Effect of aromatase inhibitor (AI) treatment on gene expression of breast cancer [tissueseq]
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA849597 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19664251_1.fastq.gz | Fastqsanger.gz | |||
| SRR19664251_2.fastq.gz | Fastqsanger.gz | |||
| SRR19664252_1.fastq.gz | Fastqsanger.gz | |||
| SRR19664252_2.fastq.gz | Fastqsanger.gz | |||
| SRR19664253_1.fastq.gz | Fastqsanger.gz |
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Project description:To investigate the expression profiling of estrogen receptor positive breast cancer after AI treatment, we obtained tumor samples from breast cancer patients receiving adjuvant AI treatment, then performed RNA sequencing and gene expression profiling analysis for 14 different breast tumor samples.
2022-10-11 | GSE206199 | GEO
Project description:To identify in clinical breast cancer those genes and pathways most associated with resistance to aromatase inhibitors by examining the global transcriptional effects of aromatase inhibitor (AI) treatment. Analysis of gene-expression measured in core-cut biopsies at baseline and surgery from patients received 2-week’s presurgical AI revealed: i) the molecular response to AI treatment varies greatly between patients, consistent with the variable clinical benefit from AI treatment; ii) higher baseline expression of an inflammatory signature is associated with poor antiproliferative response, and should be assessed further as a novel biomarker and potential target for AI-treated patients.
2020-06-29 | GSE153470 | GEO
Project description:Obesity represents a risk factor for breast cancer development and therapy resistance, but the molecular players underling these links are unclear. Here, we identify a role for the obesity-cytokine leptin in sustaining aromatase inhibitor (AI) resistant growth and progression in breast cancer. Using as a cellular model MCF-7 breast cancer cells surviving long-term to the AI treatment Anastrozole (AnaR) and Ana-sensitive counterparts, we found that AnaR cells expressed higher levels of leptin and its receptors (ObR) along with a constitutive activation of downstream effectors. Accordingly, leptin signaling inhibition reduced only AnaR cell growth and motility, highlighting the existence of an autocrine loop in mechanisms governing drug-resistant phenotype. In agreement with ObR overexpression, increasing doses of leptin were able to stimulate at a greater extent growth and migration in AnaR than sensitive cells. Moreover, leptin contributed to an enhanced crosstalk between AnaR cells and macrophages within tumor microenvironment. Indeed, AnaR through leptin secretion modulated macrophage profiles and increased macrophage motility through CXCR4 signaling, as evidenced by RNA-sequencing, realtime-PCR and immunoblotting. Reciprocally, activated macrophages increased AnaR cell growth and motility in coculture systems.
2022-03-04 | E-MTAB-8843 | biostudies-arrayexpress
Project description:Endocrine therapy reduces breast cancer mortality by 40%; but resistance remains a major clinical problem. Identification of gene signatures associated with resistance during endocrine treatment should enable rational therapeutic choices to be made to combat this in individual patients. Here we present an in-depth analysis of global gene-expression that was measured on pairs of core-cut biopsies taken at baseline and at surgery from 254 patients with ER-positive primary breast cancer randomised to receive 2-week’s presurgical AI (n=198) or no presurgical treatment (Control n=56) in the POETIC trial, using changes-in and residual-of the proliferation marker, Ki67 as end-points, to investigate the impact of aromatase inhibitor (AI) therapy on gene expression and identify gene modules representing key biological pathways that relate to early AI-therapy resistance. Our study revealed a high degree of heterogeneity in adaptive mechanisms after as little as 2-weeks’ AI-therapy, however, all appear to converge on cell cycle regulation. Our data support the evaluation of whether an E2F signatures after short-term exposure to AI may identify those patients most likely to benefit from the early addition of CDK4/6 inhibitors.
2020-02-24 | GSE126870 | GEO
Project description:Understanding the complex molecular mechanisms underlying resistance to endocrine therapy is a major challenge in the treatment of estrogen receptor-positive (ER+) breast cancers. We have previously demonstrated that glial cell line-derived neurotrophic factor (GDNF) signaling via the receptor tyrosine kinase RET promotes estrogen independent activation of ER. Here we have addressed the relevance of GDNF-RET signaling in response to aromatase inhibitor treatment and explored the efficacy of using RET inhibitors in breast cancer models of aromatase inhibitor response and resistance. A GDNF-response gene set, identified from gene expression profiling, was demonstrated to be an independent prognostic marker of poor patient outcome and, importantly, to be predictive of poor response to aromatase inhibitor treatment and development of resistance. The relevance of these findings was validated first by demonstrating an association of RET protein expression in an independent cohort of aromatase inhibitor resistant patient samples. Second, in in vitro models, GDNF-mediated RET signaling was demonstrated to enhance the survival of aromatase inhibitor resistant cells and to increase resistance in aromatase inhibitor sensitive cells. These effects could be reversed by targeting GDNF/RET signaling with the RET selective inhibitor NVP-BBT594 thus identifying GDNF-RET signaling as a potential therapeutic target, particularly in breast cancers resistant to aromatase inhibitors.<br>MCF7 cells were E2-deprived by culturing in phenol red-free RPMI 1640 supplemented with 10% DCC for 3 days and then serum-starved overnight in the presence or absence of fulvestrant (ICI182,780) (100 nM). The following day, cells were treated with GDNF (20 ng/ml) for 0, 4, 8, 24 and 48 hours in the presence or absence of fulvestrant (ICI182,780) (100 nM).
2013-01-17 | E-MEXP-3662 | biostudies-arrayexpress
Project description:Resistance to endocrine therapy agents has presented a clinical obstacle in the treatment of hormone-dependent breast cancer. Our laboratory has initiated a study of microRNA regulation of signaling pathways that may result in breast cancer progression on aromatase inhibitors (AI). Microarray analysis of microRNA expression identified 115 significantly regulated microRNAs, of which 49 microRNAs were believed to be hormone-responsive. Within the AI-resistant cells, microRNAs were differentially expressed between the steroidal and non-steroidal AI-resistant lines. Also, a group of microRNAs were inversely expressed in the AI-resistant lines versus LTEDaro and tamoxifen-resistant. We focused our work on hsa-miR-128a which was hormone-responsive and up-regulated in the letrozole-resistant cell lines. Human miR-128a was shown to negatively target TGFBRI protein expression by binding to the 3âUTR region of the gene. Loss of TGFBRI resulted in compromised sensitivity to the growth inhibitory effects of TGFB in the letrozole-resistant lines. Inhibition of endogenous miR-128a resulted in re-sensitization of the letrozole-resistant lines to TGFB growth inhibitory effects. This data suggests that the hormone-responsive miR-128a can modulate TGFB signaling and survival of the letrozole-resistant cell lines. To our knowledge, this is the first study to address the role of microRNA regulation as well as TGFB signaling in AI-resistant breast cancer cell lines. We believe that in addition to estrogen-modulation of gene expression, hormone-regulated microRNAs may provide an additional level of post-transcriptional regulation of signaling pathways critically involved in breast cancer progression and AI-resistance. To look at microRNA expression profiles of breast cancer cell lines derived from MCF-7 cells that are resistant to endocrine therapy agents. MCF-7 cells that overexpress aromatase (MCF-7aro) were cultured long-term in the presence of endocrine therapy agents until cells acquired resistance. Three different aromatase inhibitors (letrozole, anastrozole or exemestane) were used, as well as the ER antagonist tamoxifen, or the hormone-free long-term estrogen deprived cells (LTED). Three replicates of the control cells (MCF-7aro) and all resistant cells were used for microarray experiments. Total of 23 samples were analyzed by microarray.
2010-05-16 | E-GEOD-17775 | biostudies-arrayexpress
Project description:Resistance to endocrine therapy agents has presented a clinical obstacle in the treatment of hormone-dependent breast cancer. Our laboratory has initiated a study of microRNA regulation of signaling pathways that may result in breast cancer progression on aromatase inhibitors (AI). Microarray analysis of microRNA expression identified 115 significantly regulated microRNAs, of which 49 microRNAs were believed to be hormone-responsive. Within the AI-resistant cells, microRNAs were differentially expressed between the steroidal and non-steroidal AI-resistant lines. Also, a group of microRNAs were inversely expressed in the AI-resistant lines versus LTEDaro and tamoxifen-resistant. We focused our work on hsa-miR-128a which was hormone-responsive and up-regulated in the letrozole-resistant cell lines. Human miR-128a was shown to negatively target TGFBRI protein expression by binding to the 3’UTR region of the gene. Loss of TGFBRI resulted in compromised sensitivity to the growth inhibitory effects of TGFB in the letrozole-resistant lines. Inhibition of endogenous miR-128a resulted in re-sensitization of the letrozole-resistant lines to TGFB growth inhibitory effects. This data suggests that the hormone-responsive miR-128a can modulate TGFB signaling and survival of the letrozole-resistant cell lines. To our knowledge, this is the first study to address the role of microRNA regulation as well as TGFB signaling in AI-resistant breast cancer cell lines. We believe that in addition to estrogen-modulation of gene expression, hormone-regulated microRNAs may provide an additional level of post-transcriptional regulation of signaling pathways critically involved in breast cancer progression and AI-resistance.
2010-01-01 | GSE17775 | GEO
Project description:The goal of the experiment is untargeted metabolomic and shotgun lipidomic profiling of serum samples collected from 50 patients before patients initiated therapy with an aromatase inhibitor and again after 3 months of aromatase inhibitor therapy. Half of the patients discontinued treatment within 6 months because of development of arthralgias during therapy and half remained on therapy for at least 24 months without development of significant arthralgias. We plan to analyse effects of AI therapy on metabolomic and lipidomic profiles, and to investigate associations between changes in profiles and development of symptoms.
2017-06-19 | ST000695 | MetabolomicsWorkbench
Project description:MCF-7aro cells were used to generate a cell culture model system that is resistant to 3 aromatase inhibitors (AIs), letrozole, anastrozole and exemestane. For comparison, the MCF-7aro cells were also used to generate the tamoxifen-resistant cells as well as long-term estrogen deprived, LTEDaro. Affymetrix microarray analysis was performed to determine changes in gene expression that are unique to AI-resistance. Keywords: cell lines, aromatase inhibitor resistance, tamoxifen resistance
2008-03-22 | GSE10911 | GEO
Project description:<p>Highly variable outcomes are observed in patients with estrogen receptor positive (ER+) breast cancer who undergo preoperative estrogen deprivation therapy with aromatase inhibitors (AI). In this study, 46 baseline tumor and normal genomes and 31 baseline tumor/normal exomes of participants selected from two clinical trials of neoadjuvant AI therapy on ER+ breast cancer were sequenced to identify somatic alterations that correlate with response to AI, to screen for therapeutic targets and to elucidate the genetic landscape of ER+ breast cancer. From the same set of patients we later performed deep genomic characterization of a subset of matched primary tumors after four months of AI therapy, generating comprehensive information about the range of changes that occur when ER+ breast cancers are subjected to estrogen deprivation. This data includes whole genome sequence and transcriptome data. To better understand tumor heterogeneity and the evolution of resistance to estrogen-deprivation therapy, a subset of these tumours, along with 38 additional cases were sequenced to greater depth using targeted capture with a gene panel.</p>
| phs000472 | dbGaP