ArticleGigaScience2020
A generalizable data-driven multicellular model of pancreatic ductal adenocarcinoma.
Article in GigaScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 28 citations in OpenAlex.
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- Integrating mechanism-based T cell phenotypes into a model of tumor-immune cell interactions.APL bioengineering · 2024Article
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- Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3DBiophysics reviews · 2024Review
- Pancreatic cancer mutationscape: revealing the link between modular restructuring and intervention efficacy amidst common mutations.bioRxiv : the preprint server for biology · 2024Article
- Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology.Briefings in bioinformatics · 2024Article
- Dysregulated FGFR3 signaling alters the immune landscape in bladder cancer and presents therapeutic possibilities in an agent-based model.Frontiers in immunology · 2024Article
- Phenotype Control techniques for Boolean gene regulatory networks.Bulletin of mathematical biology · 2023Review
- From time-series transcriptomics to gene regulatory networks: A review on inference methods.PLoS computational biology · 2023Review
- An agent-based model of monocyte differentiation into tumour-associated macrophages in chronic lymphocytic leukemia.iScience · 2023Article
- Phenotype control techniques for Boolean gene regulatory networks.bioRxiv : the preprint server for biology · 2023Article
- Article
- What Is a Digital Twin? Experimental Design for a Data-Centric Machine Learning Perspective in Health.International journal of molecular sciences · 2022Article
- Integrating single cell sequencing with a spatial quantitative systems pharmacology model spQSP for personalized prediction of triple-negative breast cancer immunotherapy response.Immunoinformatics (Amsterdam, Netherlands) · 2021Article
- circRNA circ_102049 Implicates in Pancreatic Ductal Adenocarcinoma Progression through Activating CD80 by Targeting miR-455-3p.Mediators of inflammation · 2021Article
- A generalizable data-driven multicellular model of pancreatic ductal adenocarcinoma.GigaScience · 2020Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMechanistic models, when combined with pertinent data, can improve our knowledge regarding important molecular and cellular mechanisms found in cancer. These models make the prediction of tissue-level response to drug treatment possible, which can lead to new therapies and improved patient outcomes. Here we present a data-driven multiscale modeling framework to study molecular interactions between cancer, stromal, and immune cells found in the tumor microenvironment. We also develop methods to use molecular data available in The Cancer Genome Atlas to generate sample-specific models of cancer.
resultsBy combining published models of different cells relevant to pancreatic ductal adenocarcinoma (PDAC), we built an agent-based model of the multicellular pancreatic tumor microenvironment, formally describing cell type-specific molecular interactions and cytokine-mediated cell-cell communications. We used an ensemble-based modeling approach to systematically explore how variations in the tumor microenvironment affect the viability of cancer cells. The results suggest that the autocrine loop involving EGF signaling is a key interaction modulator between pancreatic cancer and stellate cells. EGF is also found to be associated with previously described subtypes of PDAC. Moreover, the model allows a systematic exploration of the effect of possible therapeutic perturbations; our simulations suggest that reducing bFGF secretion by stellate cells will have, on average, a positive impact on cancer apoptosis.
conclusionsThe developed framework allows model-driven hypotheses to be generated regarding therapeutically relevant PDAC states with potential molecular and cellular drivers indicating specific intervention strategies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.