ArticleNature communications2023
Single test-based diagnosis of multiple cancer types using Exosome-SERS-AI for early stage cancers.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 141 papers.
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
141 citing papers in PubMed, 310 citations in OpenAlex.
- Artificial intelligence and extracellular vesicles in oncology: towards tumor diagnosis, prediction, and therapy.Drug delivery · 2026Review
- Ultrasound-enhanced exosome secretion and antibody-free SERS profiling for Alzheimer's disease via iPSC-derived cortical organoids.Science advances · 2026Article
- Surface-Enhanced Raman Spectroscopy in Breast Cancer Detection: A Bibliometric Review and Landscape of Global Trends.Biosensors · 2026Review
- Extracellular vesicles in gastric cancer: biological functions, clinical applications, and engineering strategies.Medical oncology (Northwood, London, England) · 2026Review
- Extracellular vesicle biomarkers in pancreatic ductal adenocarcinoma: from bulk detection to single-extracellular vesicle profiling and endoscopic liquid biopsy.Journal of gastroenterology · 2026Review
- Machine-Learning-Assisted Impedance Component Analysis Enables Standardizable Surface Protein Analysis of Extracellular Vesicles Using Engineered Nanovesicles.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Liquid Biopsy for Molecular Residual Disease Detection and Postoperative Surveillance in Gastric Cancer: Current Evidence and Future Directions.International journal of molecular sciences · 2026Review
- Advances in Extracellular Vesicle-Based Surface-Enhanced Raman Spectroscopy for Cancer Diagnosis.Biosensors · 2026Review
- Advanced integrated SERS-based strategies for the early diagnosis of upper gastrointestinal cancers.Journal of nanobiotechnology · 2026Review
- Extracellular Vesicles in Cancer: Biomarkers, Mechanisms, and Emerging Diagnostic Technologies.Advanced healthcare materials · 2026Review
- Artificial Intelligence-Enabled Exosomes in Precision Oncology: A Framework for Clinical Utility and Biomedical Applications.Current issues in molecular biology · 2026Review
- Dual-mode analysis of ischemic stroke based on urine SERS spectra and carotid B-ultrasound.Science advances · 2026Article
- Emerging Plasmonic Nanomaterials for SERS-Based Disease Diagnostics: Innovations, Clinical Challenges, and AI Integration.Molecules (Basel, Switzerland) · 2026Review
- AI/ML-Assisted SERS Biosensing for Biomolecular Detection: From Direct Spectral Response to Integrated Diagnostic Systems.Biosensors · 2026Review
- Protocol for cerebrospinal fluid analysis using enrichment-enhanced surface-enhanced Raman spectroscopy and transformer-enabled spectral classification.STAR protocols · 2026Article
- The Dual Roles of Extracellular Vesicle Subtypes in Regulating Traumatic Brain Injury.International journal of molecular sciences · 2026Review
- Mapping Artificial Intelligence Research in Oral and Maxillofacial Surgery: A Bibliometric Analysis.International dental journal · 2026Article
- Exosomes in bone health and disease: cellular crosstalk, systemic signaling, and AI-driven advances in regenerative therapy.Stem cell research & therapy · 2026Review
- Raman Spectroscopy in Cancer Diagnostics and Surgery: 25 Years of Progress from Surface-Enhanced Raman Spectroscopy to Artificial Intelligence─A Bibliometric and Visualized Study.Analytical chemistry · 2026Review
- Emerging Trends in Artificial Intelligence-Integrated Biochip Technologies for Biomedical Applications.Micromachines · 2026Review
81 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
8 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early cancer detection has significant clinical value, but there remains no single method that can comprehensively identify multiple types of early-stage cancer. Here, we report the diagnostic accuracy of simultaneous detection of 6 types of early-stage cancers (lung, breast, colon, liver, pancreas, and stomach) by analyzing surface-enhanced Raman spectroscopy profiles of exosomes using artificial intelligence in a retrospective study design. It includes classification models that recognize signal patterns of plasma exosomes to identify both their presence and tissues of origin. Using 520 test samples, our system identified cancer presence with an area under the curve value of 0.970. Moreover, the system classified the tumor organ type of 278 early-stage cancer patients with a mean area under the curve of 0.945. The final integrated decision model showed a sensitivity of 90.2% at a specificity of 94.4% while predicting the tumor organ of 72% of positive patients. Since our method utilizes a non-specific analysis of Raman signatures, its diagnostic scope could potentially be expanded to include other diseases.
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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 Socratic graph.