ArticleNature communications2021
Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
97 citing papers in PubMed, 2 syntheses or guidelines pooled it, 182 citations in OpenAlex.
- Multilevel Mechanisms of Cancer Drug Resistance.International journal of molecular sciences · 2024Pooled it
- Investigating the effects of artificial intelligence on the personalization of breast cancer management: a systematic study.BMC cancer · 2024Pooled it
- Biochemically Constrained Multi-Omics Integration Reveals Protein-Metabolite Dependencies Across Diseases.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Oncometabolites in Cancer Metabolism: Mechanistic Insights and Biomarker Potential- A Narrative Review.Health science reports · 2026Article
- Metabolomic analysis for diagnosis of oral squamous cell carcinoma using machine learning.Discover oncology · 2026Article
- Early Epigenetic and Metabolic Responses to the Adipocyte Secretome Reveal Stress-Adaptive States in Triple-Negative Breast Cancer.bioRxiv : the preprint server for biology · 2026Article
- Microarray-Based Genomic Profiling in Low-Dose Radiation Research: Evidence, Limitations, and Translational Perspectives.International journal of molecular sciences · 2026Review
- Enzymatic colorimetric encoding-based digital medicine for pancreatic cancer diagnosis.Nature communications · 2026Article
- Non-coding RNA regulation of the radiation-induced DNA damage response and its translational relevance.Discover oncology · 2026Review
- Modeling Microbiome Modulation of Tumor Metabolic Networks to Predict Synergistic Therapies.bioRxiv : the preprint server for biology · 2026Article
- A Closed Computational-Experimental Loop Identifies Metabolic Collapse at the Root of Macrophage Dysfunction due to Zinc Dyshomeostasis.bioRxiv : the preprint server for biology · 2026Article
- Mathematical Modeling in Cancer Metabolism: Tools for Translational Applications in Metabolism-Based Therapy.Advances in experimental medicine and biology · 2026Review
- GAN-enhanced machine learning and metabolic modeling identify reprogramming in pancreatic cancer.PLoS computational biology · 2026Article
- Machine learning and metabolic modeling-based identification of hypoxia-driven metabolic signatures in pediatric cancers.Frontiers in pharmacology · 2026Article
- Multi-omic data integration and exploiting metabolic models using systems biology approach increase precision in subtyping and early diagnosis of cancer.Quantitative biology (Beijing, China) · 2025Article
- RPL29 as a radiotherapy-sensitive prognostic biomarker in multiple myeloma.World journal of surgical oncology · 2025Article
- AI-powered programmable virtual humans toward human physiologically-based drug discovery.Drug discovery today · 2025Review
- Molecular Adaptations to Repeated Radiation Exposure in Triple-Negative Breast Cancer: Dysregulation of Cell Adhesion, Mitochondrial Function, and Epithelial-Mesenchymal Transition.International journal of molecular sciences · 2025Article
- Mitochondrial metabolic reprogramming in colorectal cancer: mechanisms of resistance and future clinical interventions.Cell death discovery · 2025Review
- Serum metabolic profiling enables diagnosis, prognosis, and monitoring for brainstem gliomas.Nature communications · 2025Article
37 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challenge. Personalized prediction of tumor radiosensitivity is not currently implemented clinically due to insufficient accuracy of existing machine learning classifiers. Despite the acknowledged role of tumor metabolism in radiation response, metabolomics data is rarely collected in large multi-omics initiatives such as The Cancer Genome Atlas (TCGA) and consequently omitted from algorithm development. In this study, we circumvent the paucity of personalized metabolomics information by characterizing 915 TCGA patient tumors with genome-scale metabolic Flux Balance Analysis models generated from transcriptomic and genomic datasets. Metabolic biomarkers differentiating radiation-sensitive and -resistant tumors are predicted and experimentally validated, enabling integration of metabolic features with other multi-omics datasets into ensemble-based machine learning classifiers for radiation response. These multi-omics classifiers show improved classification accuracy, identify clinical patient subgroups, and demonstrate the utility of personalized blood-based metabolic biomarkers for radiation sensitivity. The integration of machine learning with genome-scale metabolic modeling represents a significant methodological advancement for identifying prognostic metabolite biomarkers and predicting radiosensitivity for individual patients.
Indexed as
Identifiers
What OpenQuestion holds
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.