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从血浆外泌体中提取的 FGB 和 FGG 作为潜在的生物标志物,可区分良、恶性肺结节。

FGB and FGG derived from plasma exosomes as potential biomarkers to distinguish benign from malignant pulmonary nodules.

机构信息

Huadong Hospital, Fudan University, Shanghai, China.

Fudan University Shanghai Cancer Center, Shanghai, China.

出版信息

Clin Exp Med. 2019 Nov;19(4):557-564. doi: 10.1007/s10238-019-00581-8. Epub 2019 Oct 1.

DOI:10.1007/s10238-019-00581-8
PMID:31576477
Abstract

Previous proteomic analysis (label-free) of plasma exosomes revealed that the expression of FGG and FGB was significantly higher in the malignant pulmonary nodules group, compared to the benign pulmonary nodules group. The present study was performed to evaluate the role of plasma exosomal proteins FGB and FGG in the diagnosis of benign and malignant pulmonary nodules. We examined the expression levels of FGB and FGG in plasma exosomes from 63 patients before surgery. Postoperative pathological diagnosis confirmed that 43 cases were malignant and 20 cases were benign. The ROC curve was used to describe the sensitivity, specificity, area under the curve (AUC) of the biomarker and the corresponding 95% confidence interval. We confirmed that the expression levels of FGB and FGG were higher in the plasma exosomes of malignant group than in the benign group. The sensitivity and AUC of FGB combined with FGG detection to determine the nature of pulmonary nodules are superior to single FGB or FGG detection. FGB and FGG might represent novel and sensitive biomarker to distinguish benign from malignant pulmonary nodules.

摘要

先前的血浆外泌体蛋白质组学分析(无标记)显示,与良性肺结节组相比,恶性肺结节组中 FGG 和 FGB 的表达明显更高。本研究旨在评估血浆外泌体蛋白 FGB 和 FGG 在良恶性肺结节诊断中的作用。我们检测了 63 例患者术前血浆外泌体中 FGB 和 FGG 的表达水平。术后病理诊断证实 43 例为恶性,20 例为良性。ROC 曲线用于描述生物标志物的灵敏度、特异性、曲线下面积(AUC)和相应的 95%置信区间。我们证实 FGB 和 FGG 在恶性组的血浆外泌体中的表达水平高于良性组。FGB 联合 FGG 检测对确定肺结节性质的灵敏度和 AUC 优于单独检测 FGB 或 FGG。FGB 和 FGG 可能是鉴别良恶性肺结节的新型敏感生物标志物。

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2
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3
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Cancer Cell Int. 2024 Oct 14;24(1):341. doi: 10.1186/s12935-024-03522-y.
4
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Cancer Biomark. 2024;41(1):69-82. doi: 10.3233/CBM-240137.
5
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6
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Respir Res. 2023 Nov 12;24(1):276. doi: 10.1186/s12931-023-02566-4.
7
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9
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4
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5
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8
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9
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10
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