Dataset Information

A novel approach for the non-invasive diagnosis of pulmonary nodules using low-depth whole-genome sequencing of cell-free DNA.

ABSTRACT:

Background

Differentiating between benign and malignant pulmonary nodules is a diagnostic challenge, and inaccurate detection can result in unnecessary invasive procedures. Cell-free DNA (cfDNA) has been successfully utilized to detect various solid tumors. In this study, we developed a genome-wide approach to explore the characteristics of cfDNA sequencing reads obtained by low-depth whole-genome sequencing (LD-WGS) to diagnose pulmonary nodules.

Methods

LD-WGS was performed on cfDNA extracted from 420 plasma samples from individuals with pulmonary nodules that were no more than 30 mm in diameter, as determined by computed tomography (CT). The sequencing read distribution patterns of cfDNA were analyzed and used to establish a model for distinguishing benign from malignant pulmonary nodules.

Results

We proposed the concept of weighted reads distribution difference (WRDD) based on the copy number alterations (CNAs) of cfDNA to construct a benign and malignant diagnostic (BEMAD) algorithm model. In a training cohort of 360 plasma samples, the model achieved an average area under the receiver operating characteristic (ROC) curve (AUC) value of 0.84 in 10-fold cross-validation. The model was validated in an independent cohort of 60 plasma samples, obtaining an AUC value of 0.87. The BEMAD model could distinguish benign from malignant nodules at a sensitivity of 74% and a specificity of 86%. Furthermore, analysis of the critical features of the cfDNA using the BEMAD model identified repeat regions that were associated with microsatellite instability, which is an important indicator of tumorigenesis.

Conclusions

This study provides a novel non-invasive diagnostic approach to discriminate between benign and malignant pulmonary nodules to avoid unnecessary invasive procedures.

SUBMITTER: Zhang B

PROVIDER: S-EPMC9641036 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Publications

A novel approach for the non-invasive diagnosis of pulmonary nodules using low-depth whole-genome sequencing of cell-free DNA.

Zhang Bin B Liang Han H Liu Weiran W Zhou Xinlan X Qiao Sitan S Li Fuqiang F Tian Pengfei P Li Chenguang C Ma Yuchen Y Zhang Hua H Zhang Zhenfa Z Nanjo Shigeki S Russo Alessandro A Puig-Butillé Joan Anton JA Wu Kui K Wang Changli C Zhao Xin X Yue Dongsheng D

Translational lung cancer research 20221001 10

<h4>Background</h4>Differentiating between benign and malignant pulmonary nodules is a diagnostic challenge, and inaccurate detection can result in unnecessary invasive procedures. Cell-free DNA (cfDNA) has been successfully utilized to detect various solid tumors. In this study, we developed a genome-wide approach to explore the characteristics of cfDNA sequencing reads obtained by low-depth whole-genome sequencing (LD-WGS) to diagnose pulmonary nodules.<h4>Methods</h4>LD-WGS was performed on c ...[more]

PMID: 36386459

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Project description:BackgroundThis study aimed to systematically evaluate and compare the diagnostic value of bubble lucency, interface, lobulated margin and spiculation in distinguishing early invasive and preinvasive intrapulmonary ground-glass nodules (GGNs) using evidence-based meta-analysis methods. Dual low-dose targeted perfusion computed tomography (CT) imaging is controversial in the diagnosis of invasive and preinvasive ground-glass nodules. Different studies have different views and opinions. Therefore, it is necessary to conduct a systematic review of this subject in the form of meta-analysis to guide clinical diagnosis and treatment.MethodsPubMed, Web of Science, Cochrane library and Embase were searched for recent documentation on the diagnostic value of different signs in invasive and preinvasive pulmonary GGNs. CT imaging signs of bubble lucency, speculation, interface, lobulated margin, and spiculation were used as diagnostic references to discriminate pre-invasive and invasive disease. The sensitivity, specificity, summary receiver operating characteristic (SROC) curves, and the area under the SROC curve (AUC) were calculated to evaluate diagnostic efficiency.ResultsThe diagnostic sensitivity and specificity using bubble lucency as a reference of invasive ground-glass opacity (GGO) discrimination was 0.33 (0.24-0.44) and 0.74 (0.62-0.83) respectively. For interface, lobulated margin, and speculation, the diagnostic sensitivity were 0.30 (0.21-0.41), 0.49 (0.39-0.60) and 0.22 (0.14-0.33); and the specificity were 0.83 (0.74-0.89), 0.66 (0.49-0.80) and 0.86 (0.67-0.95). The pooled ROC curve was drawn by sensitivity against 1-specificity using Stata version 15.0. The area under the ROC curve (AUC) values were 0.53, 0.60, 0.58, and 0.43 for bubble lucency, speculation, lobulated margin, and pleural indentation of GGO for discriminating pre-invasive and invasive disease.ConclusionsThe diagnostic value of a single CT imaging sign of GGO, such as bubble lucency, speculation, interface, lobulated margin, and spiculation is limited for discriminating pre-invasive and invasive disease because of low sensitivity, specificity, and AUC.

Dataset Information

A novel approach for the non-invasive diagnosis of pulmonary nodules using low-depth whole-genome sequencing of cell-free DNA.

Background

Methods

Results

Conclusions

Publications

A novel approach for the non-invasive diagnosis of pulmonary nodules using low-depth whole-genome sequencing of cell-free DNA.

Similar Datasets

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