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PROVIDER: PRJNA326930 | ENA |
REPOSITORIES: ENA
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Project description:Therapeutic vulnerabilities of mesenchymal subpopulations of pancreatic cancer cells undergoing anabolic reprogramming
| PRJNA326925 | ENA
Project description:Therapeutic vulnerabilities of mesenchymal subpopulations of pancreatic cancer cells undergoing anabolic reprogramming [set2]
| PRJNA326929 | ENA
Project description:Malignant neoplasms adapt and evolve in response to changes in oncogenic signaling, tumor microenvironmental stresses,and therapeutic interventions. Cancer cell plasticity in response to these evolutionary pressures is foundational to tumor progression and maintenance and therapeutic resistance. Here, to elucidate the underlying molecular and cellularmechanisms of cancer cell plasticity, integrated system-level, functional and genetic analyses were conducted in a conditional oncogenic Kras model of pancreatic ductal adenocarcinoma (PDAC), amalignancy displaying remarkable phenotypic diversityand morphological heterogeneity. In this model, stochastic extinction of oncogenic Krassignaling and emergence ofKras-independent escaper populationsis associated withde-differentiation and aggressive biological behavior.Transcriptomic and functional analyses ofKras-independent escapers reveal mesenchymal reprogramming driven by aSmarcb1/Mycnetwork and independence from MAPK signaling.A somatic mosaic model of PDAC which can track evolving subpopulations shows that depletion of Smarcb1 activates theMyc network which results in an anabolic switch to increased protein metabolism and the adaptive activation of ERstress-induced survival pathways.Theelevated protein turnover made mesenchymal sub-populationshighly susceptible topharmacological and genetic perturbation of the cellular proteostatic machinery andthe IRE1-α/MKK4 arm of the ER stress response pathway. Specifically, combination regimens impairing the unfolded protein responses (UPR) and the ER stress response can block the emergence of aggressive mesenchymal subpopulations in murine andpatient-derived PDACmodels. These molecular and biological insights inform a potential therapeutic strategy fortargeting aggressive mesenchymal features of PDAC.
2017-02-13 | GSE83753 | GEO
Project description:Malignant neoplasms adapt and evolve in response to changes in oncogenic signaling, tumor microenvironmental stresses,and therapeutic interventions. Cancer cell plasticity in response to these evolutionary pressures is foundational to tumor progression and maintenance and therapeutic resistance. Here, to elucidate the underlying molecular and cellularmechanisms of cancer cell plasticity, integrated system-level, functional and genetic analyses were conducted in a conditional oncogenic Kras model of pancreatic ductal adenocarcinoma (PDAC), amalignancy displaying remarkable phenotypic diversityand morphological heterogeneity. In this model, stochastic extinction of oncogenic Krassignaling and emergence ofKras-independent escaper populationsis associated withde-differentiation and aggressive biological behavior.Transcriptomic and functional analyses ofKras-independent escapers reveal mesenchymal reprogramming driven by aSmarcb1/Mycnetwork and independence from MAPK signaling.A somatic mosaic model of PDAC which can track evolving subpopulations shows that depletion of Smarcb1 activates theMyc network which results in an anabolic switch to increased protein metabolism and the adaptive activation of ERstress-induced survival pathways.Theelevated protein turnover made mesenchymal sub-populationshighly susceptible topharmacological and genetic perturbation of the cellular proteostatic machinery andthe IRE1-α/MKK4 arm of the ER stress response pathway. Specifically, combination regimens impairing the unfolded protein responses (UPR) and the ER stress response can block the emergence of aggressive mesenchymal subpopulations in murine andpatient-derived PDACmodels. These molecular and biological insights inform a potential therapeutic strategy fortargeting aggressive mesenchymal features of PDAC.
2017-02-13 | GSE83752 | GEO
Project description:<p>Metabolic reprogramming is a hallmark of cancer and is crucial for cancer progression, making it an attractive therapeutic target. Understanding the role of metabolic reprogramming in cancer initiation could help identify prevention strategies. To address this, we investigated metabolism during acinar-to-ductal metaplasia (ADM), the first step of pancreatic carcinogenesis. Glycolytic markers were elevated in ADM lesions compared to normal tissue from human samples. Comprehensive metabolic assessment in three mouse models with pancreas-specific activation of KRAS, PI3K or MEK1 using Seahorse measurements, NMR metabolome analysis, mass spectrometry, isotope tracing and RNA-seq analysis revealed a switch from oxidative phosphorylation to glycolysis in ADM. Blocking the metabolic switch attenuated ADM formation. Furthermore, mitochondrial metabolism was required for de novo synthesis of serine and glutathione but not for ATP production. MYC mediated the increase in GSH intermediates in ADM, and inhibition of GSH synthesis suppressed ADM development. This study thus identifies metabolic changes and vulnerabilities in the early stages of pancreatic carcinogenesis.</p>
2024-05-31 | MTBLS9772 | MetaboLights
Project description:<p>The involvement of membrane-bound solute carriers (SLCs) in neoplastic transdifferentiation processes is poorly defined. Here, we examined changes in the SLC landscape during epithelial-mesenchymal transition (EMT) of pancreatic cancer cells. We show that two SLCs from the organic anion/cation transporter family, SLC22A10 and SLC22A15, favor EMT via interferon (IFN) α and γ signaling activation of receptor tyrosine kinase-like orphan receptor 1 (ROR1) expression. In addition, SLC22A10 and SLC22A15 allow tumor cell accumulation of glutathione to support EMT via the IFNα/γ-ROR1 axis. Moreover, a pan-SLC22A inhibitor lesinurad reduces EMT-induced metastasis and gemcitabine chemoresistance to prolong survival in mouse models of pancreatic cancer, thus identifying new vulnerabilities for human PDAC.</p>
2021-10-15 | MTBLS1925 | MetaboLights
Project description:Pancreatic cancer is one of the most lethal malignancies, partly due to its profound metabolic adaptability, which contributes to drug resistance and therapeutic failure. Understanding how pancreatic cancer cells reprogram their metabolism in response to treatment may uncover new therapeutic vulnerabilities. This study investigates the metabolic adaptations underlying resistance to drug treatment in pancreatic cancer using a systems metabolomics approach to explore novel biomarkers and therapeutic strategies. Methods: Eight human pancreatic cancer cell lines were analyzed to assess metabolic heterogeneity and drug response. Untargeted and isotope-labeled metabolomics were performed to evaluate metabolic rewiring before and after treatment with erastin, a redox-disrupting agent. Differential correlation analysis was applied to identify key metabolic nodes associated with treatment adaptation. Combinatorial treatments using FDA-approved drugs targeting glycolysis and one-carbon metabolism were tested. Multi-omics integration of metabolomics and transcriptomics data was conducted to elucidate mechanisms of resistance. Results: Pancreatic cancer cell lines exhibited marked metabolic heterogeneity, with differences in nutrient dependency and mitochondrial activity. Erastin treatment revealed metabolic vulnerabilities but failed to sustain long-term growth suppression. Combinatorial treatments of erastin with methotrexate or alpelisib significantly reduced proliferation and induced metabolic alteration. A systems-level analysis identified serine metabolism as a central adaptive pathway activated in resistant mechanism. Metabolic tracing and gene expression analyses revealed increased de novo serine biosynthesis and uptake, coupled with enhanced redox balancing and epigenetic regulation. Notably, cell lines that reactivated growth after drug withdrawal exhibited transcriptional reprogramming involving serine-driven pathways. These adaptations were associated with increased expression of survival, proliferation and migration-related genes. Conclusions: This study demonstrates that pancreatic cancer cells rewire their metabolism in response to combinatorial drug treatment by activating serine synthesis and uptake. These metabolic adaptations sustain redox homeostasis, biosynthetic processes and transcriptional reprogramming, contributing to resistance mechanism. Serine metabolism emerges as a functional biomarker of metabolic plasticity and drug tolerance. These insights open new avenues for metabolism-based strategies to overcome resistance and advance precision therapy in pancreatic cancer.
2025-07-08 | GSE292891 | GEO
Project description:Pancreatic cancer is one of the most lethal malignancies, partly due to its profound metabolic adaptability, which contributes to drug resistance and therapeutic failure. Understanding how pancreatic cancer cells reprogram their metabolism in response to treatment may uncover new therapeutic vulnerabilities. This study investigates the metabolic adaptations underlying resistance to drug treatment in pancreatic cancer using a systems metabolomics approach to explore novel biomarkers and therapeutic strategies. Methods: Eight human pancreatic cancer cell lines were analyzed to assess metabolic heterogeneity and drug response. Untargeted and isotope-labeled metabolomics were performed to evaluate metabolic rewiring before and after treatment with erastin, a redox-disrupting agent. Differential correlation analysis was applied to identify key metabolic nodes associated with treatment adaptation. Combinatorial treatments using FDA-approved drugs targeting glycolysis and one-carbon metabolism were tested. Multi-omics integration of metabolomics and transcriptomics data was conducted to elucidate mechanisms of resistance. Results: Pancreatic cancer cell lines exhibited marked metabolic heterogeneity, with differences in nutrient dependency and mitochondrial activity. Erastin treatment revealed metabolic vulnerabilities but failed to sustain long-term growth suppression. Combinatorial treatments of erastin with methotrexate or alpelisib significantly reduced proliferation and induced metabolic alteration. A systems-level analysis identified serine metabolism as a central adaptive pathway activated in resistant mechanism. Metabolic tracing and gene expression analyses revealed increased de novo serine biosynthesis and uptake, coupled with enhanced redox balancing and epigenetic regulation. Notably, cell lines that reactivated growth after drug withdrawal exhibited transcriptional reprogramming involving serine-driven pathways. These adaptations were associated with increased expression of survival, proliferation and migration-related genes. Conclusions: This study demonstrates that pancreatic cancer cells rewire their metabolism in response to combinatorial drug treatment by activating serine synthesis and uptake. These metabolic adaptations sustain redox homeostasis, biosynthetic processes and transcriptional reprogramming, contributing to resistance mechanism. Serine metabolism emerges as a functional biomarker of metabolic plasticity and drug tolerance. These insights open new avenues for metabolism-based strategies to overcome resistance and advance precision therapy in pancreatic cancer.
2025-07-08 | GSE292890 | GEO
Project description:In this study, we applied Drop-seq, a high throughput single cell RNA-seq platform, to characterize the different cell types present in pancreatic cancer organoids. We sequenced the transcriptomes of 7675 single cells from organoids derived from a patient undergoing a Whipple procedure for pancreatic ductal adenocarcinoma (PDAC). We then developed a novel clustering approach based on a class of probabilistic generative models called topic models, leading to the identification of subpopulations of cells.
2020-06-01 | GSE114454 | GEO
Project description:This model is based on:
Computational Modeling of the Crosstalk Between Macrophage Polarization and Tumor Cell Plasticity in the Tumor Microenvironment.
Abstract:
Tumor microenvironments contain multiple cell types interacting among one another via different signaling pathways. Furthermore, both cancer cells and different immune cells can display phenotypic plasticity in response to these communicating signals, thereby leading to complex spatiotemporal patterns that can impact therapeutic response. Here, we investigate the crosstalk between cancer cells and macrophages in a tumor microenvironment through in silico (computational) co-culture models. In particular, we investigate how macrophages of different polarization (M1 vs. M2) can interact with epithelial-mesenchymal plasticity of cancer cells, and conversely, how cancer cells exhibiting different phenotypes (epithelial vs. mesenchymal) can influence the polarization of macrophages. Based on interactions documented in the literature, an interaction network of cancer cells and macrophages is constructed. The steady states of the network are then analyzed. Various interactions were removed or added into the constructed-network to test the functions of those interactions. Also, parameters in the mathematical models were varied to explore their effects on the steady states of the network. In general, the interactions between cancer cells and macrophages can give rise to multiple stable steady-states for a given set of parameters and each steady state is stable against perturbations. Importantly, we show that the system can often reach one type of stable steady states where cancer cells go extinct. Our results may help inform efficient therapeutic strategies.
2019-09-23 | MODEL1909230002 | BioModels