ArticleeLife2022
Serum RNAs can predict lung cancer up to 10 years prior to diagnosis.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- tRNA-derived fragments: mechanism of gene regulation and clinical application in lung cancer.Cellular oncology (Dordrecht, Netherlands) · 2024Pooled it
- A Panel of Circulating Exosomal sncRNAs Associated With Lung Cancer Risk up to 10 Years in Advance.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Lung cancer screening for never smokers: current evidence and future directions.Singapore medical journal · 2026Review
- Recommendations for Validating Omics Prediction Models: Insights from a Lung Cancer RNA Biomarker Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025Article
- Article
- Networks of pre-diagnostic circulating RNA in testicular germ cell tumour.Scientific reports · 2025Article
- Changes in the Repertoire of tRNA-Derived Fragments in Different Blood Cell Populations.Life (Basel, Switzerland) · 2024Article
- Article
- Improved lung cancer classification by employing diverse molecular features of microRNAs.Heliyon · 2024Article
- tRNA-derived small RNAs (tsRNAs): establishing their dominance in the regulation of human cancer.Frontiers in genetics · 2024Review
- Validation of miRNA signatures for ovarian cancer earlier detection in the pre-diagnosis setting using machine learning approaches.Frontiers in oncology · 2024Article
- Accurate microRNA annotation of animal genomes using trained covariance models of curated microRNA complements in MirMachine.Cell genomics · 2023Article
- Emerging roles of tRNA-derived fragments in cancer.Molecular cancer · 2023Review
- Blood-Based mRNA Tests as Emerging Diagnostic Tools for Personalised Medicine in Breast Cancer.Cancers · 2023Review
- Increased levels of microRNA-320 in blood serum and plasma is associated with imminent and advanced lung cancer.Molecular oncology · 2023Article
- AI/ML advances in non-small cell lung cancer biomarker discovery.Frontiers in oncology · 2023Review
- Serum transfer RNA-derived fragment tRF-31-79MP9P9NH57SD acts as a novel diagnostic biomarker for non-small cell lung cancer.Journal of clinical laboratory analysis · 2022Article
- Rolling circle reverse transcription enables high fidelity nanopore sequencing of small RNA.PloS one · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer (LC) prognosis is closely linked to the stage of disease when diagnosed. We investigated the biomarker potential of serum RNAs for the early detection of LC in smokers at different prediagnostic time intervals and histological subtypes. In total, 1061 samples from 925 individuals were analyzed. RNA sequencing with an average of 18 million reads per sample was performed. We generated machine learning models using normalized serum RNA levels and found that smokers later diagnosed with LC in 10 years can be robustly separated from healthy controls regardless of histology with an average area under the ROC curve (AUC) of 0.76 (95% CI, 0.68-0.83). Furthermore, the strongest models that took both time to diagnosis and histology into account successfully predicted non-small cell LC (NSCLC) between 6 and 8 years, with an AUC of 0.82 (95% CI, 0.76-0.88), and SCLC between 2 and 5 years, with an AUC of 0.89 (95% CI, 0.77-1.0), before diagnosis. The most important separators were microRNAs, miscellaneous RNAs, isomiRs, and tRNA-derived fragments. We have shown that LC can be detected years before diagnosis and manifestation of disease symptoms independently of histological subtype. However, the highest AUCs were achieved for specific subtypes and time intervals before diagnosis. The collection of models may therefore also predict the severity of cancer development and its histology. Our study demonstrates that serum RNAs can be promising prediagnostic biomarkers in an LC screening setting, from early detection to risk assessment.
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