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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of human breast cancer cell lines (23)

ABSTRACT: Transcriptional profiling was conducted on RNA from 23 breast cancer cell lines to identify genes whose expression level correlates with sensitivity of particular drug Experiment Overall Design: Baseline gene expression profiling was performed using 23 breast cancer cell lines to identify genomic signatures highly correlated with in vitro sensitivity to a particular drug

ORGANISM(S): Homo sapiens

SUBMITTER: Fei Huang

PROVIDER: E-GEOD-6569 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Identification of candidate molecular markers predicting sensitivity in solid tumors to dasatinib: rationale for patient selection.

Huang Fei F Reeves Karen K Han Xia X Fairchild Craig C Platero Suso S Wong Tai W TW Lee Francis F Shaw Peter P Clark Edwin E

Cancer research 20070301 5

Dasatinib is a multitargeted kinase inhibitor that was recently approved for the treatment of chronic myelogenous leukemia and Philadelphia chromosome-positive acute lymphoblastic leukemia with resistance or intolerance to prior therapy. It is also in clinical trials for treating patients with solid tumors. The identification of molecular markers predictive of response to dasatinib could assist in clinical development by selecting patients most likely to derive clinical benefit. Using baseline g ...[more]

PMID: 17332353

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Expression data from 23 breast cancer cell lines

Project description:Transcriptional profiling was conducted on RNA from 23 breast cancer cell lines to identify genes whose expression level correlates with sensitivity of particular drug Keywords: comparison of sensitive group versus resistant group of cell lines to particular drug

2007-03-05 | GSE6569 | GEO

IRSN-23 Prospective Analyses

Project description:PURPOSE: The IRSN-23 model uses DNA microarray analysis of tumor tissue to personalize patients into highly sensitive chemotherapy (Gp-R) or less sensitive (Gp-NR) based on the expression of immune-related genes. This study assessed the reproducibility of the IRSN-23 in prospective independent validation sets and investigated its clinical significance and impact on breast cancer subtype classification. METHODS: Tumour tissues were collected from 146 breast cancer patients undergoing preoperative chemotherapy (paclitaxel-FEC) ± trastuzumab in Osaka University Hospital (OUH). Patients were classified into Gp-R or Gp-NR using IRSN-23, and the model was examined for its ability to predict the pathological complete response (pCR). RESULTS: In the OUH prospective dataset, the pCR rate was significantly higher in the Gp-R group (29·3% (11/41)) than in the Gp-NR group (1·4% (1/71)) not using trastuzumab (P = 1·70E-5). CONCLUSION: This study provides prospective validation of the IRSN-23 in predicting chemotherapy efficacy, demonstrating a high degree of reproducibility.

2023-05-19 | GSE230881 | GEO

DECIPHERING THE SIGNALING NETWORK LANDSCAPE OF BREAST CANCER IMPROVES DRUG SENSITIVITY PREDICTION

Project description:Although genetic and epigenetic abnormalities in breast cancer have been extensively studied, it remains difficult to identify those patients who will respond to particular therapies. This is due in part to our lack of understanding of how the variability of cellular signaling affects drug sensitivity. Here, we used mass cytometry to characterize the single-cell signaling landscapes of 62 breast cancer cell lines and five lines from healthy tissue. We quantified 34 markers in each cell line upon stimulation by the growth factor EGF in the presence or absence of five kinase inhibitors. These data – on more than 80 million single cells from 4,000 conditions – were used to fit mechanistic signaling network models that provide unprecedented insights into the biological principles of how cancer cells process information. Our dynamic single-cell-based models more accurately predicted drug sensitivity than static bulk measurements for drugs targeting the PI3K-MTOR signaling pathway. Finally, we identified genomic features associated with drug sensitivity by using signaling phenotypes as proxies, including a missense mutation in DDIT3 predictive of PI3K-inhibition sensitivity. This provides proof of principle that single-cell measurements and modeling could inform matching of patients with appropriate treatments in the future.

2021-04-20 | PXD017199 | Pride

A phenotype-based model for rational selection of novel targeted therapies in treating aggressive breast cancer

Project description:Treating unselected cancer patients with new drugs dilutes proof of efficacy when only a fraction of patients respond to therapy. We conducted a meta-analysis on eight primary breast cancer microarray datasets representing diverse breast cancer phenotypes. We present a high-throughput protocol which incorporates drug sensitivity signatures to guide preclinical testing for effective therapeutic agents. Specifically, we focus on drug classes currently undergoing early phase clinical testing. Our genomic and experimental results suggest that the majority of basal-like breast cancers should respond to inhibitors of the phosphatidylinositol-3-kinase pathway, and that a relatively low toxicity histone deacetylase inhibitor, valproic acid, may target aggressive breast cancers. For a subset of drugs, prediction of sensitivity associates with tumor recurrence, suggesting clinical relevance. Preclinical studies using both cell lines and patient tumors grown in 3-dimensional in vitro and orthotopic in vivo preclinical models provide an efficient and highly relevant assessment of drug sensitivity in tumor phenotypes, and validate our genomic analyses. Together, our results show that high-throughput transcriptional profiling can significantly impact drug selection for breast cancer patients. Pre-identification of patient response may not only improve therapeutic response rates, it can also assist in quickly identifying the optimal inclusion criteria for clinical trials. Our model facilitates personalized drug therapy for cancer patients and may be generalized for study of drug efficacy in other diseases. Breast cancer pleural effusion samples from triple negative patients. Compared samples that are computationally predicted to be sensitive to valproic acid and those that are not predicted to be sensitive.

2011-06-01 | E-GEOD-18331 | biostudies-arrayexpress

CDK4 phosphorylation status and a linked gene expression profile predict sensitivity to Palbociclib [tumors]

Project description:Cyclin D-CDK4/6 are the first CDK complexes to be activated in G1 phase in response to oncogenic pathways. The specific CDK4/6 inhibitor PD0332991 (Palbociclib) was recently approved by the FDA to treat advanced ER+ breast tumors. Unfortunately, reliable predictive tools are lacking to identify potentially responsive or insensitive tumors. We have shown that the activating T172 phosphorylation of CDK4 is the central rate-limiting event that initiates the cell cycle decision and signals the presence of active CDK4. Here, we found that, in breast cancer cell lines, the CDK4 T172 phosphorylation best correlates with the sensitivity to PD0332991. Moreover, the modification profile of CDK4 differs among breast tumors and it associates with their subtypes and risk. A gene expression signature faithfully predicted CDK4 modification profiles in tumors and cell lines. This surrogate biomarker identifies tumors that are unlikely to respond to CDK4/6 inhibitors and could allow extending the indication of the drug to HER-2 positive and some basal-like tumors. Predictive tools to identify breast cancer patients sensitive to Pfizer's new drug targeting CDK4/6 are lacking. We correlated the sensitivity of breast cancer cell lines to the drug to their post-translational modification profile of CDK4 revealed by 2D SDS/poly-acrylamide gel electrophoresis followed by CDK4 immuno-detection and their gene expression profiles. we revealed that breast tumors display similar CDK4 post-translational modification profiles as cell lines and that a gene expression profile can be used to predict the CDK4 post-translational modification profile of a tumor or cell line and thereby its sensitivity to CDK4 inhibitor

2017-01-01 | GSE87007 | GEO

CDK4 phosphorylation status and a linked gene expression profile predict sensitivity to Palbociclib [lines]

2017-01-01 | GSE87006 | GEO

Prediction of drug sensitivity

Project description:Tumor cell lines and drug-resistant counterparts. These data support the publication Gyorffy et al, Oncogene 2005 (July), Prediction of doxorubicin sensitivity in breast tumors based on gene expression profiles of drug-resistant cell lines correlates with patient survival. We contrasted the expression profiles of 13 different human tumor cell lines of gastric (EPG85-257), pancreatic (EPP85-181), colon (HT29) and breast (MCF7 and MDA-MB-231) origin and their counterparts resistant to the topoisomerase inhibitors daunorubicin, doxorubicin or mitoxantrone. We interrogated cDNA arrays with 43 000 cDNA clones ( approximately 30 000 unique genes) to study the expression pattern of these cell lines. A cell type comparison design experiment design type compares cells of different type for example different cell lines. Using regression correlation

2005-07-30 | E-GEOD-3034 | biostudies-arrayexpress

A phenotype-based model for rational selection of novel targeted therapies in treating aggressive breast cancer

2011-06-01 | GSE18331 | GEO

Indole-3-Carbinol Preferentially Target ERÎ±-Positive Breast Cancer Cells.

Project description:Indole-3-carbinol (I3C) is a natural anti-carcinogenic compound found at high concentrations in Brassica vegetables. ER-positive cell lines demonstrated the greatest sensitivity to the anti-tumor effects of I3C compared to ER-negative breast cancer cell lines. Gene expression analysis was performed to identify genes and pathways that accounted for sensitivity to I3C. Microarray analysis performed using Illumina HT-12 v4 expression arrays A total of 36 samples were analyzed with six breast cancer cell lines treated with either the vehicle control or the drug Indole-3-carbinol in triplicate. The cell lines were: MCF-7, T47D, ZR751(sensitive to the drug, apoptosis/growth arrest) and MDA-MB-231, MDA-MB-157, and MDA-MB-436 (insensitive to the drug). Sensitive cell lines are of the luminal subtype and insensitive cell lines are of the basal subtype.

2014-08-12 | E-GEOD-55897 | biostudies-arrayexpress

The effects on the deficient of PRMT1 on gene expression for the acquisition of chemoresistance in triple negative breast cancer cells.

Project description:In cancer cells, metabolic programming is regulated by gene expression and/or by post-translational modifications of metabolic enzymes. The correlation between metabolic characteristics of breast cancer and their drug sensitivity has attracted much attention. Here, we investigated whether PRMT1, a major arginine methyltransferase, affects the expression levels of metabolic enzymes by mRNA expression profiling of wild-type and PRMT1 knockout cells of the breast cancer cell line MDA-MB-468 cells. The results strongly suggest that PRMT1-mediated breast cancer drug sensitivity is regulated by post-transcriptional rather than transcriptional regulation.

2024-01-28 | GSE250022 | GEO

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