Serum RNAs can predict lung cancer up to 10 years prior to diagnosis
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 an...
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eLife Sciences Publications Ltd
2022-02-01
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Online Access: | https://elifesciences.org/articles/71035 |
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author | Sinan U Umu Hilde Langseth Verena Zuber Åslaug Helland Robert Lyle Trine B Rounge |
author_facet | Sinan U Umu Hilde Langseth Verena Zuber Åslaug Helland Robert Lyle Trine B Rounge |
author_sort | Sinan U Umu |
collection | DOAJ |
description | 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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format | Article |
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institution | Directory Open Access Journal |
issn | 2050-084X |
language | English |
last_indexed | 2024-04-12T02:04:13Z |
publishDate | 2022-02-01 |
publisher | eLife Sciences Publications Ltd |
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spelling | doaj.art-0e79fdf6757e47629d180d1d01d441522022-12-22T03:52:34ZengeLife Sciences Publications LtdeLife2050-084X2022-02-011110.7554/eLife.71035Serum RNAs can predict lung cancer up to 10 years prior to diagnosisSinan U Umu0https://orcid.org/0000-0001-8081-7819Hilde Langseth1Verena Zuber2Åslaug Helland3Robert Lyle4Trine B Rounge5https://orcid.org/0000-0003-2677-2722Department of Research, Cancer Registry of Norway, Oslo, NorwayDepartment of Research, Cancer Registry of Norway, Oslo, Norway; Department of Epidemiology and Biostatistics, Imperial College London, London, United KingdomDepartment of Epidemiology and Biostatistics, Imperial College London, London, United KingdomDepartment of Oncology, Oslo University Hospital, Oslo, Norway; Institute for Cancer Research, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, NorwayDepartment of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway; Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, NorwayDepartment of Research, Cancer Registry of Norway, Oslo, Norway; Department of Informatics, University of Oslo, Oslo, NorwayLung 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.https://elifesciences.org/articles/71035lung cancerbiomarkerRNAprediagnostic sampleshuman serum |
spellingShingle | Sinan U Umu Hilde Langseth Verena Zuber Åslaug Helland Robert Lyle Trine B Rounge Serum RNAs can predict lung cancer up to 10 years prior to diagnosis eLife lung cancer biomarker RNA prediagnostic samples human serum |
title | Serum RNAs can predict lung cancer up to 10 years prior to diagnosis |
title_full | Serum RNAs can predict lung cancer up to 10 years prior to diagnosis |
title_fullStr | Serum RNAs can predict lung cancer up to 10 years prior to diagnosis |
title_full_unstemmed | Serum RNAs can predict lung cancer up to 10 years prior to diagnosis |
title_short | Serum RNAs can predict lung cancer up to 10 years prior to diagnosis |
title_sort | serum rnas can predict lung cancer up to 10 years prior to diagnosis |
topic | lung cancer biomarker RNA prediagnostic samples human serum |
url | https://elifesciences.org/articles/71035 |
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