ArticleJournal of translational medicine2019
Identifying subpathway signatures for individualized anticancer drug response by integrating multi-omics data.
Article in Journal of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- The impact of deep learning and omics data in transforming precision therapy for brain cancer.Frontiers in bioinformatics · 2026Review
- A network model for patient-derived drug response in breast cancer integrating multi-omics datasets.bioRxiv : the preprint server for biology · 2025Article
- Large-Scale Machine Learning Analysis Reveals DNA Methylation and Gene Expression Response Signatures for Gemcitabine-Treated Pancreatic Cancer.Health data science · 2024Article
- Advances in the Applications of Bioinformatics and Chemoinformatics.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Identification and Functional Analysis of Individual-Specific Subpathways in Lung Adenocarcinoma.Genes · 2022Article
- Gut microbiota specifically mediates the anti-hypercholesterolemic effect of berberine (BBR) and facilitates to predict BBR's cholesterol-decreasing efficacy in patients.Journal of advanced research · 2022Article
- Big Data to Knowledge: Application of Machine Learning to Predictive Modeling of Therapeutic Response in Cancer.Current genomics · 2021Review
- The Comprehensive "Omics" Approach from Metabolomics to Advanced Omics for Development of Immune Checkpoint Inhibitors: Potential Strategies for Next Generation of Cancer Immunotherapy.International journal of molecular sciences · 2021Review
- Incorporating Machine Learning into Established Bioinformatics Frameworks.International journal of molecular sciences · 2021Review
- Omics and Computational Modeling Approaches for the Effective Treatment of Drug-Resistant Cancer Cells.Frontiers in genetics · 2021Review
- DRIM: A Web-Based System for Investigating Drug Response at the Molecular Level by Condition-Specific Multi-Omics Data Integration.Frontiers in genetics · 2020Article
- Systematic dissection, preservation, and multiomics in whole human and bovine hearts.Cardiovascular pathology : the official journal of the Society for Cardiovascular PathologyArticle
Corrections and comments
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Authors and funding
15 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIndividualized drug response prediction is vital for achieving personalized treatment of cancer and moving precision medicine forward. Large-scale multi-omics profiles provide unprecedented opportunities for precision cancer therapy.
methodsIn this study, we propose a pipeline to identify subpathway signatures for anticancer drug response of individuals by integrating the comprehensive contributions of multiple genetic and epigenetic (gene expression, copy number variation and DNA methylation) alterations.
resultsTotally, 46 subpathway signatures associated with individual responses to different anticancer drugs were identified based on five cancer-drug response datasets. We have validated the reliability of subpathway signatures in two independent datasets. Furthermore, we also demonstrated these multi-omics subpathway signatures could significantly improve the performance of anticancer drug response prediction. In-depth analysis of these 46 subpathway signatures uncovered the essential roles of three omics types and the functional associations underlying different anticancer drug responses. Patient stratification based on subpathway signatures involved in anticancer drug response identified subtypes with different clinical outcomes, implying their potential roles as prognostic biomarkers. In addition, a landscape of subpathways associated with cellular responses to 191 anticancer drugs from CellMiner was provided and the mechanism similarity of drug action was accurately unclosed based on these subpathways. Finally, we constructed a user-friendly web interface-CancerDAP ( http://bio-bigdata.hrbmu.edu.cn/CancerDAP/ ) available to explore 2751 subpathways relevant with 191 anticancer drugs response.
conclusionsTaken together, our study identified and systematically characterized subpathway signatures for individualized anticancer drug response prediction, which may promote the precise treatment of cancer and the study for molecular mechanisms of drug actions.
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