CTCs Detection and Whole-exome Sequencing Might Be Used to Differentiate Benign and Malignant Pulmonary Nodules
(2023) In Chinese Journal of Lung Cancer 26(6). p.449-460- Abstract
Background and objective Low-density computed tomography (LDCT) improved early lung cancer diagnosis but introduces an excess of false-positive pulmonary nodules data. Hence, accurate diagnosis of early-stage lung cancer remains challenging. The purpose of the study was to assess the feasibility of using circulating tumour cells (CTCs) to differentiate malignant from benign pulmonary nodules. Materials and methods 122 patients with suspected malignant pulmonary nodules detected on chest CT in preparation for surgery were prospectively recruited. Peripheral blood samples were collected before surgery, and CTCs were identified upon isolation by size of epithelial tumour cells and morphological analysis. Laser capture microdissection,... (More)
Background and objective Low-density computed tomography (LDCT) improved early lung cancer diagnosis but introduces an excess of false-positive pulmonary nodules data. Hence, accurate diagnosis of early-stage lung cancer remains challenging. The purpose of the study was to assess the feasibility of using circulating tumour cells (CTCs) to differentiate malignant from benign pulmonary nodules. Materials and methods 122 patients with suspected malignant pulmonary nodules detected on chest CT in preparation for surgery were prospectively recruited. Peripheral blood samples were collected before surgery, and CTCs were identified upon isolation by size of epithelial tumour cells and morphological analysis. Laser capture microdissection, MALBAC amplification, and whole-exome sequencing were performed on 8 samples. The diagnostic efficacy of CTCs counting, and the genomic variation profile of benign and malignant CTCs samples were analysed. Results Using 2.5 cells/5 mL as the cut-off value, the area under the receiver operating characteristic curve was of 0.651 (95% confidence interval: 0.538-0.764), with a sensitivity and specificity of 0.526 and 0.800, respectively, and positive and negative predictive values of 91.1% and 30.3%, respectively. Distinct sequence variations differences in DNA damage repair-related and driver genes were observed in benign and malignant samples. TP53 mutations were identified in CTCs of four malignant cases; in particular, g.7578115T>C, g.7578645C>T, and g.7579472G>C were exclusively detected in all four malignant samples. Conclusion CTCs play an ancillary role in the diagnosis of pulmonary nodules. TP53 mutations in CTCs might be used to identify benign and malignant pulmonary nodules.
(Less)
- author
- Xu, Changdan
; Xu, Xiaohong
; Shao, Weipeng
; Sun, Hongliang
; Liu, Xiaohong
; Feng, Hongxiang
; Zuo, Xianbo
; Gao, Jingyang
; Wang, Guohui
; Yang, Xiongtao
; Gu, Runchuan
LU
; Ge, Shutong
; Wang, Shijie
; Gao, Liwei
and Zhu, Guangying
(Less) - organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Chest computed tomography, Circulating tumour cells, Lung nodule, TP53, Whole-exome sequencing
- in
- Chinese Journal of Lung Cancer
- volume
- 26
- issue
- 6
- pages
- 12 pages
- publisher
- Chinese Journal of Lung Cancer
- external identifiers
-
- pmid:37488082
- scopus:85165744520
- ISSN
- 1009-3419
- DOI
- 10.3779/j.issn.1009-3419.2023.106.12
- language
- English
- LU publication?
- yes
- id
- 7bf7810d-91d7-40ab-88e6-0f7a87e0b592
- date added to LUP
- 2023-11-21 15:53:57
- date last changed
- 2024-04-18 19:16:59
@article{7bf7810d-91d7-40ab-88e6-0f7a87e0b592,
abstract = {{<p>Background and objective Low-density computed tomography (LDCT) improved early lung cancer diagnosis but introduces an excess of false-positive pulmonary nodules data. Hence, accurate diagnosis of early-stage lung cancer remains challenging. The purpose of the study was to assess the feasibility of using circulating tumour cells (CTCs) to differentiate malignant from benign pulmonary nodules. Materials and methods 122 patients with suspected malignant pulmonary nodules detected on chest CT in preparation for surgery were prospectively recruited. Peripheral blood samples were collected before surgery, and CTCs were identified upon isolation by size of epithelial tumour cells and morphological analysis. Laser capture microdissection, MALBAC amplification, and whole-exome sequencing were performed on 8 samples. The diagnostic efficacy of CTCs counting, and the genomic variation profile of benign and malignant CTCs samples were analysed. Results Using 2.5 cells/5 mL as the cut-off value, the area under the receiver operating characteristic curve was of 0.651 (95% confidence interval: 0.538-0.764), with a sensitivity and specificity of 0.526 and 0.800, respectively, and positive and negative predictive values of 91.1% and 30.3%, respectively. Distinct sequence variations differences in DNA damage repair-related and driver genes were observed in benign and malignant samples. TP53 mutations were identified in CTCs of four malignant cases; in particular, g.7578115T>C, g.7578645C>T, and g.7579472G>C were exclusively detected in all four malignant samples. Conclusion CTCs play an ancillary role in the diagnosis of pulmonary nodules. TP53 mutations in CTCs might be used to identify benign and malignant pulmonary nodules.</p>}},
author = {{Xu, Changdan and Xu, Xiaohong and Shao, Weipeng and Sun, Hongliang and Liu, Xiaohong and Feng, Hongxiang and Zuo, Xianbo and Gao, Jingyang and Wang, Guohui and Yang, Xiongtao and Gu, Runchuan and Ge, Shutong and Wang, Shijie and Gao, Liwei and Zhu, Guangying}},
issn = {{1009-3419}},
keywords = {{Chest computed tomography; Circulating tumour cells; Lung nodule; TP53; Whole-exome sequencing}},
language = {{eng}},
number = {{6}},
pages = {{449--460}},
publisher = {{Chinese Journal of Lung Cancer}},
series = {{Chinese Journal of Lung Cancer}},
title = {{CTCs Detection and Whole-exome Sequencing Might Be Used to Differentiate Benign and Malignant Pulmonary Nodules}},
url = {{http://dx.doi.org/10.3779/j.issn.1009-3419.2023.106.12}},
doi = {{10.3779/j.issn.1009-3419.2023.106.12}},
volume = {{26}},
year = {{2023}},
}