Epigenetic profiling of docetaxel resistance in Breast Cancer
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA433090 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Illumina Infinium MethylationEPIC Beadchip was used to obtain DNA methylation profiles across 850000 CpGsites in nine different breast cancer PDX models. Docetaxel resistant and residual disease PDX models were also analyzed
2019-07-18 | GSE110184 | GEO
Project description:Breast cancer is the most common type of malignant tumour among women globally, with a major cause of cancer-related mortality worldwide. Chemoresistance presents a significant challenge in breast cancer therapy and serves as the primary factor contributing to tumour recurrence and metastasis. At present, there is a paucity of effective predictive strategies in this field. In this study, we successfully established patient-derived primary cancer cell lines (PCCL) from four patients with HR+/HER2- breast cancer (Luminal B, HER2 non-amplified) using primary cell culture technology. The retention of the original tumour's pathological characteristics and drug response heterogeneity was confirmed. The aim was to delve into the mechanisms and predictive models underlying chemotherapy resistance in HR+/HER2- breast cancer. Our investigation revealed varying sensitivities of PCCL to taxanes, including docetaxel. Through RNA sequencing and protein-protein interaction (PPI) network analysis, we discovered that the COL1A2 gene is significantly overexpressed in HR+/HER2- breast cancer patients exhibiting docetaxel resistance. Notably, this overexpression shows a negative correlation with the patients' pathological complete response rate (pCR) and recurrence-free survival (RFS). In functional assays, higher COL1A2 expression correlated with diminished docetaxel sensitivity in HR+/HER2-negative breast cancer cells. These findings are consistent with the imaging assessments and postoperative pathological outcomes of patients who underwent neoadjuvant therapy (AC-T regimen). These findings suggest that COL1A2 is associated with reduced chemotherapy sensitivity in HR+/HER2- breast cancer and may serve as a candidate biomarker to guide neoadjuvant taxane selection. Overall, this study provides a novel theoretical foundation for selecting neoadjuvant chemotherapy drugs for advanced breast cancer patients.
2026-02-18 | GSE319840 | GEO
Project description:Resistance to neoadjuvant chemotherapy in HR+/HER2- breast cancers is increasingly recognized as a consequence of tumor cell plasticity rather than fixed genetic alterations. Large-scale genomic analyses comparing tumors before and after chemotherapy have failed to identify recurrent mutations that consistently account for treatment failure. Instead, resistance is thought to arise predominantly through non-genetic, adaptive mechanisms, including the acquisition of gene expression changes that allow cancer cells to survive chemotherapy-induced stress and later re-enter proliferative programs.To uncover transcriptional adaptations to docetaxel, a chemotherapeutic agent used in the NAC clinical setting, we performed bulk RNA-sequencing on parental and docetaxel-resistant MCF-7 cells.
2026-07-14 | GSE327278 | GEO
Project description:Among microtubule-targeting agents, docetaxel has received recent interest owing to its good therapeutic index. Clinical trials have underlined its potential for the treatment of advanced breast cancer, although little is known about its molecular mode of action in this context. We characterized the molecular changes induced by docetaxel in two well-known human breast carcinoma cell lines. Two mechanisms of action according to drug concentration were suggested by a biphasic sensitivity curve, and were further validated by cell morphology, cell cycle and cell death changes. Two to four nanomolar docetaxel induced aberrant mitosis followed by late necrosis, and 100 nM docetaxel induced mitotic arrest followed by apoptosis. Passing through mitosis phase was a requirement for hypodiploidy to occur, as shown by functional studies in synchronized cells and by combining docetaxel with the proteasome inhibitor MG132. Transcriptional profiling showed differences according to cell line and docetaxel concentration, with cell cycle, cell death and structural genes commonly regulated in both cell lines. Although p53 targets were mainly induced with low concentration of drug in MCF7 cells, its relevance in the dual mechanism of docetaxel cytotoxicity was ruled out by using an isogenic shp53 cell line. Many of the genes shown in this study may contribute to the dual mechanism by which docetaxel inhibits the growth of breast cancer cells at different concentrations. These findings provide a basis for rationally enhancing docetaxel therapy, considering lower concentrations, and better drug combinations. Keywords: Dose-response analysis
2007-02-09 | GSE5149 | GEO
Project description:Gene expression profiles of human breast cancer tissues from 100 different patients treated with primary systemic chemotherapy (Gemcitabine, Epirubicin and Docetaxel) Keywords: expression profiling
2006-01-21 | GSE4056 | GEO
Project description:The majority of prostate cancer (PCa) patients treated with docetaxel develop resistance to it. In order to better understand the mechanism behind the acquisition of resistance, we conducted single cell total RNA sequencing (sctotal RNA-seq) of docetaxel sensitive and resistant variants of DU145 and PC3 PCa cell lines. Overall, sensitive and resistant cells clustered separately. However, for both cell lines we identified rare sensitive cells that clustered with the resistant cells indicating resistant cells pre-exist in the sensitive population. Differential gene expression analysis between resistant and sensitive cells revealed 182 differentially expressed genes common to both PCa cell lines. A subset of these genes gave a gene expression profile in the resistant-like sensitive cells similar to the resistant cells. Exploration for functional gene pathways identified 218 common pathways between the two cell lines. Protein ubiquitination was the most differentially regulated pathway and was enriched in the resistant cells. Transcriptional regulator analysis identified potential 321 regulators across both cell lines. One of the top regulators identified was nuclear protein 1 (NUPR1). In contrast to the single cell analysis, bulk analysis of the cells did not reveal NUPR1 as a promising candidate. Knockdown and overexpression of NUPR1 in the PCa cells demonstrated that NUPR1 confers docetaxel resistance in both cell lines. Collectively, these data demonstrate the utility of sctotal RNA-seq to identify regulators of drug resistance. Furthermore, NUPR1 was identified as a mediator of PCa drug resistance, which provides the rationale to explore NUPR1 and its target genes to for reversal of docetaxel resistance.
2020-09-01 | GSE140440 | GEO
Project description:Prostate cancer C4-2B cells were cultured in docetaxel in a dose-escalation manner. After nine months selection, cells were able to divide freely in 5 nM docetaxel, with a specific sets of genes been deregulated. We performed global gene expression analysis by cDNA microarrays to identify genes responsible for docetaxel resistance in TaxR cells. Docetaxel resistant TaxR cells were selected from C4-2B cells during long time docetaxel treatment. Genes responsible for docetaxel resistance were identified using C4-2B vs. TaxR RNA extraction and hybridization on Affymetrix microarrays.
2013-08-01 | E-GEOD-47040 | biostudies-arrayexpress
Project description:Docetaxel is the standard first line therapy for hormone-refractory prostate cancer patients. Here we generated models of Docetaxel resistance in prostate cancer cells to study the molecular pathways that drive the acquisition of resistance to this therapy. We used microarrays to detail the global program of gene expression underlying the acquisition of Docetaxel resistance in prostate cancer cells. Parental Docetaxel-sensitive prostate cancer cell lines (DU145 and 22Rv1) and selected Docetaxel-resistant cells (DU145-DR and 22Rv1-DR) were harvested for RNA extraction and hybridization on Affymetrix microarrays. Samples were analyzed in triplicates in order to increase the resolution of expression profiles.
2012-10-02 | E-GEOD-36135 | biostudies-arrayexpress
Project description:Docetaxel is the standard first line therapy for hormone-refractory prostate cancer patients. Here we generated models of Docetaxel resistance in prostate cancer cells to study the molecular pathways that drive the acquisition of resistance to this therapy. We used microarrays to detail the global program of gene expression underlying the acquisition of Docetaxel resistance in prostate cancer cells.
2012-10-02 | GSE36135 | GEO
Project description:Overcoming drug resistance is critical increasing the survival rate for prostate cancer (PCa). In this study, we modeled docetaxel resistance using two PCa cell lines, DU145 and PC3. We conducted both single cell and bulk RNA sequencing. We constructed a transcription factor (TF) network for the docetaxel sensitive and resistant variants for all cell lines and sequencing methods resulting in 8 networks. We identified shared edges and nodes that represent a shared TF network for PCa that modeled the changes after acquiring drug resistance. Using this shared TF network, we identified drivers of the resistant phenotype. Interestingly, the network constructed from the bulk sequencing dataset revealed different TF drivers of resistance compared with the network constructed from the single cells. We validated the results constructed from the single cells to demonstrate the validity of the single cell sequenced TF network. We targeted GABPA (only identified in the single cell constructed network) and successfully re-sensitized both cell lines to docetaxel treatment. Additionally, we conducted connectivity map analysis to identify potential drugs that disrupt the resistant networks. We identified trichostatin A as a potential combination treatment using the single cell sequenced network. Combination treatment of trichostatin A and docetaxel, both in vitro and in vivo PCa models decreased tumor growth. These results suggest by analyzing a population of resistant cells, identification of drivers and novel treatments is possible.
2023-04-01 | GSE149681 | GEO