Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab. Export

@article{Faratian2009SystemsBiology, 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.}, author = {Faratian, Dana and Goltsov, Alexey and Lebedeva, Galina and Sorokin, Anatoly and Moodie, Stuart and Mullen, Peter and Kay, Charlene and In Hwa and Langdon, Simon and Goryanin, Igor and Harrison, David J.}, citeulike-article-id = {5430875}, citeulike-linkout-0 = {http://dx.doi.org/10.1158/0008-5472.CAN-09-0777}, citeulike-linkout-1 = {http://cancerres.aacrjournals.org/content/69/16/6713.abstract}, citeulike-linkout-2 = {http://cancerres.aacrjournals.org/content/69/16/6713.full.pdf}, citeulike-linkout-3 = {http://cancerres.aacrjournals.org/cgi/content/abstract/69/16/6713}, citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/19638581}, citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=19638581}, day = {15}, doi = {10.1158/0008-5472.CAN-09-0777}, issn = {1538-7445}, journal = {Cancer research}, keywords = {cancer, clinical, insilico, kinetic, personalized-medicine, protein-expression, systems-biology, therapy}, month = {August}, number = {16}, pages = {6713--6720}, posted-at = {2009-10-06 20:39:56}, priority = {2}, title = {Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab.}, url = {http://dx.doi.org/10.1158/0008-5472.CAN-09-0777}, volume = {69}, year = {2009} }

TY - JOUR ID - Faratian2009SystemsBiology L3 - citeulike-article-id:5430875 N2 - 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. IS - 16 JF - Cancer research SN - 1538-7445 EP - 6720 TI - Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab. VL - 69 SP - 6713 KW - cancer KW - clinical KW - insilico KW - kinetic KW - personalized-medicine KW - protein-expression KW - systems-biology KW - therapy AU - Faratian, Dana AU - Goltsov, Alexey AU - Lebedeva, Galina AU - Sorokin, Anatoly AU - Moodie, Stuart AU - Mullen, Peter AU - Kay, Charlene AU - In Hwa AU - Langdon, Simon AU - Goryanin, Igor AU - Harrison, David PY - 2009/08/15/ UR - http://dx.doi.org/10.1158/0008-5472.CAN-09-0777 ER -