血浆游离DNA检测对非小细胞肺癌靶向治疗相关基因筛选及患者预后预测的研究

doi:10.19401/j.cnki.1007-3639.2025.04.003

摘要/Abstract

摘要：

背景与目的：肿瘤患者血浆游离DNA（cell-free DNA，cfDNA）高通量检测广泛用于肿瘤靶向治疗相关基因的筛选。本研究探讨cfDNA中Ⅰ类及Ⅱ类靶向治疗相关基因变异类型及数量与非小细胞肺癌（non-small cell lung cancer，NSCLC）患癌预后的关系。方法：收集2021年—2023年在中山大学肿瘤防治中心进行血浆cfDNA高通量测序项目的NSCLC患者的测序结果及临床资料，并对入组患者从2021年6月1日采集血浆当天开始截至2024年5月27日进行生存随访，并使用GraphPad Prism 8.0及SPSS Statistics 25.0对患者生存期与临床资料及测序结果中Ⅰ类与Ⅱ类靶向治疗相关基因类型及数目进行单因素及多因素统计学分析（伦理批号：B2024-359-01）。结果：313例NSCLC患者中确诊时分期Ⅰ期25例（7.98%）、Ⅱ期20例（6.39%）、Ⅲ期38例（12.14%）和Ⅳ期230例（73.48%）；组内NSCLC分型包含腺癌（90.10%），鳞癌（5.11%），大细胞癌（2.87%）及其他分型（1.92%）；入组的NSCLC患者血浆cfDNA中Ⅰ类与Ⅱ类靶向治疗相关基因数及占比分别为：0个（25.24%）、1个（17.57%）、2个（19.17%）、3个（14.38%）、4个（8.31%）、5个及以上（15.34%）。患者血浆cfDNA高通量测序检测结果中，突变频率最高的3个基因分别为EGFR、TP53、ERBB2基因，其中EGFR基因突变频率为36.04%，TP53基因突变频率为30.63%，ERBB2基因突变频率为4.95%。患者生存期不仅与热点靶向基因表达情况相关，与血浆cfDNA高通量测序中Ⅰ类和Ⅱ类靶向相关位点基因变异个数也呈正相关。经过治疗后无靶向治疗相关基因的位点变异比有靶向治疗相关基因的位点变异的患者的生存期长，死亡风险可降低63.2%。而单纯一个基因位点变异比多个驱动基因位点变异的患者的生存期长，死亡风险更低，所测得的Ⅰ类及Ⅱ类靶向治疗药物在3个基因数以内，基因数目越少，患者的生存期越长。结论：血浆cfDNA高通量测序中Ⅰ类和Ⅱ类靶向相关位点基因变异个数对经过治疗后的NSCLC患者的生存期有影响。血浆cfDNA高通量测序检测可作为患者预后的评估指标。

关键词: 非小细胞肺癌, 血浆游离DNA, 高通量测序, 基因突变位点, 靶向治疗药物筛选, 生存分析

Abstract:

Background and purpose: High-throughput detection of plasma cell-free DNA (cfDNA) is widely used for multi-cancer targeted therapy drug screening, and this study investigated the relationship between the type and number of plasma cfDNA class Ⅰ and Ⅱ targeted therapy-related gene variants and cancer survival in patients with non-small cell lung cancer (NSCLC). Methods: The sequencing results and clinical data of NSCLC patients who underwent tumor plasma cfDNA high-throughput sequencing projects in Sun Yat-sen University Cancer Center from 2021 to 2023 were collected. The survival follow-up of enrolled patients was carried out from the day of plasma collection on June 1, 2021 to May 27, 2024, and GraphPad Prism 8.0 and SPSS Statistics 25.0 were used. Univariate and multivariate statistical analyses were conducted on the types and numbers of class Ⅰ and class Ⅱ targeted therapy-related genes in the survival and clinical data of patients and sequencing results (Ethical approval: B2024-359-01). Results: A total of 313 patients included in this study with NSCLC were categorized into stage Ⅰ 25 patients (7.98%), stage Ⅱ 20 patients (6.39%), stage Ⅲ 38patients (12.14%), and stage Ⅳ 230 patients (73.48%). Pathological diagnosis results showed that adenocarcinoma accounted for 90.10%, squamous cell carcinoma accounted for 5.11%, large cell carcinoma accounted for 2.87% and other classifications accounted for 1.92%. The number and the percentage of class Ⅰ and class Ⅱ targeted therapy drug-related genes in the plasma cfDNA NSCLC patients were 0 (25.24%), 1 (17.57%), 2 (19.17%), 3 (14.38%), 4 (8.31%), and 5 or more (15.34%). The results of statistical analysis showed that 3 genes with the highest mutation frequencies were EGFR, TP53 and ERBB2, and the mutation frequency of EGFR gene was 36.04%. The mutation frequency of TP53 gene was 30.63%. The mutation frequency of ERBB2 gene was 4.95%. The survival time of patients is related to not only the expression of hotspot targeted genes, but also the number of class Ⅰ and Ⅱ target-related gene variants detected by plasma cfDNA high-throughput sequencing. The survival time of the patients with no targeted therapy-related locus variants after treatment was longer compares with targeted therapy-related locus variants, which can reduce the risk of death by 63.2%. However, patients with a single gene locus variant had longer survival time and lower risk of death than those with multiple driver locus variants, and the measured class Ⅰ and Ⅱ targeted therapy drugs were within 3 genes. Overall, the smaller the number of genes, the longer the survival. Conclusions: The number of class Ⅰ and class Ⅱ targeted therapy-related gene variants in plasma cfDNA high-throughput sequencing also has an effect on the survival of patients after treatment. Plasma cfDNA level detected by high-throughput sequencing could be a prognostic factor for the NSCLC patients.

Key words: Non-small cell lung cancer, Plasma cell-free DNA, High-throughput sequencing, Gene mutation sites, Targeted therapy drug selection, Survival analysis

邓绮玲, 宋迪, 奚可欣, 谢晓婷, 吴小延, 赵卫. 血浆游离DNA检测对非小细胞肺癌靶向治疗相关基因筛选及患者预后预测的研究[J]. 中国癌症杂志, 2025, 35(4): 355-364.

DENG Qiling, SONG Di, XI Kexin, XIE Xiaoting, WU Xiaoyan, ZHAO Wei. Research on high-throughput detection of plasma cell-free DNA for targeted therapy-related genes screening and prognosis prediction in non-small cell lung cancer patients[J]. China Oncology, 2025, 35(4): 355-364.

图/表 11

表1

体细胞变异分类解释"

Somatic variant classification	Level of evidence	Explained
Class Ⅰ variants (strong clinical significance)	A	FDA/NMPA approved for use as a biomarker that is responsive or resistant to cancer treatment in patients
	A	Professional guidelines (NCCN) identify biomarkers that are responsive to or resistant to cancer treatment in patients
	A	professional guideline (NCCN) clarifies biomarkers that have diagnostic or prognostic significance for the patient's tumor
	B	Expert consensus studies identify biomarkers that are responsive to or resistant to cancer treatment in patients
	B	Expert consensus studies identify biomarkers that have diagnostic or prognostic significance for the patient's tumor
	C	FDA/NMPA approved biomarkers for other tumor treatments that are responsive or resistant
Class Ⅱ variant (potential clinical significance)	C	Professional guidelines (NCCN) recommend biomarkers that are responsive to or resistant to other oncology treatments
	C	Has been used as a biomarker for clinical trial screening and enrolment criteria
	C	The results of several small studies have shown biomarkers of significance for the diagnosis or prognosis of cancer in patients
	D	The results of the study indicate biomarkers of significance for the diagnosis, treatment, or prognosis of other tumors
	D	Biomarkers with potential therapeutic significance in preclinical studies
	D	There are a few studies and case reports or conclusions that do not reach a consensus to assess the diagnostic or prognostic significance of the disease with other biomarkers Class Ⅲ variants
Category Ⅲ variants (variants of unknown clinical significance)	-	Not detected in population databases, specific subpopulation databases, pan-cancer databases, tumor-specific databases
	-	There is no conclusive evidence of a cancer type
Class Ⅳ variants (benign polymorphisms and suspected benign variants)	-	No evidence of cancer associated with the population database, specific subpopulation database.

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Item	P value	HR(A/B)	95% CI
The number of loci is 0	0.001	-	-
The number of loci is 1	0.142	2.016	1.984-5.062
The number of loci is 2	0.002	3.848	1.645-8.824
The number of loci is 3	0	5.006	2.334-12.440
The number of loci is 4	0.005	4.530	1.445-11.734
The number of loci is 5	0	4.629	2.047-10.606
History of surgery	0.001	1.752	1.244-2.467
Clinical staging	0.002	0.509	0.336-0.773