Expression data from primary breast tumors, M0 patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE82172 | GEO | 2017/06/09
SECONDARY ACCESSION(S): PRJNA324253
REPOSITORIES: GEO
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Project description:Expression data were used to predict the activity status of diverse pathways, which were compared to Tamoxifen response 20 M1 breast cancer patients were evaluated for the activity of transcriptomic pathways.
2017-06-09 | GSE82171 | GEO
Project description:In this study, we used human THP-1-derived macrophages as an immune cell model, and systematically performed glycoproteomics of three subtypes of macrophages by StrucGP.To study the N‑Glycoproteomic of them, the intact glycopeptides were first enriched and identified using triplicate mass spectrometry (MS)-based glycoproteomic approaches, then StrucGP was used for subsequent analysis. In total three subtypes of macrophages, these intact glycopeptides consist of 253 N-linked glycan structures at 652 unique glycosites from 372 N-glycoproteins, along with their PSM information. A total of 135, 163, and 201 N-glycan structures were identified from M0, M1, and M2 macrophages, respectively.
2023-10-19 | PXD030277 | Pride
Project description:Tamoxifen, a small molecule inhibitor that binds the Estrogen Receptor alpha (ERα), blocks breast cancer progression while increasing the risk for endometrial cancer. In this study, we assessed genome-wide ERα-chromatin interactions in surgical specimens of endometrial tumors from patients who were previously treated for breast cancer with tamoxifen, and endometrial tumors from patients who were treated without tamoxifen. We compared ERα and signal at differential ERα sites in endometrial tumors of nine patients who received tamoxifen with endometrial tumors with six patients who never used tamoxifen. In addition, we performed H3K27ac (a marker for activity) ChIPs on the above mentioned endometrial tumors, and assed this signal at differential ERα sites. Compared to endometrial tumors of non-users, tamoxifen-associated endometrial tumors exposed higher H3K27ac intensities at ERα sites that are enriched in tamoxifen-associated endometrial tumors. Four tamoxifen-associated endometrial tumors that we used in our analysis have been previously published as Tumor A, B, D, and E in GSE81213.
2017-03-07 | GSE94523 | GEO
Project description:Tamoxifen, a small molecule inhibitor that binds the Estrogen Receptor alpha (ERα), blocks breast cancer progression while increasing the risk for endometrial cancer. In this study, we assessed genome-wide ERα-chromatin interactions in surgical specimens of endometrial tumors from patients who were previously treated for breast cancer with tamoxifen, and endometrial tumors from patients who were treated without tamoxifen. We compared ERα and signal at differential ERα sites in endometrial tumors of nine patients who received tamoxifen with endometrial tumors with six patients who never used tamoxifen. In addition, we performed H3K27ac (a marker for activity) ChIPs on the above mentioned endometrial tumors, and assed this signal at differential ERα sites. Compared to endometrial tumors of non-users, tamoxifen-associated endometrial tumors exposed higher H3K27ac intensities at ERα sites that are enriched in tamoxifen-associated endometrial tumors. Four tamoxifen-associated endometrial tumors that we used in our analysis have been previously published as Tumor A, B, D, and E in GSE81213.
2017-03-06 | GSE94031 | 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: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: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
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
Project description:Majority of breast cancer specific deaths in women with ERα (+) tumor occur due to metastases that are resistant to endocrine therapy. There is a critical need for novel therapeutic approaches to resensitize recurrent ERα (+) tumors to endocrine therapies. The objective of this study was to elucidate mechanisms of improved effectiveness of combined targeting of ERα and XPO1, a nuclear transport protein in overcoming endocrine resistance. Selinexor (SXR), an XPO1 antagonist, has been evaluated in multiple later stage clinical trials in patients with relapsed and /or refractory hematological and solid tumor malignancies. Using human phosphokinase array to profile kinase signaling pathways, we found that 4-OH Tamoxifen, SXR or their combination induced differential Akt phosphorylation profiles, changing the phosphorylation status and activity of the kinase. Also, our RNA sequencing data indicated that 4-OH Tamoxifen+SXR combination treatment causes gene expression changes distinct from 4-OH Tamoxifen and SXR treatments alone in tamoxifen-resistant cell lines. Since we observed dramatic changes in Akt activity and we saw a differential gene expression pattern with individual and combined 4-OH Tamoxifen and SXR treatments, we hypothesized that metabolic profile of breast cancer cells would change in the presence of 4-OH Tamoxifen and SXR. Using Seahorse metabolic profiler and cell viability experiments in limited media conditions, we showed that tamoxifen resistant cells were more dependent on mitochondria for energy production. Their glucose and fatty acid dependency decreased in the presence of SXR and cells were more dependent on glutamine as the mitochondrial fuel source. We demonstrated that combined targeting of XPO1 and ERα rewires metabolic pathways and shuts down both glycolytic and mitochondrial pathways that would eventually lead to autophagy. Remodelling metabolic pathways to regenerate new vulnerabilities in endocrine resistant breast tumors is novel, and given the need for better strategies for improving therapy response of relapsed ERα (+) tumors, our findings show great promise for uncovering the role of ERα-XPO1 crosstalk plays in reducing cancer recurrences.
2019-05-26 | GSE112883 | GEO
Project description:We used a mouse expressing three alleles 1) KitV558Delta/+ activating allele that develop GIST-like tumors in the cecum, 2) Etv1 flox/flox conditional knockout allele and 3) Rosa26-CreERT2 tamoxifen activated Cre allele. Mice were treated with either Tamoxifen (to delete Etv1) or corn oil (control). Cecal tumors were isolated for gene expression profiling by RNA-Seq.
2015-01-01 | GSE64608 | GEO