no reference sample.

| S-ECPF-GEOD-6532 | biostudies-other

Transcription profiling of human breast tumors to identify a signature to predict survival

Project description:Expression profiling of breast cancer patients to identify a signature

| S-ECPF-UCON-1 | biostudies-other

Transcription profiling of human lung cancers to identify signatures that reflect the activation status of oncogenic pathways

| S-ECPF-GEOD-3141 | biostudies-other

Transcription profiling of breast cancer tissue from 64 patients to identify transcriptional differences between subgroups of grade III invasive ductal breast cancers

Project description:To gain insights into the transcriptional differences between subgroups of grade III invasive ductal breast cancers, we performed gene expression profiling of a series of RNA extracted from microdissected frozen tissue from patients with breast cancer

| S-ECPF-TABM-543 | biostudies-other

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