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Discovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical Modeling
TLDR
A dynamical model representing a cell fate decision network in the AGS gastric cancer cell line is developed, demonstrating that a model predictive of combinatorial drug effects can be inferred from background knowledge on unperturbed and proliferating cancer cells.
The gastrin and cholecystokinin receptors mediated signaling network: a scaffold for data analysis and new hypotheses on regulatory mechanisms
TLDR
It is demonstrated how a literature-based CCKR signaling map together with its protein interaction extensions can be analyzed to generate new hypotheses on molecular mechanisms involved in gastrin- and cholecystokinin-mediated regulation of cellular processes.
A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines
TLDR
A dataset comprising 171 pairwise combinations of 19 individual drugs targeting signal transduction mechanisms across eight cancer cell lines is presented, where the effect of each drug and drug combination is reported as cell viability assessed by metabolic activity.
High-throughput screening reveals higher synergistic effect of MEK inhibitor combinations in colon cancer spheroids
TLDR
Spheroids, compared to 2D cultures, were generally both more sensitive and showed greater synergistic response to combinations involving a MEK inhibitor, which further shed light on the importance of including more complex culture models in order to increase the efficiency of drug discovery pipelines.
Tumor Targeting by αvβ3-Integrin-Specific Lipid Nanoparticles Occurs via Phagocyte Hitchhiking
TLDR
It is observed that ligand-mediated accumulation in cancerous lesions is multifaceted and identified “NP hitchhiking” with phagocytes to contribute considerably to this intricate process.
Network and Systems Medicine: Position Paper of the European Collaboration on Science and Technology Action on Open Multiscale Systems Medicine
TLDR
The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales and the health care system will also have to evolve, if not revolutionize, in terms of organization and management.
CImbinator: a web-based tool for drug synergy analysis in small- and large-scale datasets
TLDR
This work proposes a web‐service that can aid in batch‐wise and in‐depth analyzes of data from small‐scale and large‐scale drug combination screens, and offers to quantify drug combination effects, using both the commonly employed median effect equation and advanced experimental mathematical models describing dose response relationships.
Strategies to Enhance Logic Modeling-Based Cell Line-Specific Drug Synergy Prediction
TLDR
The results indicate that the performance of logic models can be improved by focusing on high-influence node protein activity data for model configuration and that these nodes accommodate high information flow in the regulatory network.
A Middle-Out Modeling Strategy to Extend a Colon Cancer Logical Model Improves Drug Synergy Predictions in Epithelial-Derived Cancer Cell Lines
TLDR
This study demonstrates how a tumor-data driven middle-out approach toward refining a logical model of a biological system can further customize a computer model to represent specific cancer cell lines and provide a basis for identifying synergistic effects of drugs targeting specific regulatory proteins.
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