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基于亚洲人群,通过下一代测序的116基因检测板鉴定的多原发性肺癌的不同预后。

Different prognosis of multiple lung cancer identified by 116-gene panel by next-generation sequencing based on an Asian population.

作者信息

Ni Chen-Hui, Wang Mu-Ting, Lin Ping-Hua, Lu Yan-Qi, Chen Yi-Peng, Zheng Wei, Chen Yuan-Zhong, Yang Chang-Ping, Chen Chun, Zheng Bin

机构信息

Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, China.

Key Laboratory of Cardio-Thoracic Surgery (Fujian Medical University), Fujian Province University, Fuzhou, China.

出版信息

Transl Lung Cancer Res. 2025 May 30;14(5):1699-1714. doi: 10.21037/tlcr-2024-1160. Epub 2025 May 27.

DOI:10.21037/tlcr-2024-1160
PMID:40535087
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12170254/
Abstract

BACKGROUND

Patients with multiple lung cancer are becoming more common. The optimal criterion to distinguish multiple primary lung cancer (MPLC) from intrapulmonary metastases (IPM) is still unclear. In this study, we try to distinguish between MPLC and IPM and investigate their prognosis and risk factors.

METHODS

This study was a retrospective analysis of patients with at least two malignant resected nodules in three medical centers from January 2019 to December 2019. Fifty-three patients with 130 lesions were enrolled and tested with 10-gene and 116-gene panels using next-generation sequencing (NGS). Disease-free survival (DFS) was defined as the time from surgery to either the date of the first recurrence (local or distant) or the last follow-up. The follow-up period was up to October 31, 2024. Tumor mutations were identified for each gene using the 116-gene and 10-gene panels, and clonal relatedness was identified by mutational profiling. Univariate and multivariate Cox regression analyses were conducted to identify independent risk factors for DFS.

RESULTS

Fifty-three cases with 130 lesions met the inclusion criteria. A total of 16 recurrences were identified during follow-up. The 3- and 5-year DFS was 77.4% and 69.8%, respectively. According to the 116-gene panel, 35 (66.1%) cases favored MPLC, and 18 cases (33.9%) favored IPM on the basis of shared mutations. There was no difference in the 3-year DFS (82.9% 66.7%, log-rank P=0.22), while there was an obvious difference in the 5-year DFS (80% 60%, log-rank P=0.02). Univariate analysis showed alkaline phosphatase and forced expiratory volume in the first second percentage (FEV1%) as risk factors for metastasis (P=0.03 and P=0.003). Multivariate analysis showed that FEV1% was an independent factor (P=0.001). Cox regression analysis showed that the positive covariates were as follows: early stage [hazard ratio (HR) =4.192; 95% confidence interval (CI): 1.378 to 12.749; P=0.01] and MPLC (HR =0.187; 95% CI: 0.057 to 0.613; P=0.006).

CONCLUSIONS

NGS-based 116-gene panel classification can improve the accuracy of diagnosing MPLC and IPM. The diagnosis of IPM was associated with poor prognosis in Asian population.

摘要

背景

多发性肺癌患者越来越常见。区分多原发性肺癌(MPLC)和肺内转移瘤(IPM)的最佳标准仍不明确。在本研究中,我们试图区分MPLC和IPM,并调查它们的预后及危险因素。

方法

本研究是一项对2019年1月至2019年12月期间在三个医疗中心至少有两个恶性切除结节的患者进行的回顾性分析。纳入了53例患者的130个病灶,使用二代测序(NGS)对其进行10基因和116基因检测。无病生存期(DFS)定义为从手术到首次复发(局部或远处)日期或最后一次随访的时间。随访期至2024年10月31日。使用116基因和10基因检测识别每个基因的肿瘤突变,并通过突变谱分析确定克隆相关性。进行单因素和多因素Cox回归分析以确定DFS的独立危险因素。

结果

53例患者的130个病灶符合纳入标准。随访期间共发现16例复发。3年和5年DFS分别为77.4%和69.8%。根据116基因检测,基于共享突变,35例(66.1%)倾向于MPLC,18例(33.9%)倾向于IPM。3年DFS无差异(82.9%对66.7%,对数秩检验P = 0.22),而5年DFS有明显差异(80%对60%,对数秩检验P = 0.02)。单因素分析显示碱性磷酸酶和第1秒用力呼气容积百分比(FEV1%)是转移的危险因素(P = 0.03和P = 0.003)。多因素分析显示FEV1%是独立因素(P = 0.001)。Cox回归分析显示阳性协变量如下:早期[风险比(HR)= 4.192;95%置信区间(CI):1.378至12.749;P = 0.01]和MPLC(HR = 0.187;95% CI:0.057至0.613;P = 0.006)。

结论

基于NGS的116基因检测分类可提高MPLC和IPM诊断的准确性。在亚洲人群中,IPM的诊断与预后不良相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/7a146111945f/tlcr-14-05-1699-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/022bea360824/tlcr-14-05-1699-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/f98286f60ebb/tlcr-14-05-1699-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/0a0b721be66c/tlcr-14-05-1699-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/a8c169cd6a2d/tlcr-14-05-1699-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/7a146111945f/tlcr-14-05-1699-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/022bea360824/tlcr-14-05-1699-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/f98286f60ebb/tlcr-14-05-1699-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/0a0b721be66c/tlcr-14-05-1699-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/a8c169cd6a2d/tlcr-14-05-1699-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8b4/12170254/7a146111945f/tlcr-14-05-1699-f5.jpg

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