Show simple item record

dc.contributor.authorSikosek, Tobias
dc.contributor.authorHoros, Rastislav
dc.contributor.authorTrudzinski, Franziska
dc.contributor.authorJehn, Julia
dc.contributor.authorFrank, Maurice
dc.contributor.authorRajakumar, Timothy
dc.contributor.authorKlotz, Laura V
dc.contributor.authorMercaldo, Nathaniel
dc.contributor.authorKahraman, Mustafa
dc.contributor.authorHeuvelman, Marco
dc.contributor.authorTaha, Yasser
dc.contributor.authorGerwing, Jennifer
dc.contributor.authorSkottke, Jasmin
dc.contributor.authorDaniel-Moreno, Alberto
dc.contributor.authorSanchez-Delgado, Marta
dc.contributor.authorBender, Sophie
dc.contributor.authorRudolf, Christina
dc.contributor.authorHinkfoth, Franziska
dc.contributor.authorTikk, Kaja
dc.contributor.authorSchenz, Judith
dc.contributor.authorWeigand, Markus A
dc.contributor.authorFeindt, Peter
dc.contributor.authorSchumann, Christian
dc.contributor.authorChristopoulos, Petros
dc.contributor.authorWinter, Hauke
dc.contributor.authorKreuter, Michael
dc.contributor.authorSchneider, Marc A
dc.contributor.authorMuley, Thomas
dc.contributor.authorWalterspacher, Stephan
dc.contributor.authorSchuler, Martin
dc.contributor.authorDarwiche, Kaid
dc.contributor.authorTaube, Christian
dc.contributor.authorHegedus, Balazs
dc.contributor.authorRabe, Klaus F
dc.contributor.authorRieger-Christ, Kimberly
dc.contributor.authorJacobsen, Francine L
dc.contributor.authorAigner, Clemens
dc.contributor.authorReck, Martin
dc.contributor.authorBankier, Alexander A
dc.contributor.authorSharma, Amita
dc.contributor.authorSteinkraus, Bruno R
dc.identifier.citationSikosek T, Horos R, Trudzinski F, Jehn J, Frank M, Rajakumar T, Klotz LV, Mercaldo N, Kahraman M, Heuvelman M, Taha Y, Gerwing J, Skottke J, Daniel-Moreno A, Sanchez-Delgado M, Bender S, Rudolf C, Hinkfoth F, Tikk K, Schenz J, Weigand MA, Feindt P, Schumann C, Christopoulos P, Winter H, Kreuter M, Schneider MA, Muley T, Walterspacher S, Schuler M, Darwiche K, Taube C, Hegedus B, Rabe KF, Rieger-Christ K, Jacobsen FL, Aigner C, Reck M, Bankier AA, Sharma A, Steinkraus BR. Early Detection of Lung Cancer Using Small RNAs. J Thorac Oncol. 2023 Nov;18(11):1504-1523. doi: 10.1016/j.jtho.2023.07.005. Epub 2023 Jul 16. PMID: 37437883.en_US
dc.description.abstractIntroduction: Lung cancer remains the deadliest cancer in the world, and lung cancer survival is heavily dependent on tumor stage at the time of detection. Low-dose computed tomography screening can reduce mortality; however, annual screening is limited by low adherence in the United States of America and still not broadly implemented in Europe. As a result, less than 10% of lung cancers are detected through existing programs. Thus, there is a great need for additional screening tests, such as a blood test, that could be deployed in the primary care setting. Methods: We prospectively recruited 1384 individuals meeting the National Lung Screening Trial demographic eligibility criteria for lung cancer and collected stabilized whole blood to enable the pipetting-free collection of material, thus minimizing preanalytical noise. Ultra-deep small RNA sequencing (20 million reads per sample) was performed with the addition of a method to remove highly abundant erythroid RNAs, and thus open bandwidth for the detection of less abundant species originating from the plasma or the immune cellular compartment. We used 100 random data splits to train and evaluate an ensemble of logistic regression classifiers using small RNA expression of 943 individuals, discovered an 18-small RNA feature consensus signature (miLung), and validated this signature in an independent cohort (441 individuals). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin. Results: We generated diagnostic models and report a median receiver-operating characteristic area under the curve of 0.86 (95% confidence interval [CI]: 0.84-0.86) in the discovery cohort and generalized performance of 0.83 in the validation cohort. Diagnostic performance increased in a stage-dependent manner ranging from 0.73 (95% CI: 0.71-0.76) for stage I to 0.90 (95% CI: 0.89-0.90) for stage IV in the discovery cohort and from 0.76 to 0.86 in the validation cohort. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased after surgery with curative intent. In additional experiments, results of dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted through home sampling. Conclusions: These data suggest the potential of a small RNA-based blood test as a viable alternative to low-dose computed tomography screening for early detection of smoking-associated lung cancer.en_US
dc.relation.ispartofJournal of Thoracic Oncologyen_US
dc.rightsCopyright 2023 International Association for the Study of Lung Cancer. Published by Elsevier Inc. This is an open access article under the CC BY license (
dc.rightsAttribution 4.0 International*
dc.subjectBlood testen_US
dc.subjectEarly detectionen_US
dc.subjectLiquid biopsyen_US
dc.subjectSmall RNAen_US
dc.titleEarly Detection of Lung Cancer Using Small RNAsen_US
dc.typeJournal Articleen_US
dc.source.journaltitleJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
dc.source.countryUnited States
dc.identifier.journalJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer

Files in this item

Publisher version

This item appears in the following Collection(s)

Show simple item record

Copyright 2023 International Association for the Study of Lung Cancer.
Published by Elsevier Inc. This is an open access article under the
CC BY license (
Except where otherwise noted, this item's license is described as Copyright 2023 International Association for the Study of Lung Cancer. Published by Elsevier Inc. This is an open access article under the CC BY license (