author_facet Faratian, Dana
Goltsov, Alexey
Lebedeva, Galina
Sorokin, Anatoly
Moodie, Stuart
Mullen, Peter
Kay, Charlene
Um, In Hwa
Langdon, Simon
Goryanin, Igor
Harrison, David J.
Faratian, Dana
Goltsov, Alexey
Lebedeva, Galina
Sorokin, Anatoly
Moodie, Stuart
Mullen, Peter
Kay, Charlene
Um, In Hwa
Langdon, Simon
Goryanin, Igor
Harrison, David J.
author Faratian, Dana
Goltsov, Alexey
Lebedeva, Galina
Sorokin, Anatoly
Moodie, Stuart
Mullen, Peter
Kay, Charlene
Um, In Hwa
Langdon, Simon
Goryanin, Igor
Harrison, David J.
spellingShingle Faratian, Dana
Goltsov, Alexey
Lebedeva, Galina
Sorokin, Anatoly
Moodie, Stuart
Mullen, Peter
Kay, Charlene
Um, In Hwa
Langdon, Simon
Goryanin, Igor
Harrison, David J.
Cancer Research
Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
Cancer Research
Oncology
author_sort faratian, dana
spelling Faratian, Dana Goltsov, Alexey Lebedeva, Galina Sorokin, Anatoly Moodie, Stuart Mullen, Peter Kay, Charlene Um, In Hwa Langdon, Simon Goryanin, Igor Harrison, David J. 0008-5472 1538-7445 American Association for Cancer Research (AACR) Cancer Research Oncology http://dx.doi.org/10.1158/0008-5472.can-09-0777 <jats:title>Abstract</jats:title> <jats:p>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 &amp;lt; 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. [Cancer Res 2009;69(16):6713–20]</jats:p> Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab Cancer Research
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title Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_unstemmed Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_full Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_fullStr Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_full_unstemmed Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_short Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_sort systems biology reveals new strategies for personalizing cancer medicine and confirms the role of pten in resistance to trastuzumab
topic Cancer Research
Oncology
url http://dx.doi.org/10.1158/0008-5472.can-09-0777
publishDate 2009
physical 6713-6720
description <jats:title>Abstract</jats:title> <jats:p>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 &amp;lt; 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. [Cancer Res 2009;69(16):6713–20]</jats:p>
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author Faratian, Dana, Goltsov, Alexey, Lebedeva, Galina, Sorokin, Anatoly, Moodie, Stuart, Mullen, Peter, Kay, Charlene, Um, In Hwa, Langdon, Simon, Goryanin, Igor, Harrison, David J.
author_facet Faratian, Dana, Goltsov, Alexey, Lebedeva, Galina, Sorokin, Anatoly, Moodie, Stuart, Mullen, Peter, Kay, Charlene, Um, In Hwa, Langdon, Simon, Goryanin, Igor, Harrison, David J., Faratian, Dana, Goltsov, Alexey, Lebedeva, Galina, Sorokin, Anatoly, Moodie, Stuart, Mullen, Peter, Kay, Charlene, Um, In Hwa, Langdon, Simon, Goryanin, Igor, Harrison, David J.
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description <jats:title>Abstract</jats:title> <jats:p>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 &amp;lt; 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. [Cancer Res 2009;69(16):6713–20]</jats:p>
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spelling Faratian, Dana Goltsov, Alexey Lebedeva, Galina Sorokin, Anatoly Moodie, Stuart Mullen, Peter Kay, Charlene Um, In Hwa Langdon, Simon Goryanin, Igor Harrison, David J. 0008-5472 1538-7445 American Association for Cancer Research (AACR) Cancer Research Oncology http://dx.doi.org/10.1158/0008-5472.can-09-0777 <jats:title>Abstract</jats:title> <jats:p>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 &amp;lt; 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. [Cancer Res 2009;69(16):6713–20]</jats:p> Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab Cancer Research
spellingShingle Faratian, Dana, Goltsov, Alexey, Lebedeva, Galina, Sorokin, Anatoly, Moodie, Stuart, Mullen, Peter, Kay, Charlene, Um, In Hwa, Langdon, Simon, Goryanin, Igor, Harrison, David J., Cancer Research, Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab, Cancer Research, Oncology
title Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_full Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_fullStr Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_full_unstemmed Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_short Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
title_sort systems biology reveals new strategies for personalizing cancer medicine and confirms the role of pten in resistance to trastuzumab
title_unstemmed Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
topic Cancer Research, Oncology
url http://dx.doi.org/10.1158/0008-5472.can-09-0777