Dataset Information

Faratian2009 - Role of PTEN in Trastuzumab resistance

ABSTRACT: 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 BioModels Database and identified by: BIOMD0000000424. To cite BioModels Database, please use: BioModels Database: 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 CC0 Public Domain Dedication for more information.

DISEASE(S): Cancer

SUBMITTER: Galina Lebedeva

PROVIDER: BIOMD0000000424 | BioModels | 2011-08-18

REPOSITORIES: BioModels

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

Faratian Dana D Goltsov Alexey A Lebedeva Galina G Sorokin Anatoly A Moodie Stuart S Mullen Peter P Kay Charlene C Um In Hwa IH Langdon Simon S Goryanin Igor I Harrison David J DJ

Cancer research 20090728 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 ( ...[more]

PMID: 19638581

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Project description:Abstract BACKGROUND: The basal-like breast cancer (BLBC) subtype is characterized by positive staining for basal mammary epithelial cytokeratin markers, lack of hormone receptor and HER2 expression, and poor prognosis with currently no approved molecularly-targeted therapies. The oncogenic signaling pathways driving basal-like tumorigenesis are not fully elucidated. METHODS: One hundred sixteen unselected breast tumors were subjected to integrated analysis of phosphoinositide 3-kinase (PI3K) pathway related molecular aberrations by immunohistochemistry, mutation analysis, and gene expression profiling. Incidence and relationships between molecular biomarkers were characterized. Findings for select biomarkers were validated in an independent series. Synergistic cell killing in vitro and in vivo tumor therapy was investigated in breast cancer cell lines and mouse xenograft models, respectively. RESULTS: Sixty-four % of cases had an oncogenic alteration to PIK3CA, PTEN, or INPP4B; when including upstream kinases HER2 and EGFR, 75 % of cases had one or more aberration including 97 % of estrogen receptor (ER)-negative tumors. PTEN-loss was significantly associated to stathmin and EGFR overexpression, positivity for the BLBC markers cytokeratin 5/14, and the BLBC molecular subtype by gene expression profiling, informing a potential therapeutic combination targeting these pathways in BLBC. Combination treatment of BLBC cell lines with the EGFR-inhibitor gefitinib plus the PI3K pathway inhibitor LY294002 was synergistic, and correspondingly, in an in vivo BLBC xenograft mouse model, gefitinib plus PI3K-inhibitor PWT-458 was more effective than either monotherapy and caused tumor regression. CONCLUSIONS: Our study emphasizes the importance of PI3K/PTEN pathway activity in ER-negative and basal-like breast cancer and supports the future clinical evaluation of combining EGFR and PI3K pathway inhibitors for the treatment of BLBC. Gene expression profiles were generated for 95 breast tumors using Agilent Human 44K v5 microarrays following the manufacturer protocol. Stratagene Universal Human Reference RNA was used as the common control sample.

Project description:Gene expression data of HER2+ breast tumor samples Increasing evidence indicates that a subset of patients with HER2-positive breast cancer may achieve significant clinical benefit with anti-HER2 targeted therapy without chemotherapy. Thus, identification of biomarkers of long-term benefit from anti-HER2 agents is needed, especially in the metastatic setting. In the HERLAP study (NCT00842998), patients with HER2-positive metastatic breast cancer were randomized to trastuzumab or lapatinib as first-line therapy. Patients showing radiological signs of tumor regression after 8 weeks of treatment were allowed to continue on single agent anti-HER2 therapy until disease progression. Chemotherapy was added to anti-HER-2 therapy in patients failing to achieve tumor regression at the 8-week evaluation and those progressing at any time. Expression analysis of 105 selected genes was performed from formalin-fixed paraffin-embedded in 17 primary tumor samples. The research-based PAM50 intrinsic subtypes were also identified. The association of the expression of each biomarker with clinical outcome endpoints was evaluated. Nineteen patients were enrolled. In 4 patients (21.1%) we observed disease control lasting longer than 12 months with single agent anti-HER2 therapy (range 14.9-38.8 months). High expression of 17q12-21 amplicon genes HER2 and GRB7, and the PAM50 HER2-enriched intrinsic profile, were found significantly associated with 8-week overall response rate and with the duration of disease control during single agent anti-HER2 therapy. Conversely, high expression of luminal-related genes such as PGR, MDM2 or PIK3CA, or the PAM50 luminal intrinsic profile, was found associated with reduced benefit from single agent anti-HER2 therapy. Conclusions: Our data indicate that gene expression-based biomarkers can identify patients with HER2-positive metastatic breast cancer that benefit substantially from single agent chemo-free anti-HER2 targeted therapy. In the study presented here, a well-defined cohort of 21 breast cancer cases from the HERLAP trial, was used to acquire expression profiles of a total of 105 unique genes

Dataset Information

Faratian2009 - Role of PTEN in Trastuzumab resistance

Publications

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

Similar Datasets

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