ArticleScience translational medicine2013
A blood-based proteomic classifier for the molecular characterization of pulmonary nodules.
Article in Science translational medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers.
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Who cites it
111 citing papers in PubMed, 195 citations in OpenAlex.
- Accurate diagnosis of pulmonary nodules using a noninvasive DNA methylation test.The Journal of clinical investigation · 2021Trial
- Validation of the SHOX2/PTGER4 DNA Methylation Marker Panel for Plasma-Based Discrimination between Patients with Malignant and Nonmalignant Lung Disease.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2017Trial
- Is This Calculator Broken?: Comparative Performance of Lung Nodule Risk Assessment Calculators in a High-Prevalence Cohort.CHEST pulmonary · 2026Article
- Article
- External Validation of Plasma Glycosaminoglycans as Biomarkers to Improve Lung Cancer Risk Stratification.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025Article
- An integrated proteomic classifier to distinguish benign from malignant pulmonary nodules.Clinical proteomics · 2025Article
- A clinically effective model based on cell-free DNA methylation and low-dose CT for risk stratification of pulmonary nodules.Cell reports. Medicine · 2024Article
- Mass Spectrometry-Based Proteomics for Classification and Treatment Optimisation of Triple Negative Breast Cancer.Journal of personalized medicine · 2024Review
- New perspectives on inoperable early-stage lung cancer management: Clinicians, physicists, and biologists unveil strategies and insights.The journal of liquid biopsy · 2024Review
- The transition from genomics to phenomics in personalized population health.Nature reviews. Genetics · 2024Review
- Cheaper, faster, simpler trypsin digestion for high-throughput targeted protein quantification.Journal of mass spectrometry and advances in the clinical lab · 2023Article
- Clinical Proteomics for Solid Organ Tissues.Molecular & cellular proteomics : MCP · 2023Article
- Impact of an integrated classifier using biomarkers, clinical and imaging factors on clinical decisions making for lung nodules.Journal of thoracic disease · 2023Article
- A simple and available measurement of onco-sEV dsDNA to protein ratio as a potential tumor marker.BMC cancer · 2023Article
- Metabolic biomarkers in lung cancer screening and early diagnosis (Review).Oncology letters · 2023Review
- Simultaneous Detection of Tumor Derived Exosomal Protein-MicroRNA Pairs with an Exo-PROS Biosensor for Cancer Diagnosis.ACS nano · 2023Article
- The Importance of the Immune System and Molecular Cell Signaling Pathways in the Pathogenesis and Progression of Lung Cancer.International journal of molecular sciences · 2023Review
- Assessing a biomarker's ability to reduce invasive procedures in patients with benign lung nodules: Results from the ORACLE study.PloS one · 2023Observational
- Article
- Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
51 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
23 authors at 5 institutions in 1 country.
Funding
Abstract
Each year, millions of pulmonary nodules are discovered by computed tomography and subsequently biopsied. Because most of these nodules are benign, many patients undergo unnecessary and costly invasive procedures. We present a 13-protein blood-based classifier that differentiates malignant and benign nodules with high confidence, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules. Using a systems biology strategy, we identified 371 protein candidates and developed a multiple reaction monitoring (MRM) assay for each. The MRM assays were applied in a three-site discovery study (n = 143) on plasma samples from patients with benign and stage IA lung cancer matched for nodule size, age, gender, and clinical site, producing a 13-protein classifier. The classifier was validated on an independent set of plasma samples (n = 104), exhibiting a negative predictive value (NPV) of 90%. Validation performance on samples from a nondiscovery clinical site showed an NPV of 94%, indicating the general effectiveness of the classifier. A pathway analysis demonstrated that the classifier proteins are likely modulated by a few transcription regulators (NF2L2, AHR, MYC, and FOS) that are associated with lung cancer, lung inflammation, and oxidative stress networks. The classifier score was independent of patient nodule size, smoking history, and age, which are risk factors used for clinical management of pulmonary nodules. Thus, this molecular test provides a potential complementary tool to help physicians in lung cancer diagnosis.
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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.