ArticleCancers2022
Integrated Network Pharmacology Approach for Drug Combination Discovery: A Multi-Cancer Case Study.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
14 citing papers in PubMed.
- Computer-Aided Drug Design Across Breast Cancer Subtypes: Methods, Applications and Translational Outlook.International journal of molecular sciences · 2025Review
- Exploration of isolated actives from Coleus amboinicus leaves as anticancer agents: in vitro testing, network pharmacology studies, and molecular docking.Scientific reports · 2025Article
- Gene context drift identifies drug targets to mitigate cancer treatment resistance.Cancer cell · 2025Article
- Strategies for the drug development of cancer therapeutics.Frontiers in pharmacology · 2025Review
- Comparing gene-gene co-expression network approaches for the analysis of cell differentiation and specification on scRNAseq data.Computational and structural biotechnology journal · 2025Article
- Harnessing Drug Repurposing to Combat Breast Cancer by Targeting Altered Metabolism and Epithelial-to-Mesenchymal Transition Pathways.ACS pharmacology & translational science · 2024Review
- Computer-aided drug discovery strategies for novel therapeutics for prostate cancer leveraging next-generating sequencing data.Expert opinion on drug discovery · 2024Review
- PHGDH: a novel therapeutic target in cancer.Experimental & molecular medicine · 2024Review
- Prevention of neointimal hyperplasia after coronary artery bypass graft via local delivery of sirolimus and rosuvastatin: network pharmacology and in vivo validation.Journal of translational medicine · 2024Article
- Revolutionizing Cancer Treatment: Unveiling New Frontiers by Targeting the (Un)Usual Suspects.Cancers · 2023Article
- Computational Advancements in Cancer Combination Therapy Prediction.JCO precision oncology · 2023Article
- Toxicogenomics Data for Chemical Safety Assessment and Development of New Approach Methodologies: An Adverse Outcome Pathway-Based Approach.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Comprehensive exploration of JQ1 and GSK2801 targets in breast cancer using network pharmacology and molecular modeling approaches.Computational and structural biotechnology journal · 2023Article
- The potential of a data centred approach & knowledge graph data representation in chemical safety and drug design.Computational and structural biotechnology journal · 2022Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Despite remarkable efforts of computational and predictive pharmacology to improve therapeutic strategies for complex diseases, only in a few cases have the predictions been eventually employed in the clinics. One of the reasons behind this drawback is that current predictive approaches are based only on the integration of molecular perturbation of a certain disease with drug sensitivity signatures, neglecting intrinsic properties of the drugs. Here we integrate mechanistic and chemocentric approaches to drug repositioning by developing an innovative network pharmacology strategy. We developed a multilayer network-based computational framework integrating perturbational signatures of the disease as well as intrinsic characteristics of the drugs, such as their mechanism of action and chemical structure. We present five case studies carried out on public data from The Cancer Genome Atlas, including invasive breast cancer, colon adenocarcinoma, lung squamous cell carcinoma, hepatocellular carcinoma and prostate adenocarcinoma. Our results highlight paclitaxel as a suitable drug for combination therapy for many of the considered cancer types. In addition, several non-cancer-related genes representing unusual drug targets were identified as potential candidates for pharmacological treatment of cancer.
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Registered trials
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.