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Contribution of synergism between PHF8 and HER2 signalling to breast cancer development and drug resistance

ABSTRACT: HER2 plays a critical role in tumorigenesis and is associated with poor prognosis of patients with HER2-positive breast cancers. Although anti-HER2 drugs are beneficial benefits for treating breast cancer, de novo, or acquired resistance often develops. Epigenetic factors are increasingly targeted for therapy; however, such mechanisms that interact with HER2 signaling are poorly understood. RNA sequencing was performed to identify PHF8 targets downstream of HER2 signaling. CHIP-qPCR were used to investigate how PHF8 regulates HER2 transcription. ELISA determined cytokine secretion. Cell-based assay revealed a feed forward loop in HER2 signaling and then evaluated in vivo. We report the synergistic interplay between histone demethylase PHF8 and HER2 signaling. Specifically, PHF8 levels were elevated in HER2-positive breast cancers and upregulated by HER2. PHF8 functioned as a coactivator that regulated the expression of HER2, markers of the HER2-driven epithelial-to-mesenchymal transition and cytokines. The HER2-PHF8-IL-6 regulatory axis was active in cell lines and in newly established MMTV-Her2/MMTV-Cre/Phf8-floxed mouse models, which revealed the oncogenic function of Phf8 in breast cancer for the first time. Further, the PHF8-IL-6 axis contributed to the resistance to trastuzumab in vitro and may play a critical role in the infiltration of T cells in HER2-driven breast cancers. These findings provided informative mechanistic insight into the potential application of PHF8 inhibitors to overcome resistance to anti-HER2 therapies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE140373 | GEO | 2019/11/15

REPOSITORIES: GEO

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Project description:Breast cancers with HER2 overexpression are sensitive to drugs targeting the receptor or its kinase activity. HER2-targeting drugs are initially effective against HER2- positive breast cancer, but resistance inevitably occurs. We previously found that nuclear factor kappa B is hyper-activated in the subset of HER-2 positive breast cancer cells and tissue specimens. In this study, we report that constitutively active NF-ÎºB rendered HER2-positive cancer cells resistant to anti-HER2 drugs, and cells selected for Lapatinib resistance up-regulated NF-ÎºB. In both circumstances, cells were anti-apoptotic and grew rapidly as xenografts. Lapatinib-resistant cells were refractory to HER2 and NF-ÎºB inhibitors alone but were sensitive to their combination, suggesting a novel therapeutic strategy. A subset of NF-ÎºB-responsive genes was overexpressed in HER2-positive and triple-negative breast cancers, and patients with this NF-ÎºB signature had poor clinical outcome. Anti-HER2 drug resistance may be a consequence of NF-ÎºB activation, and selection for resistance results in NF-ÎºB activation, suggesting this transcription factor is central to oncogenesis and drug resistance. Clinically, the combined targeting of HER2 and NF-ÎºB suggests a potential treatment paradigm for patients who relapse after anti-HER2 therapy. Patients with these cancers may be treated by simultaneously suppressing HER2 signaling and NF-ÎºB activation. We used microarrays to detail the gene expression differences underlying the characterictic survival differences between the SKR6, SKR6-Vector, SKR6CA, and SKR6LR cell lines, which are defined as follows: SKR6: A clonal derivative of SKBR3 cells isolated by fluorescence-activated cell sorting (FACS) to enrich for elevated HER2 levels, SKR6CA: SKR6 cells retrovirally transduced with constitutively active NF-ÎºB relA/p65 (CAp65) and selected with puromycin, SKR6 vector: SKR6 cells transduced with the pQCXIP empty retroviral vector and selected with puromycin, and SKR6LR: SKR6 cells treated with increasing lapatinib concentrations (0.2 to 5 Î¼M) for several months. We sorted SKBR-3 cells by fluorescence-activated cell sorting (FACS) to enriched for cell population with elevated HER2 expression, which we termed SKR6. The following cell lines were then created from SKR6 cells: SKR6CA: SKR6 cells retrovirally transduced with constitutively active NF-ÎºB relA/p65 (CAp65), SKR6 vector: SKR6 cells transduced with the pQCXIP empty retroviral vector and selected with puromycin, and SKR6LR: SKR6 cells treated with increasing lapatinib concentrations (0.2 to 5 Î¼M) for several months.

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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Contribution of synergism between PHF8 and HER2 signalling to breast cancer development and drug resistance

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