Primary exploration of cell-free DNA in the plasma of patients with parathyroid neoplasms using next-generation sequencing.

IF 5.3 2区医学 Q1 ONCOLOGY

Cancer Cell International Pub Date : 2025-03-12 DOI:10.1186/s12935-025-03699-w

Qingyuan Zheng, Ming Cui, Ou Wang, Xiaoyan Chang, Jinheng Xiao, Tianqi Chen, Mengyi Wang, Surong Hua, Ya Hu, Quan Liao

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引用次数: 0

Abstract

Background and aims: Plasma cell-free DNA (cfDNA) has been used to monitor gene mutations and diagnose tumors. Discriminating parathyroid carcinoma (PC) from parathyroid adenoma (PA) before surgery is difficult because of the overlap in clinical features between parathyroid neoplasms. We aimed to detect cfDNA mutations in plasma samples from PC and PA patients before surgery to predict the CDC73 status in tumor tissue and help in the differential diagnosis of parathyroid neoplasms.

Materials and methods: Eighteen PC patients and 13 PA patients were enrolled. Plasma cfDNA was detected using next-generation sequencing, with DNA from matched peripheral white blood cells used as a control. CDC73 gene mutations were detected via whole-exome sequencing or parafibromin staining via immunohistochemistry of tumor tissues. Logistic regression was used to evaluate the ability of cfDNA mutations to predict the CDC73 status in tumor tissue and for differential diagnosis. CDC73 gene mutation or parafibromin staining loss were defined as CDC73 abnormalities.

Results: One PC patient was not tested for CDC73 abnormalities due to the absence of tumor specimen. CDC73 abnormalities were not detected in all 13 PA patients, whereas 10 PC patients harboured CDC73 abnormalities in tumor specimens (P = 0.001). Among the 10 patients, CDC73 mutations were identified in the cfDNA of 8 patients. In another 20 patients without CDC73 abnormalities in tumors, CDC73 mutation was detected in the cfDNA of 4 patients. Using the CDC73 status in cfDNA, the area under the receiver operating characteristic curve (AUC) for predicting CDC73 abnormalities in tumor tissue was 0.80 (95% CI: 0.622-0.978), and the AUC for predicting malignancy was 0.795 (95% CI 0.632-0.958).

Conclusion: This study is the first attempt to evaluate the gene mutation status of parathyroid neoplasms through the deep sequencing of plasma cfDNA, which could also help to identify PC prior to surgery.

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应用新一代测序技术对甲状旁腺肿瘤患者血浆中游离DNA的初步探索。

背景与目的：血浆游离DNA （cfDNA）已被用于监测基因突变和诊断肿瘤。术前鉴别甲状旁腺癌（PC）和甲状旁腺瘤（PA）是困难的，因为甲状旁腺肿瘤的临床特征有重叠。我们旨在检测PC和PA患者术前血浆样本中的cfDNA突变，以预测肿瘤组织中CDC73的状态，并有助于甲状旁腺肿瘤的鉴别诊断。材料与方法：18例PC患者和13例PA患者入组。使用新一代测序检测血浆cfDNA，并将来自匹配的外周血细胞的DNA作为对照。采用全外显子组测序或免疫组化对肿瘤组织进行副纤白蛋白染色检测CDC73基因突变。使用Logistic回归来评估cfDNA突变预测肿瘤组织中CDC73状态和鉴别诊断的能力。CDC73基因突变或副纤白蛋白染色丢失定义为CDC73异常。结果：1例PC患者因未见肿瘤标本，未检测CDC73异常。所有13例PA患者未检测到CDC73异常，而10例PC患者肿瘤标本中存在CDC73异常（P = 0.001）。在10例患者中，8例患者的cfDNA中发现CDC73突变。在20例肿瘤中未发现CDC73异常的患者中，有4例患者的cfDNA中检测到CDC73突变。利用CDC73在cfDNA中的状态，预测肿瘤组织CDC73异常的受者工作特征曲线下面积（AUC）为0.80 (95% CI: 0.622-0.978)，预测恶性肿瘤的AUC为0.795 （95% CI 0.632-0.958）。结论：本研究首次尝试通过血浆cfDNA深度测序来评估甲状旁腺肿瘤的基因突变状态，也有助于术前鉴别PC。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cancer Cell International ONCOLOGY-

CiteScore

10.90

自引率

1.70%

发文量

360

审稿时长

1 months

期刊介绍： Cancer Cell International publishes articles on all aspects of cancer cell biology, originating largely from, but not limited to, work using cell culture techniques. The journal focuses on novel cancer studies reporting data from biological experiments performed on cells grown in vitro, in two- or three-dimensional systems, and/or in vivo (animal experiments). These types of experiments have provided crucial data in many fields, from cell proliferation and transformation, to epithelial-mesenchymal interaction, to apoptosis, and host immune response to tumors. Cancer Cell International also considers articles that focus on novel technologies or novel pathways in molecular analysis and on epidemiological studies that may affect patient care, as well as articles reporting translational cancer research studies where in vitro discoveries are bridged to the clinic. As such, the journal is interested in laboratory and animal studies reporting on novel biomarkers of tumor progression and response to therapy and on their applicability to human cancers.