Browse
Submit Data
Databases
API
Help

Dataset Information

432 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Discovery dataset on tamoxifen treated Estrogen Receptor (ER) positive breast cancer patients

ABSTRACT: 56 estrogen receptor positive breast cancer tissues from patients treated with tamoxifen upon recurrence (32 Good outcome vs 24 Poor outcome) have been microdissected to obtain a pure population of epithelial tumor cells. Breast tumor enriched tissues have been sonicated and proteins have been in-solution digested and analyzed via a LTQ-Orbitrap coupled online with a nano-LC system. Thermo output .RAW files were analyzed through MaxQuant (version 1.4.1.2) using the human proteome FASTA (version 2012-09, human canonical proteome) as search library.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Tommaso De Marchi

PROVIDER: PXD000484 | Pride | 2015-08-21

REPOSITORIES: Pride

ACCESS DATA

Json Xml

Publications

4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer.

De Marchi Tommaso T Liu Ning Qing NQ Stingl Cristoph C Timmermans Mieke A MA Smid Marcel M Look Maxime P MP Tjoa Mila M Braakman Rene B H RB Opdam Mark M Linn Sabine C SC Sweep Fred C G J FC Span Paul N PN Kliffen Mike M Luider Theo M TM Foekens John A JA Martens John W M JW Umar Arzu A

Molecular oncology 20150807 1

Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, ...[more]

PMID: 26285647

Similar Datasets

Validation dataset on tamoxifen treated Estrogen Receptor (ER) positive breast cancer patients

Project description:56 Estrogen Receptor Positive Breast cancer tissues coming from patients treated with tamoxifen upon recurrence (41 Good outcome vs 15 Poor outcome) have been microdissected to enrich for breast cancer tumor cells. Enriched tissue has been lysed and proteins digested and analyzed in an LTQ-Orbitrap coupled online with a Dionex nLC system. Thermo output .RAW files were analyzed through MaxQuant (version 1.4.1.2) using the human proteome FASTA (version 2012-09, human canonical proteome) as search library. LFQ parameters in MaxQuant have been enabled (Fast LFQ) and other settings have been kept as default.

2015-08-21 | PXD000485 | Pride

Transcription profiling of human estrogen receptor postive breast cancer samples treated with tamoxifen to predict prognosis

Project description:Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings. Results: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29-3.13; p=0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response. Conclusions: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen. Experiment Overall Design: dataset of microarray experiments from primary breast tumors of patients treated by Tamoxifen in adjuvant setting. No replicate, no reference sample.

2008-06-20 | E-GEOD-9195 | biostudies-arrayexpress

Novel estrogen and tamoxifen induced genes

Project description:The breast cancer promoting effects of estrogen and the chemopreventive effects of tamoxifen are thought to be mediated by the estrogen receptor, a ligand-dependent transcription factor. Therefore, comprehensive analysis of gene expression profiles following estrogen or tamoxifen treatment may help us better understand the role estrogen plays in tumorigenesis. We utilized SAGE (Serial Analysis of Gene Expression) technology to identify genes regulated by estrogen and tamoxifen in the ZR75-1 estrogen dependent breast cancer cell line. In this manner we have identified several genes that were regulated by estrogen or tamoxifen. Here we report the identification and initial characterization of EIT-6 (Estrogen Induced Tag-6), a novel nuclear protein and a new member of the evolutionarily conserved SM-20 family of growth regulatory immediate-early genes. EIT-6 appears to be a direct transcriptional target of the estrogen receptor and constitutive expression of EIT-6 promotes colony growth in human breast cancer cells. These data indicate that EIT-6 may play a role in estrogen induced cell growth. Keywords: other

2003-07-16 | GSE507 | GEO

Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen

2008-05-07 | GSE9195 | GEO

Novel estrogen and tamoxifen induced genes

2003-07-16 | E-GEOD-507 | biostudies-arrayexpress

Global mapping of estrogen receptor and histone modifications in breast tumor samples uncovers distinct patterns for aromatase inhibitor resistance

Project description:ChIP-seq on primary breast cancer tumor samples for Era, H3K4me3, H3K27me3. Patients had a poor or good outcome after aromatase inhibitor treatment. Differential binding patterns between good and poor outcome patients were identified for each marker, predicting response to treatment comparing ER, H3K4me3 and H3K27me3 patterns between two breast cancer patient populations

2013-12-05 | E-GEOD-40867 | biostudies-arrayexpress

Global mapping of estrogen receptor and histone modifications in breast tumor samples uncovers distinct patterns for aromatase inhibitor resistance

2013-12-05 | GSE40867 | GEO

Prognostic value of biomarkers EpCAM and B-crystallin is associated with lymphatic metastasis in breast cancer by iTRAQ analysis

Project description:Metastasis is responsible for the majority of deaths in a variety of cancer types, including breast cancer. Although several factors or biomarkers have been identified to predict the outcome of patients with breast cancer, few studies have been conducted to identify metastasis-associated biomarkers. Quantitative iTRAQ proteomics analysis was used to detect differentially expressed proteins between lymph node metastases and their paired primary tumor tissues from 23 patients with metastatic breast cancer. Immunohistochemistry was performed to validate the expression of two upregulated (EpCAM, FADD) and two downregulated (NDRG1, αB-crystallin) proteins in 190 paraffin-embedded tissue samples. These four proteins were further analyzed for their correlation with clinicopathological features in 190 breast cancer patients. We identified 637 differentially regulated proteins (397 upregulated and 240 downregulated) in lymph node metastases compared with their paired primary tumor tissues. Furthermore, bioinformatics analysis using GEO profiling confirmed the difference in the expression of EpCAM between metastases and primary tumors tissues. Two upregulated (EpCAM, FADD) and two downregulated (NDRG1, αB-crystallin) proteins were associated with the progression of breast cancer. Obviously, EpCAM plays a role in the metastasis of breast cancer cells to the lymph node. We further identified αB-crystallin as an independent biomarker to predict lymph node metastasis and the outcome of breast cancer patients.

2019-08-29 | PXD013931 | Pride

Tamoxifen Response at Single Cell Resolution in Estrogen Receptor Positive Primary Human Breast Tumors

Project description:In ER-positive, HER2-negative breast cancer, multiple measures of intra-tumor heterogeneity are associated with worse response to endocrine therapy. To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live human tumors and normal breast specimens immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from 3 distinct resistant subpopulations are prognostic in large cohorts of ER-positive breast cancer patients and enriched in endocrine therapy resistant tumors. This novel ex vivo model system now provides a foundation to define responsive and resistant sub-populations within heterogeneous tumors, to develop precise single cell-based predictors of response to therapy, and to identify genes and pathways driving resistance to therapy.

2023-10-19 | GSE245601 | GEO

Nuclear Estrogen Receptor alpha (ERα) interactome following estrogen and antiestrogen treatment.

Project description:The Estrogen Receptor alpha (ERα) controls key cellular functions in hormone responsive breast cancer by assembling in large functional multiprotein complexes. ERα ligands are classified as agonists and antagonist, according to the response they elicit, thus the molecular characterization of the of ERα nuclear iteractome composition following estrogen and antiestrogen stimulation whose is needed to understand their effects on estrogen target tissues, in particular breast cancer. To this aim interaction proteomics coupled to mass spectrometry (MS) was applied to map the ERα nuclear interacting partners in MCF7 breast cancer cell nuclei following estrogen and antiestrogen stimuli.

2020-09-02 | PXD018709 | Pride

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