ArticleThoracic cancer2018
New method of lung cancer detection by saliva test using surface-enhanced Raman spectroscopy.
Article in Thoracic cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 3 of them syntheses that pooled it.
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Who cites it
24 citing papers in PubMed, 3 syntheses or guidelines pooled it, 75 citations in OpenAlex.
- Raman spectroscopy in the detection and diagnosis of lung cancer: a meta-analysis.Lasers in medical science · 2025Pooled it
- The efficacy of Raman spectroscopy in lung cancer diagnosis: the first diagnostic meta-analysis.Lasers in medical science · 2022Pooled it
- Vibrational Spectroscopy Saliva Profiling as Biometric Tool for Disease Diagnostics: A Systematic Literature.Molecules (Basel, Switzerland) · 2020Pooled it
- Review: Detection of Cancer Biomarkers from a Clinical Perspective.International journal of molecular sciences · 2025Review
- BreathERJ open research · 2025Article
- Diagnosis of lung cancer using salivary miRNAs expression and clinical characteristics.BMC pulmonary medicine · 2025Article
- Surface-enhanced Raman spectroscopy for label-free cancer liquid biopsy: from fundamentals to clinical analysis of biofluid.Frontiers in chemistry · 2025Review
- Utility of Raman Spectroscopy in Pulmonary Medicine.Advances in respiratory medicine · 2024Review
- Rapid detection of lung cancer based on serum Raman spectroscopy and a support vector machine: a case-control study.BMC cancer · 2024Article
- Computational and experimental microfluidics: Total analysis system for mixing, sorting, and concentrating particles and cells.APL bioengineering · 2024Article
- Filtered Saliva for Rapid and Accurate Analyte Detection for POC Diagnostics.Diagnostics (Basel, Switzerland) · 2024Article
- Accurate categorization and rapid pathological diagnosis correction with Micro-Raman technique in human lung adenocarcinoma infiltration level.Translational lung cancer research · 2024Article
- Detection and Identification of Pesticides in Fruits Coupling to an Au-Au Nanorod Array SERS Substrate and RF-1D-CNN Model Analysis.Nanomaterials (Basel, Switzerland) · 2024Article
- Raman-Based Techniques in Medical Applications for Diagnostic Tasks: A Review.International journal of molecular sciences · 2023Review
- Nanostructures for prevention, diagnosis, and treatment of viral respiratory infections: from influenza virus to SARS-CoV-2 variants.Journal of nanobiotechnology · 2023Review
- [Latest Findings on Salivary Tumor Biomarkers].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023Review
- A New Detection Method of Oral and Oropharyngeal Squamous Cell Carcinoma Based on Multivariate Analysis of Surface Enhanced Raman Spectra of Salivary Exosomes.Journal of personalized medicine · 2023Article
- Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques.Biosensors · 2023Review
- Trends in Application of SERS Substrates beyond Ag and Au, and Their Role in Bioanalysis.Biosensors · 2022Review
- Raman spectroscopy: current applications in breast cancer diagnosis, challenges and future prospects.British journal of cancer · 2022Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Surface-enhanced Raman spectroscopy (SERS) is a surface-sensitive technique that enhances Raman scattering by molecules adsorbed on nanostructures. The advantages of using SERS include high detection sensibility and fast analysis, thus it is a potentially promising tool for sensing metabolic cancer molecules in trace amounts. To explore this new method of lung cancer detection, we analyzed saliva samples from 61 lung cancer patients and 66 healthy controls. An SERS system and a nano-modified chip were used in this study. Statistics were analyzed using support vector machine (SVM) and random forest algorithms. The leave-one-out algorithm was used based on SVM results to analyze differences in saliva between lung cancer patients and controls. There was a significant difference between the saliva of patients with lung cancer and healthy controls using the Raman spectrum; the intensity of the spectral line in lung cancer patients was weaker than in controls and 12 characteristic peaks were detected. Saliva SERS peaks have been characterized to refer to tissues, body fluids, and biological standard Raman peaks, but it is difficult to identify molecules with current information. The sensitivity and specificity of Raman spectroscopy data and SVM classification results of lung cancer patients and normal saliva samples were both 100%. Using the leave-one-out algorithm, the sensitivity was 95.08% and the specificity was 100%. The sensitivity of the random forest method was 96.72% and specificity was 100%. Our results show that SERS has the potential to detect lung cancer.
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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.