ArticleBriefings in bioinformatics2016
A network medicine approach to build a comprehensive atlas for the prognosis of human cancer.
Article in Briefings in bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed.
- MiR-381-3p inhibits Warburg effect and progression in osteosarcoma via targeting PFKFB3.World journal of surgical oncology · 2026Article
- A network medicine approach for identifying diagnostic and prognostic biomarkers and exploring drug repurposing in human cancer.Computational and structural biotechnology journal · 2023Article
- The Immune-related ceRNA Network in Prognosis of Cervical Cancer.Asian Pacific journal of cancer prevention : APJCP · 2022Article
- Amino Acid Conjugates of Aminothiazole and Aminopyridine as Potential Anticancer Agents: Synthesis, Molecular Docking and in vitro Evaluation.Drug design, development and therapy · 2021Article
- A census of pathway maps in cancer systems biology.Nature reviews. Cancer · 2020Review
- Article
- Identification of Pan-Cancer Prognostic Biomarkers Through Integration of Multi-Omics Data.Frontiers in bioengineering and biotechnology · 2020Article
- Identifying subpathway signatures for individualized anticancer drug response by integrating multi-omics data.Journal of translational medicine · 2019Article
- Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.Briefings in bioinformatics · 2019Review
- Recurrence-Associated Long Non-coding RNA Signature for Determining the Risk of Recurrence in Patients with Colon Cancer.Molecular therapy. Nucleic acids · 2018Article
- A long non-coding RNA expression signature to predict survival of patients with colon adenocarcinoma.Oncotarget · 2017Article
- Microarray analyses reveal genes related to progression and prognosis of esophageal squamous cell carcinoma.Oncotarget · 2017Article
- DisSetSim: an online system for calculating similarity between disease sets.Journal of biomedical semantics · 2017Article
- LncRNAs2Pathways: Identifying the pathways influenced by a set of lncRNAs of interest based on a global network propagation method.Scientific reports · 2017Article
- Integrative analysis of lncRNAs and miRNAs with coding RNAs associated with ceRNA crosstalk network in triple negative breast cancer.OncoTargets and therapy · 2017Article
- Hedgehog signaling pathway in colorectal cancer: function, mechanism, and therapy.OncoTargets and therapy · 2017Review
- Introducing crucial protein panel of gastric adenocarcinoma disease.Gastroenterology and hepatology from bed to bench · 2017Article
- Article
- Article
- OAHG: an integrated resource for annotating human genes with multi-level ontologies.Scientific reports · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
The Cancer Genome Atlas project has generated multi-dimensional and highly integrated genomic data from a large number of patient samples with detailed clinical records across many cancer types, but it remains unclear how to best integrate the massive amount of genomic data into clinical practice. We report here our methodology to build a multi-dimensional subnetwork atlas for cancer prognosis to better investigate the potential impact of multiple genetic and epigenetic (gene expression, copy number variation, microRNA expression and DNA methylation) changes on the molecular states of networks that in turn affects complex cancer survivorship. We uncover an average of 38 novel subnetworks in the protein-protein interaction network that correlate with prognosis across four prominent cancer types. The clinical utility of these subnetwork biomarkers was further evaluated by prognostic impact evaluation, functional enrichment analysis, drug target annotation, tumor stratification and independent validation. Some pathways including the dynactin, cohesion and pyruvate dehydrogenase-related subnetworks are identified as promising new targets for therapy in specific cancer types. In conclusion, this integrative analysis of existing protein interactome and cancer genomics data allows us to systematically dissect the molecular mechanisms that underlie unexpected outcomes for cancer, which could be used to better understand and predict clinical outcomes, optimize treatment and to provide new opportunities for developing therapeutics related to the subnetworks identified.
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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.