ArticlePLoS computational biology2016
Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 42 citations in OpenAlex.
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- Uncovering specific mechanisms across cell types in dynamical models.PLoS computational biology · 2023Article
- The computational capabilities of many-to-many protein interaction networks.Cell systems · 2023Review
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- STAT5 as a Key Protein of Erythropoietin Signalization.International journal of molecular sciences · 2021Review
- The intensification of anticancer activity of LFM-A13 by erythropoietin as a possible option for inhibition of breast cancer.Journal of enzyme inhibition and medicinal chemistry · 2020Article
- Disentangling molecular mechanisms regulating sensitization of interferon alpha signal transduction.Molecular systems biology · 2020Article
- Erythropoietin and its derivatives: from tissue protection to immune regulation.Cell death & disease · 2020Review
- Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies.Molecular systems biology · 2020Article
- Benchmark problems for dynamic modeling of intracellular processes.Bioinformatics (Oxford, England) · 2019Article
- Extensions of ℓBMC bioinformatics · 2019Article
- Using Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways.Frontiers in physiology · 2018Article
- Systemic network analysis identifies XIAP and IκBα as potential drug targets in TRAIL resistant BRAF mutated melanoma.NPJ systems biology and applications · 2018Article
- Local blockage of self-sustainable erythropoietin signaling suppresses tumor progression in non-small cell lung cancer.Oncotarget · 2017Article
- Correlated receptor transport processes buffer single-cell heterogeneity.PLoS computational biology · 2017Article
- Logic Modeling in Quantitative Systems Pharmacology.CPT: pharmacometrics & systems pharmacology · 2017Article
- Drug Resistance Mechanisms in Colorectal Cancer Dissected with Cell Type-Specific Dynamic Logic Models.Cancer research · 2017Article
- Erythropoietin drives breast cancer progression by activation of its receptor EPOR.Oncotarget · 2017Article
- Protein abundance of AKT and ERK pathway components governs cell type-specific regulation of proliferation.Molecular systems biology · 2017Article
Corrections and comments
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Authors and funding
18 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer, with its most prevalent form non-small-cell lung carcinoma (NSCLC), is one of the leading causes of cancer-related deaths worldwide, and is commonly treated with chemotherapeutic drugs such as cisplatin. Lung cancer patients frequently suffer from chemotherapy-induced anemia, which can be treated with erythropoietin (EPO). However, studies have indicated that EPO not only promotes erythropoiesis in hematopoietic cells, but may also enhance survival of NSCLC cells. Here, we verified that the NSCLC cell line H838 expresses functional erythropoietin receptors (EPOR) and that treatment with EPO reduces cisplatin-induced apoptosis. To pinpoint differences in EPO-induced survival signaling in erythroid progenitor cells (CFU-E, colony forming unit-erythroid) and H838 cells, we combined mathematical modeling with a method for feature selection, the L1 regularization. Utilizing an example model and simulated data, we demonstrated that this approach enables the accurate identification and quantification of cell type-specific parameters. We applied our strategy to quantitative time-resolved data of EPO-induced JAK/STAT signaling generated by quantitative immunoblotting, mass spectrometry and quantitative real-time PCR (qRT-PCR) in CFU-E and H838 cells as well as H838 cells overexpressing human EPOR (H838-HA-hEPOR). The established parsimonious mathematical model was able to simultaneously describe the data sets of CFU-E, H838 and H838-HA-hEPOR cells. Seven cell type-specific parameters were identified that included for example parameters for nuclear translocation of STAT5 and target gene induction. Cell type-specific differences in target gene induction were experimentally validated by qRT-PCR experiments. The systematic identification of pathway differences and sensitivities of EPOR signaling in CFU-E and H838 cells revealed potential targets for intervention to selectively inhibit EPO-induced signaling in the tumor cells but leave the responses in erythroid progenitor cells unaffected. Thus, the proposed modeling strategy can be employed as a general procedure to identify cell type-specific parameters and to recommend treatment strategies for the selective targeting of specific cell types.
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