Project description:Loss of H3K27me3 repressive chromatin histone marks, maintained by the histone methyltransferase (HKMT) EZH2, may lead to reversal of epigenetic silencing in tumor cells and have therapeutic potential. Using a cell-based assay, we have identified three compounds from a HKMT inhibitor chemical library which re-express H3K27me3 mediated, silenced genes. Chromatin immunoprecipitation verified a decrease in silencing marks (H3K27me3, H3K9me3) and importantly an increase in active marks (H3K4me2/3, H3K27ac) at the promoter of re-expressed genes. Compound treated breast tumor cells induced enrichment for genome-wide changes in expression of known target genes for EZH2 and induced cell growth inhibition: with most sensitive breast tumor cell lines having low EZH2 protein expression, while a normal epithelial breast line was least sensitive. Agilent SurePrint G3 Human 8x60k two-colour microarrays were used to profile gene expression changes induced by treatment with drug compounds in MDA MB-231 cells, both at 24h and 48h. 4 replicates were used for each drug, time combination. A separate untreated control sample was used for comparison with each replicate.
Project description:Faratian2009 - Role of PTEN in Trastuzumab
This model is described in the article:
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):
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
and identified by:
To cite BioModels Database, please use:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
Public Domain Dedication for more information.