ArticleNature communications2018
Pathway-based subnetworks enable cross-disease biomarker discovery.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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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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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
23 citing papers in PubMed, 37 citations in OpenAlex.
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- The impact of the tumor microenvironment on the survival of penile cancer patients.Scientific reports · 2024Article
- Pathway-based signatures predict patient outcome, chemotherapy benefit and synthetic lethal dependencies in invasive lobular breast cancer.British journal of cancer · 2024Article
- Enhancing the anticancer potential of metformin: fabrication of efficient nanospanlastics,International journal of pharmaceutics: X · 2023Article
- Systematic assessment of prognostic molecular features across cancers.Cell genomics · 2023Article
- Insights and Strategies of Melanoma Immunotherapy: Predictive Biomarkers of Response and Resistance and Strategies to Improve Response Rates.International journal of molecular sciences · 2022Review
- Quantification of ferroptosis pathway status revealed heterogeneity in breast cancer patients with distinct immune microenvironment.Frontiers in oncology · 2022Article
- Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry.Nature reviews. Urology · 2021Review
- Pathway signatures derived from on-treatment tumor specimens predict response to anti-PD1 blockade in metastatic melanoma.Nature communications · 2021Article
- Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology.British journal of cancer · 2021Article
- Two novel oxetane containing lignans and a new megastigmane fromRSC advances · 2021Article
- Artificial Intelligence in Bulk and Single-Cell RNA-Sequencing Data to Foster Precision Oncology.International journal of molecular sciences · 2021Review
- Exploration of databases and methods supporting drug repurposing: a comprehensive survey.Briefings in bioinformatics · 2021Review
- Incorporating Machine Learning into Established Bioinformatics Frameworks.International journal of molecular sciences · 2021Review
- A Detailed Catalogue of Multi-Omics Methodologies for Identification of Putative Biomarkers and Causal Molecular Networks in Translational Cancer Research.International journal of molecular sciences · 2021Review
- Estimating the AUC with a Graphical Lasso Method for High-dimensional Biomarkers with LOD.Biostatistics & epidemiology · 2021Article
- Kinase-substrate Edge Biomarkers Provide a More Accurate Prognostic Prediction in ER-negative Breast Cancer.Genomics, proteomics & bioinformatics · 2020Article
- Prioritization of candidate cancer drugs based on a drug functional similarity network constructed by integrating pathway activities and drug activities.Molecular oncology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
25 authors at 8 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biomarkers lie at the heart of precision medicine. Surprisingly, while rapid genomic profiling is becoming ubiquitous, the development of biomarkers usually involves the application of bespoke techniques that cannot be directly applied to other datasets. There is an urgent need for a systematic methodology to create biologically-interpretable molecular models that robustly predict key phenotypes. Here we present SIMMS (Subnetwork Integration for Multi-Modal Signatures): an algorithm that fragments pathways into functional modules and uses these to predict phenotypes. We apply SIMMS to multiple data types across five diseases, and in each it reproducibly identifies known and novel subtypes, and makes superior predictions to the best bespoke approaches. To demonstrate its ability on a new dataset, we profile 33 genes/nodes of the PI3K pathway in 1734 FFPE breast tumors and create a four-subnetwork prediction model. This model out-performs a clinically-validated molecular test in an independent cohort of 1742 patients. SIMMS is generic and enables systematic data integration for robust biomarker discovery.
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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.