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Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer
by
Guo, Liuning
, Sun, Xiwen
, Yang, Minglei
, Chen, Tao
, She, Yunlang
, Song, Yongxiang
, Zhao, Mengmeng
, Zhao, Guofang
, Deng, Jiajun
, Hu, Xinlei
, Yu, Bentong
, Ma, Minjie
, He, Bingxi
, Wang, Tingting
, Xie, Dan
, Qu, Wendong
, Zhao, Deping
, He, Yiming
, Yan, Ziyue
, Chen, Chang
, Liu, Lunxu
, Zhong, Yifan
, Wang, Yang
, Xue, Gang
, Li, Shenghui
, Zhang, Jun
in
49/22
/ 49/23
/ 5-Methylcytosine - metabolism
/ 631/67/1612
/ 631/67/2322
/ 692/53/2421
/ Aged
/ Biological analysis
/ Biomarkers, Tumor - genetics
/ Cell-Free Nucleic Acids - genetics
/ Diagnosis
/ DNA Methylation
/ Female
/ Genomics - methods
/ Humanities and Social Sciences
/ Humans
/ Lung cancer
/ Lung Neoplasms - diagnosis
/ Lung Neoplasms - genetics
/ Lung nodules
/ Male
/ Malignancy
/ Middle Aged
/ multidisciplinary
/ Multiomics
/ Nodules
/ Optimization
/ Radiomics
/ Science
/ Science (multidisciplinary)
2025
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Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer
by
Guo, Liuning
, Sun, Xiwen
, Yang, Minglei
, Chen, Tao
, She, Yunlang
, Song, Yongxiang
, Zhao, Mengmeng
, Zhao, Guofang
, Deng, Jiajun
, Hu, Xinlei
, Yu, Bentong
, Ma, Minjie
, He, Bingxi
, Wang, Tingting
, Xie, Dan
, Qu, Wendong
, Zhao, Deping
, He, Yiming
, Yan, Ziyue
, Chen, Chang
, Liu, Lunxu
, Zhong, Yifan
, Wang, Yang
, Xue, Gang
, Li, Shenghui
, Zhang, Jun
in
49/22
/ 49/23
/ 5-Methylcytosine - metabolism
/ 631/67/1612
/ 631/67/2322
/ 692/53/2421
/ Aged
/ Biological analysis
/ Biomarkers, Tumor - genetics
/ Cell-Free Nucleic Acids - genetics
/ Diagnosis
/ DNA Methylation
/ Female
/ Genomics - methods
/ Humanities and Social Sciences
/ Humans
/ Lung cancer
/ Lung Neoplasms - diagnosis
/ Lung Neoplasms - genetics
/ Lung nodules
/ Male
/ Malignancy
/ Middle Aged
/ multidisciplinary
/ Multiomics
/ Nodules
/ Optimization
/ Radiomics
/ Science
/ Science (multidisciplinary)
2025
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Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer
by
Guo, Liuning
, Sun, Xiwen
, Yang, Minglei
, Chen, Tao
, She, Yunlang
, Song, Yongxiang
, Zhao, Mengmeng
, Zhao, Guofang
, Deng, Jiajun
, Hu, Xinlei
, Yu, Bentong
, Ma, Minjie
, He, Bingxi
, Wang, Tingting
, Xie, Dan
, Qu, Wendong
, Zhao, Deping
, He, Yiming
, Yan, Ziyue
, Chen, Chang
, Liu, Lunxu
, Zhong, Yifan
, Wang, Yang
, Xue, Gang
, Li, Shenghui
, Zhang, Jun
in
49/22
/ 49/23
/ 5-Methylcytosine - metabolism
/ 631/67/1612
/ 631/67/2322
/ 692/53/2421
/ Aged
/ Biological analysis
/ Biomarkers, Tumor - genetics
/ Cell-Free Nucleic Acids - genetics
/ Diagnosis
/ DNA Methylation
/ Female
/ Genomics - methods
/ Humanities and Social Sciences
/ Humans
/ Lung cancer
/ Lung Neoplasms - diagnosis
/ Lung Neoplasms - genetics
/ Lung nodules
/ Male
/ Malignancy
/ Middle Aged
/ multidisciplinary
/ Multiomics
/ Nodules
/ Optimization
/ Radiomics
/ Science
/ Science (multidisciplinary)
2025
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Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer
Journal Article
Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer
2025
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Overview
Diagnosing lung cancer from indeterminate pulmonary nodules (IPLs) remains challenging. In this multi-institutional study involving 2032 participants with IPLs, we integrate the clinical, radiomic with circulating cell-free DNA fragmentomic features in 5-methylcytosine (5mC)-enriched regions to establish a multiomics model (clinic-RadmC) for predicting the malignancy risk of IPLs. The clinic-RadmC yields an area-under-the-curve (AUC) of 0.923 on the external test set, outperforming the single-omics models, and models that only combine clinical features with radiomic, or fragmentomic features in 5mC-enriched regions (
p
< 0.050 for all). The superiority of the clinic-RadmC maintains well even after adjusting for clinic-radiological variables. Furthermore, the clinic-RadmC-guided strategy could reduce the unnecessary invasive procedures for benign IPLs by 10.9% ~ 35%, and avoid the delayed treatment for lung cancer by 3.1% ~ 38.8%. In summary, our study indicates that the clinic-RadmC provides a more effective and noninvasive tool for optimizing lung cancer diagnoses, thus facilitating the precision interventions.
Diagnosis of lung cancer from indeterminate pulmonary nodules remains challenging. Here, the authors develop a multi-omics signature to identify oncogenic nodules, and prevent unnecessary procedures.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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