Tamoxifen Response at Single Cell Resolution in Estrogen Receptor Positive Primary Human Breast Tumors
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PROVIDER: PRJNA928555 | ENA |
REPOSITORIES: ENA
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Project description:Tamoxifen Response at Single Cell Resolution in Estrogen Receptor Positive Primary Human Breast Tumors
| PRJNA928554 | ENA
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
Project description:Adjuvant tamoxifen is a valid treatment option for women with estrogen receptor (ER)-positive breast cancer. However, up to 40% of patients experience distant or local recurrence or die. MicroRNAs have been suggested to be important prognosticators in breast cancer. This study aims to identify microRNAs with the potential to predict tamoxifen response. We performed a global microRNA screen in primary tumours of six matched pairs of postmenopausal, ER-positive breast cancer patients treated with tamoxifen, who were either recurrence free or had developed a recurrence. Patients were treated at the Robert Bosch Hospital, Stuttgart, Germany, between 1986 and 2005.
2014-07-01 | GSE46823 | GEO
Project description: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.
2015-08-21 | PXD000484 | Pride
Project description:Adjuvant tamoxifen is a valid treatment option for women with estrogen receptor (ER)-positive breast cancer. However, up to 40% of patients experience distant or local recurrence or die. MicroRNAs have been suggested to be important prognosticators in breast cancer. This study aims to identify microRNAs with the potential to predict tamoxifen response. We performed a global microRNA screen in primary tumours of six matched pairs of postmenopausal, ER-positive breast cancer patients treated with tamoxifen, who were either recurrence free or had developed a recurrence. Patients were treated at the Robert Bosch Hospital, Stuttgart, Germany, between 1986 and 2005. Total RNA from FFPE tissue from 12 postmenopausal patients with ER-positive breast cancer (6 patients with and 6 patients without recurrence) was extracted. Hybridisation of biotin-labelled RNA was performed on Affymetrix GeneChip miRNA_2.0 Arrays.
2014-07-01 | E-GEOD-46823 | biostudies-arrayexpress
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
Project description:In ER+/HER2- 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+ 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.
| S-EPMC10103953 | biostudies-literature
Project description:PurposeIn estrogen receptor-positive (ER+)/HER2- breast cancer, multiple measures of intratumor heterogeneity are associated with a worse response to endocrine therapy. We sought to develop a novel experimental model to measure heterogeneity in response to tamoxifen treatment in primary breast tumors.Experimental designTo investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live normal breast specimens and human tumors immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. Live primary cell suspensions were treated ex vivo with tamoxifen (10 μmol/L) or control media for 12 hours, and single-cell RNA libraries were generated using the 10X Genomics droplet-based kit.ResultsIn total, we obtained and processed normal breast tissue from two women undergoing reduction mammoplasty and tumor tissue from 10 women with ER+/HER2- invasive breast carcinoma. 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 resistant subpopulations predict poor outcomes in two large cohorts of ER+ breast cancer patients and are enriched in endocrine therapy-resistant tumors.ConclusionsThis novel ex vivo model system now provides the foundation to define responsive and resistant subpopulations within heterogeneous human tumors, which can be used to develop precise single cell-based predictors of response to therapy and to identify genes and pathways driving therapeutic resistance.
| S-EPMC10690085 | biostudies-literature
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
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. Keywords: disease state analysis
2008-05-07 | GSE9195 | GEO