Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA337913 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Targeted FAIRE-sequencing of breast cancer risk regions in two breast cancer cell lines
| PRJNA337965 | ENA
Project description:Purpose: The goal of this study was to identify allele-specific open chromatin regions in breast cancer cell lines, focusing on the fraction of the genome that has been previously associated to breast-cancer risk. Methods: DNA obtained from Angilent SureSelect solution-based sequence capture was subjected to Illumina HiSeq 2500 paired-end sequencing (Illumina). We performed targeted sequencing of 3 replicated FAIRE samples per cell-line and the correspondent genomic DNA controls in two breast cancer cell lines (T47D and MDAMB134). Allele-specific analysis was performed with BaalChIP R package (version 0.1.9) with the default parameters and options. Results: Using targeted sequencing, we investigated 69 genomic loci that have been previously associated to breast cancer risk. We identified a total of 21 allele-specific SNPs in MDAMB134 and allele-specific 9 SNPs in T-47D cell lines (see processed files).
2017-01-26 | GSE85261 | GEO
Project description:Expression data from two breast cancer cell lines
| PRJNA221364 | ENA
Project description:We report the application of FAIRE seq in Human Mammary Epithelial Cells for identifying the breast cancer risk functional SNPs in enhancer region. Examination of FAIRE assay in HMEC
2013-05-10 | E-GEOD-46074 | biostudies-arrayexpress
Project description:We report the application of FAIRE seq in Human Mammary Epithelial Cells for identifying the breast cancer risk functional SNPs in enhancer region.
2013-05-10 | GSE46074 | GEO
Project description:Genome-wide association studies have identified over 70 common variants that are associated with breast cancer risk. Most of these variants map to non-protein-coding regions; several map to gene deserts, regions of several hundred kb lacking protein-coding genes. We hypothesized that gene deserts harbour long-range regulatory elements that can physically interact with target genes to influence their expression. To test this, we developed Capture Hi-C (CHi-C), which by incorporating a sequence capture step into a Hi-C protocol, allows high-resolution analysis of targeted regions of the genome. We used CHi-C to investigate long-range interactions at three breast cancer gene deserts mapping to 2q35, 8q24.21 and 9q31.2. We identified interaction peaks between putative regulatory elements ("bait fragments") within the captured regions and "targets" that included both protein-coding genes and long non-coding (lnc)RNAs, over distances of 6.6 kb to 2.6 Mb. Target protein-coding genes were IGFBP5, KLF4, NSMCE2 and MYC; target lncRNAs included DIRC3, PVT1 and CCDC26. For two gene deserts we were able to define a set of SNPs that were correlated with the published risk variant and that clustered within the bait end of an interaction peak. Preliminary functional analyses implicate one SNP (rs12613955; 2q35) as a potentially functional variant. Capture Hi-C was carried out in BT483, SUM44, and GM06990 cell lines to investigate breast cancer risk loci 2q35, 8q24.21 and 9q31.2.
2014-08-04 | E-GEOD-55634 | biostudies-arrayexpress
Project description:Faratian2009 - Role of PTEN in Trastuzumab
resistance
This model is described in the article:
Systems biology
reveals new strategies for personalizing cancer medicine and
confirms the role of PTEN in resistance to trastuzumab.
Faratian D, Goltsov A, Lebedeva G,
Sorokin A, Moodie S, Mullen P, Kay C, Um IH, Langdon S, Goryanin
I, Harrison DJ.
Cancer Res. 2009 Aug; 69(16):
6713-6720
Abstract:
Resistance to targeted cancer therapies such as trastuzumab
is a frequent clinical problem not solely because of
insufficient expression of HER2 receptor but also because of
the overriding activation states of cell signaling pathways.
Systems biology approaches lend themselves to rapid in silico
testing of factors, which may confer resistance to targeted
therapies. Inthis study, we aimed to develop a new kinetic
model that could be interrogated to predict resistance to
receptor tyrosine kinase (RTK) inhibitor therapies and directly
test predictions in vitro and in clinical samples. The new
mathematical model included RTK inhibitor antibody binding,
HER2/HER3 dimerization and inhibition, AKT/mitogen-activated
protein kinase cross-talk, and the regulatory properties of
PTEN. The model was parameterized using quantitative
phosphoprotein expression data from cancer cell lines using
reverse-phase protein microarrays. Quantitative PTEN protein
expression was found to be the key determinant of resistance to
anti-HER2 therapy in silico, which was predictive of unseen
experiments in vitro using the PTEN inhibitor bp(V). When
measured in cancer cell lines, PTEN expression predicts
sensitivity to anti-HER2 therapy; furthermore, this
quantitative measurement is more predictive of response
(relative risk, 3.0; 95% confidence interval, 1.6-5.5; P <
0.0001) than other pathway components taken in isolation and
when tested by multivariate analysis in a cohort of 122 breast
cancers treated with trastuzumab. For the first time, a systems
biology approach has successfully been used to stratify
patients for personalized therapy in cancer and is further
compelling evidence that PTEN, appropriately measured in the
clinical setting, refines clinical decision making in patients
treated with anti-HER2 therapies.
This model is hosted on
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and identified by:
BIOMD0000000424.
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2024-09-02 | BIOMD0000000424 | BioModels
Project description:This SuperSeries is composed of the following subset Series: GSE36324: Targeted inhibition of human breast cancer cell lines selected as model systems of ERBB2-positive/EGFR high breast cancer [RPPA-HCC1954] GSE36325: Targeted inhibition of human breast cancer cell lines selected as model systems of ERBB2-positive/EGFR high breast cancer [RPPA-Longterm] GSE36326: Targeted inhibition of human breast cancer cell lines selected as model systems of ERBB2-positive/EGFR high breast cancer [RPPA-SKBR3] Refer to individual Series
2012-10-22 | E-GEOD-36327 | biostudies-arrayexpress