Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA90701 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Macrophages are frequently the most abundant immune cells in murine and human cancers. Studies in various transgenic mouse tumor models have revealed pro-tumor functions of tumor-associated macrophages (TAMs), but despite their association with poor clinical outcome in human patients, molecular signatures for the prediction of clinical outcome in humans are still missingbeen demonstrated. Here we generated molecular signatures from F4/80+CD11b+ TAMs from two transgenic breast cancer models: K14cre;Cdh1flox/flox;Trp53flox/flox (KEP), which resembles human invasive lobular carcinoma (ILC) and MMTV-NeuT (NeuT), which resembles HER2-overexpressing breast cancer. Determination of truly specific TAM transcriptome signatures in breast cancer required relationship analysis with healthy mammary gland tissue macrophages (MTMs), since comparison with macrophages from tissues overestimated TAM-specific gene expression. Furthermore, translation of the TAM signatures to outcome prediction in patients required consideration of the breast cancer subtype. TAM signatures derived from the KEP, but not the NeuT model reliably predicted outcome in ILC patients. Collectively, we show that a transgenic mouse tumor model can be utilized to derive a TAM-based signature for human breast cancer outcome prediction and provide a generalizable strategy for determining and applying specific molecular signatures of immune cells to, in principle, any cancer provided the murine model reflects the human disease.
2019-10-30 | GSE126268 | GEO
Project description:Global gene expression profiling has demonstrated that the predominant cellular response to a range of toxicants is a general stress response. This stereotyped environmental stress response commonly includes repression of protein synthesis and cell cycle regulated genes and induction of DNA damage and oxidative stress responsive genes. Our laboratory has recently characterized the general stress response of breast cell lines derived from basal-like and luminal epithelium following treatment with doxorubicin (DOX) or 5-fluorouracil (5FU) and showed that each cell type has a distinct response. However, we expected that some of the expression changes induced by DOX and 5FU were unique to each compound and might reflect the underlying mechanisms of action of these agents. Thus, we employed supervised analyses (Significance Analysis of Microarrays) to identify genes that showed differential expression between DOX- and 5FU-treated cell lines. We then used cross-validation analyses and identified genes that afforded high predictive accuracy in classifying samples into the two treatment classes. To test whether these gene lists had good predictive accuracy in an independent data set, we treated our panel of cell lines with etoposide, a compound that is mechanistically similar to DOX. We demonstrated that using expression patterns of 100 genes, we were able to obtain 100% predictive accuracy in classifying the etoposide samples as being more similar in expression to DOX- than 5FU-treated samples. These analyses also showed that toxicant specific gene expression patterns, similar to general stress responses, vary according to cell type. Keywords = breast cancer Keywords = class prediction Keywords = doxorubicin Keywords = etoposide Keywords = 5-fluorouricil Keywords = gene expression Keywords = microarrays Keywords: dose response
2004-09-28 | GSE1647 | GEO
Project description:CDK4/6 inhibitor, Palbociclib, has shown a high success in breast cancer subtypes however it is often accompanied by a dependency on mutation status of cell lines. Consequently, there has been speculation on the breast cancer subtypes which should be offered treatment with specific CDK4/6 inhibitors and the response that can be expected. A common observation has been the induction of a cell programme known as "senescence" whereby cells experience a complete halt in mitosis, however, remaining metabolically active. Therapy-induced senescence markers and its effect on the tumour microenvironment as well as the diversity of this cell state remain unappreciated. In the following proteomics, phosphoproteomics and secretome datasets we focus on MDA-MB-231 cells, a triple negative cell line, to better understand the senescence-like cell state which arises after treatment. Ultimately, the dataset encompasses the population that arises upon Palbociclib treatment and highlights potential signatures and biomarkers of the cell state which could provide information on the use of CDK4/6 inhibitors in triple negative breast cancer subtypes.
2022-01-28 | PXD030407 | Pride
Project description:To determine toxicant specific effects of Ordnance Related Compound (ORC) exposure we performed microarray hybridizations with RNA isolated from Daphnia magna following different ORC exposures at the 1/10 LC50. The gene expression profiles revealed toxicant specific gene expression profiles allowed for the identification of specific biomarkers of exposure. Keywords: ecotoxicogenomic exposure study
2008-10-16 | GSE13169 | GEO
Project description:Breast cancer accounts for roughly 30% of all cancers in women worldwide, has a 15% death rate, and incidence rates are increasing at a rate of about 0.5% per year. Breast cancer comprises a heterogeneous group of tumor subtypes, whether defined by the histopathology of the primary tumor, the expression pattern of hormone receptors (estrogen and/or progesterone receptors; ER/PR) and epidermal growth factor receptor 2 (HER2), genetic alterations of transcriptomic traits. These patient-to-patient differences (as known as �쁦ntertumoral heterogeneity��, largely affect patient prognosis and treatment options. Alongside intertumoral heterogeneity, many studies reported that breast cancers heterogeneous consisting of many different cells or subclones of which different gene expression profiles within a patient�셲 primary tumor and individual metastases. These differences within the tumor are referred to as intratumor heterogeneity, which is caused by a combination of extrinsic factors from the tumor microenvironment and intrinsic parameters including genetic, epigenetic and transcriptomic traits, ability of proliferation, migration and invasion, cell plasticity, and the extent of stemness. These heterogeneities endow tumors with multiple capabilities and biological characteristics, making them more prone to metastasis, recurrence, and drug resistance. To overcome these facing challenges, understanding the proteome mechanisms behind transcriptome profiling from the aspect of treatment can help to improve resistance to cancer therapy. Recent proteomics technologies based on mass spectrometry enable an unbiased investigation of drug-induced changes in protein abundance and post-translational modifications. Several studies on resistance to chemotherapy have recently published data on mass spectrometry-based chemotherapeutic proteome profiling, which has the potential to discover molecular subtypes and related pathway features that may have been missed in prior transcriptome analyses. Nevertheless, few proteomics studies to date explore three types of drug-specific resistance of breast cancer signatures. In this study, we employed tandem mass tag (TMT) based proteomics technology to process the acquired mass spectrometry data to test the hypothesis that the chemotherapy in breast cancer cells may have distinct protein profiles that may result in their drug properties and new clinical implications. By unraveling the protein signatures across tamoxifen, doxorubicin, and paclitaxel and their relationship between drug-resistant cell lines and normal breast cancer cells, our study advances the understanding of drug-specific resistance and provides potential diagnostic and prognostic markers, as well as testable targets of therapy specific to breast cancer resistant cells.
2022-04-04 | PXD030881 | Pride
Project description:Paclitaxel is the most commonly used chemotherapeutic agent in breast cancer treatment. Notably, a comprehensive understanding of paclitaxel’s effects requires insight into the dose-specific activities of paclitaxel and their influence on the cancer cells and host microenvironment. The aim of our study is to reveal the gene transcriptional changes in response to low-Paclitaxel (PTX) treatment in breast cancer cells.
2016-06-01 | GSE82048 | GEO
Project description:Breast tumors are characterized into different subtypes based on their surface marker expression, which affects their prognosis and treatment. For example, triple negative breast cancer cells (ER-/PR-/Her2-) show reduced susceptibility towards radiotherapy and chemotherapeutic agents. Poly (ADP-ribose) polymerase (PARP) inhibitors have shown promising results in clinical trials, both as single agents and in combination with other chemotherapeutics, in several subtypes of breast cancer patients. PARP1 is involved in DNA repair, apoptosis, and transcriptional regulation and an understanding of the effects of PARP inhibitors, specifically on metabolism, is currently lacking. Here, we have used NMR-based metabolomics to probe the cell line-specific effects of PARP inhibitor and radiation on metabolism in three distinct breast cancer cell lines. Our data reveal several cell line independent metabolic changes upon PARP inhibition, including an increase in taurine. Pathway enrichment and topology analysis identified that nitrogen metabolism, glycine, serine and threonine metabolism, aminoacyl-tRNA biosynthesis and taurine and hypotaurine metabolism were enriched after PARP inhibition in the three breast cancer cell lines. We observed that the majority of metabolic changes due to radiation as well as PARP inhibition were cell line dependent, highlighting the need to understand how these treatments affect cancer cell response via changes in metabolism. Finally, we observed that both PARP inhibition and radiation induced a similar metabolic response in the HCC1937 (BRCA mutant cell line), but not in MCF-7 and MDAMB231 cells, suggesting that radiation and PARP inhibition share similar interactions with metabolic pathways in BRCA mutant cells. Our study emphasizes the importance of differences in metabolic responses to cancer treatments in different subtypes of cancers.
2016-11-07 | MTBLS337 | MetaboLights
Project description:Recently, expression profiling of breast carcinomas has revealed gene signatures that predict clinical outcome, and discerned prognostically relevant breast cancer subtypes. Measurement of the degree of genomic instability provides a very similar stratification of prognostic groups. We therefore hypothesized that these features are linked. We used gene expression profiling of 48 breast cancer specimens that profoundly differed in their degree of genomic instability and identified a set of 12 genes that defines the two groups. The biological and prognostic significance of this gene set was established through survival prediction in published datasets from patients with breast cancer. Of note, the gene expression signatures that define specific prognostic subtypes in other breast cancer datasets predicted genomic instability in our samples. This remarkable congruence suggests a biological dependency of poor-prognosis gene signatures, breast cancer subtypes, genomic instability, and clinical outcome. Keywords: disease state analysis 44 samples
2009-11-30 | E-GEOD-11901 | biostudies-arrayexpress
Project description:Breast cancer subtype-specific lncRNAs AL078604.2 and LINC01269 were knockdown in breast cancer cell lines LncRNA AL078604.2 was knockdown by an anti-AL076804.2 antisense oligonucleotides (ASOs) in triple-negative breast cancer cell lines MDA-MB-231 and MDA-MB-468 breast cancer cells. LncRNA LINC01269 was knockdown by an anti-LINC01269 ASOs in HER2+ SKBR3 breast cancer cells. To ensure the initial presence of AL078604.2 and LINC01269 in their respective cell lines, qPCR analysis was performed to confirm their expression levels prior to knockdown experiments. The effectiveness of knockdown was confirmed by qPCR analysis, which validated the reduction in AL078604.2 and LNC01269 expression in their corresponding cell lines following ASO treatment.
2023-12-13 | GSE235165 | GEO
Project description:Stromal and epithelial changes in breast cancer following endocrine treatment
| PRJNA252964 | ENA