ArticleScience advances2021
Metabolic detection and systems analyses of pancreatic ductal adenocarcinoma through machine learning, lipidomics, and multi-omics.
Article in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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Who cites it
54 citing papers in PubMed.
- Propionyl-CoA catabolism is a metabolic gatekeeper for fatty acid oxidation in pancreatic cancer.Oncogene · 2026Article
- Detection of Pancreatic Cancer via Specific Metabolite Markers: A Metabolomics Approach.Health science reports · 2026Article
- Fingerprinting the Metabolic and Lipidomic Landscapes of Pancreatic Ductal Adenocarcinoma with MALDI Imaging.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- Molecular residual disease-based novel modality of postoperative management for non-small-cell lung cancer (REMODEL): Protocol for a prospective multicenter study.Journal of translational internal medicine · 2026Article
- Inference of upstream-mutation and metabolomic-signature causality identifies prognostic biomarkers and therapeutic targets in pancreatic cancer.Nature communications · 2026Article
- Gata1-mediated Hras transcription stimulates blood-brain barrier injury in ischemic stroke through activation of the ERK pathway.Human cell · 2026Article
- The pivotal role of mitochondria in the pathogenesis and treatment of liver failure: a comprehensive review.Molecular and cellular biochemistry · 2026Review
- Dynamic collaboration between mitochondria and organelles: mechanisms, functions, and disease implications.Apoptosis : an international journal on programmed cell death · 2026Review
- PanMETAI - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via NMR metabolomics.Nature communications · 2026Article
- Machine learning-based multimodal biomarkers enable accurate diagnosis and early detection of pancreatic ductal adenocarcinoma.Scientific reports · 2026Article
- Conditionally Activatable Antibody Platforms: Mechanisms, Modalities, and Clinical Translation Potential.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026Review
- FNA-based lipidomics reveals coordinated lipid metabolic remodeling in pancreatic cancer.Frontiers in molecular biosciences · 2026Article
- Combined Maternal Immune Activation and Prenatal Intermittent Hypoxic Stress Lead to Developmental Motor Deficits in Rats: a Two-hit Animal Model for Cerebral Palsy Across Different Age Trajectories.Molecular neurobiology · 2025Article
- Article
- Sleep deprivation and risk for Parkinson's disease: evidence and therapeutic implications.Journal of neurology · 2025Review
- Mapping current research status and emerging frontiers of lipidomics: a comprehensive data-mining-based study.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Integrated spatial omics of metabolic reprogramming and the tumor microenvironment in pancreatic cancer.iScience · 2025Article
- Responses of natural plastisphere community and zooplankton to microplastic pollution: a review on novel remediation strategies.Archives of microbiology · 2025Review
- An integrative multi-omics analysis reveals a multi-analyte signature of pancreatic ductal adenocarcinoma in serum.Journal of gastroenterology · 2025Article
- MethPriorGCN: a deep learning tool for inferring DNA methylation prior knowledge and guiding personalized medicine.Briefings in bioinformatics · 2025Article
Corrections and comments
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Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, characterized by rapid progression, metastasis, and difficulty in diagnosis. However, there are no effective liquid-based testing methods available for PDAC detection. Here we introduce a minimally invasive approach that uses machine learning (ML) and lipidomics to detect PDAC. Through greedy algorithm and mass spectrum feature selection, we optimized 17 characteristic metabolites as detection features and developed a liquid chromatography-mass spectrometry-based targeted assay. In this study, 1033 patients with PDAC at various stages were examined. This approach has achieved 86.74% accuracy with an area under curve (AUC) of 0.9351 in the large external validation cohort and 85.00% accuracy with 0.9389 AUC in the prospective clinical cohort. Accordingly, single-cell sequencing, proteomics, and mass spectrometry imaging were applied and revealed notable alterations of selected lipids in PDAC tissues. We propose that the ML-aided lipidomics approach be used for early detection of PDAC.
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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.