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Gene expression profiling of N87 and OE19 gastric cancer cell lines grown in 3D or 2D condition

ABSTRACT: A great deal of evidence indicates that solid and hematological tumors are driven and maintained by a minor cell compartment with stem cell properties. In this context, gastric cancer stem cells (GCSCs) are implicated in tumor aggressiveness, invasion, metastasis and therapy resistance. HER2 amplification/overexpression (HER2+) is found in about 20% of GCs. Although the anti-HER2 antibody trastuzumab has improved the outcomes of patients with HER2+ advanced disease, its benefits are usually transitory because of high HER2 heterogeneity and frequent co-existence of other oncogenic drivers associated with primary/acquired resistance. To identify potential drivers of trastuzumab resistance in GCSCs, we compare the gene expression profile of OE19 and N87 HER2+ GC cell lines cultured as gastrospheres, peculiar 3D cell cultures that allow detecting the in vitro enrichment of CSCs, versus their matched adherent cell (2D) counterparts. Comparison of the transcriptomic profiles of HER2+ GC cells cultured in 2D versus 3D conditions evidenced a significant enrichment of Fatty Acid Synthase (FASN) transcript among the genes upmodulated in 3D cell cultures. We found that the pharmacological blockade of HER2 and FASN targets CSCs and decreases tumor growth of HER2-positive GC models

ORGANISM(S): Homo sapiens

PROVIDER: GSE212442 | GEO | 2023/05/31

REPOSITORIES: GEO

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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 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.

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Gene expression profiling of N87 and OE19 gastric cancer cell lines grown in 3D or 2D condition

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