A multiomics dataset of paired CT image and plasma cell-free DNA end motif for patients with pulmonary nodules
Diagnosing lung cancer at a curable stage offers the opportunity for a favorable prognosis. The emerging epigenomics analysis on plasma cell-free DNA (cfDNA), including 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) modifications, has acted as a promising approach facilitating the identification of lung cancer. And, integrating 5mC biomarker with chest computed tomography (CT) image features could optimize the diagnosis of lung cancer, exceeding the performance of models built on single feature. However, the clinical applicability of integrated markers might be limited by the potential risk of overfitting due to small sample size. Hence, we prospectively collected peripheral blood sample and the paired chest CT images of 2032 patients with indeterminate pulmonary nodules across 5 centers, and constructed a large-scale, multi-institutional, multiomics database that encompass CT imaging data and plasma cfDNA fragmentomic in 5mC-, 5hmC-enriched regions. To our best knowledge, this dataset is the first radio-epigenomic dataset with the largest sample size, and provides multi-dimensional insights for early diagnosis of lung cancer, facilitating the individuated management for lung cancer.
Authors
- Bentong Yu (ORCID: https://orcid.org/0000-0001-6396-1931)
- Yifan Zhong (ORCID: https://orcid.org/0000-0002-5126-9021)
- Ziyue Yan
- Yiming He (ORCID: https://orcid.org/0000-0002-9033-8069)
- Deping Zhao (ORCID: https://orcid.org/0000-0001-5242-4233)
- Shenghui Li
- Minglei Yang (ORCID: https://orcid.org/0000-0003-0884-9829)
- Liuning Guo
- Minjie Ma (ORCID: https://orcid.org/0000-0002-5570-1360)
- Wendong Qu
- Bingxi He (ORCID: https://orcid.org/0000-0003-4012-8458)
- Lunxu Liu (ORCID: https://orcid.org/0000-0003-3964-5378)
- Jiajun Deng (ORCID: https://orcid.org/0000-0002-6834-0322)
- Tao Chen (ORCID: https://orcid.org/0000-0003-3295-7192)
- Yang Wang (ORCID: https://orcid.org/0000-0001-9404-2372)
- Jun Zhang (ORCID: https://orcid.org/0000-0002-4379-3616)
- Tingting Wang (ORCID: https://orcid.org/0000-0002-3682-3039)
- Chang Chen (ORCID: https://orcid.org/0000-0003-2841-1250)
- Xiwen Sun (ORCID: https://orcid.org/0000-0002-0006-0930)
- Yongxiang Song (ORCID: https://orcid.org/0000-0003-1022-0202)
- Xinlei Hu (ORCID: https://orcid.org/0000-0002-4144-8923)
- Mengmeng Zhao (ORCID: https://orcid.org/0000-0002-9682-6450)
- Dan Xie
- Guofang Zhao (ORCID: https://orcid.org/0000-0002-4172-1862)
- Gang Xue
- Yunlang She (ORCID: https://orcid.org/0000-0003-2841-1250)
Institutions
- Tongji University (CN)
- Nanchang University (CN)
- Sun Yat-sen University (CN)
- Chinese Academy of Sciences (CN)
- Sichuan University (CN)
- Fudan University (CN)
- West China Hospital of Sichuan University (CN)
- Shandong Institute of Automation (CN)
- Ningbo No. 2 Hospital (CN)
- Zhongshan Hospital (CN)
- Shanghai Pulmonary Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- First Hospital of Lanzhou University (CN)
- First Affiliated Hospital of Nanchang University (CN)
- Affiliated Hospital of Zunyi Medical College (CN)
- Lanzhou University (CN)
- Beihang University (CN)
- Ministry of Industry and Information Technology (CN)
Publication Details
- Journal
- Scientific Data
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1038/s41597-025-04912-1
- Citations
- 2
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 3.04
Funders
- National Natural Science Foundation of China