Circulating tumor DNA- and cancer tissue-based next-generation sequencing reveals comparable consistency in targeted gene mutations for advanced or metastatic non-small cell lung cancer.
10.1097/CM9.0000000000003117
- Author:
Weijia HUANG
1
;
Kai XU
1
;
Zhenkun LIU
1
;
Yifeng WANG
1
;
Zijia CHEN
1
;
Yanyun GAO
2
;
Renwang PENG
2
;
Qinghua ZHOU
1
Author Information
1. Lung Cancer Center/Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
2. Department of General Thoracic Surgery, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland.
- Publication Type:Journal Article
- Keywords:
Circulating tumor DNA;
Next-generation sequencing;
Non-small cell lung cancer;
Targeted gene mutations
- MeSH:
Humans;
Carcinoma, Non-Small-Cell Lung/pathology*;
Circulating Tumor DNA/blood*;
High-Throughput Nucleotide Sequencing/methods*;
Female;
Male;
Lung Neoplasms/pathology*;
Middle Aged;
Mutation/genetics*;
Aged;
Adult;
Aged, 80 and over
- From:
Chinese Medical Journal
2025;138(7):851-858
- CountryChina
- Language:English
-
Abstract:
BACKGROUND:Molecular subtyping is an essential complementarity after pathological analyses for targeted therapy. This study aimed to investigate the consistency of next-generation sequencing (NGS) results between circulating tumor DNA (ctDNA)-based and tissue-based in non-small cell lung cancer (NSCLC) and identify the patient characteristics that favor ctDNA testing.
METHODS:Patients who diagnosed with NSCLC and received both ctDNA- and cancer tissue-based NGS before surgery or systemic treatment in Lung Cancer Center, Sichuan University West China Hospital between December 2017 and August 2022 were enrolled. A 425-cancer panel with a HiSeq 4000 NGS platform was used for NGS. The unweighted Cohen's kappa coefficient was employed to discriminate the high-concordance group from the low-concordance group with a cutoff value of 0.6. Six machine learning models were used to identify patient characteristics that relate to high concordance between ctDNA-based and tissue-based NGS.
RESULTS:A total of 85 patients were enrolled, of which 22.4% (19/85) had stage III disease and 56.5% (48/85) had stage IV disease. Forty-four patients (51.8%) showed consistent gene mutation types between ctDNA-based and tissue-based NGS, while one patient (1.2%) tested negative in both approaches. Patients with advanced diseases and metastases to other organs would be suitable for the ctDNA-based NGS, and the generalized linear model showed that T stage, M stage, and tumor mutation burden were the critical discriminators to predict the consistency of results between ctDNA-based and tissue-based NGS.
CONCLUSION:ctDNA-based NGS showed comparable detection performance in the targeted gene mutations compared with tissue-based NGS, and it could be considered in advanced or metastatic NSCLC.
