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Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations

机译:通过联合检测miRNA基因表达和体细胞基因改变对甲状腺病变进行分子分类

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Abstract Multiple molecular markers contribute to the pathogenesis of thyroid cancer and can provide valuable information to improve disease diagnosis and patient management. We performed a comprehensive evaluation of miRNA gene expression in diverse thyroid lesions ( n = 534) and developed predictive models for the classification of thyroid nodules, alone or in combination with genotyping. Expression profiling by reverse transcription-quantitative polymerase chain reaction in surgical specimens ( n = 257) identified specific miRNAs differentially expressed in 17 histopathological categories. Eight supervised machine learning algorithms were trained to discriminate benign from malignant lesions and evaluated for accuracy and robustness. The selected models showed invariant area under the receiver operating characteristic curve (AUC) in cross-validation (0.89), optimal AUC (0.94) in an independent set of preoperative thyroid nodule aspirates ( n = 235), and classified 92% of benign lesions as low riskegative and 92% of malignant lesions as high risk/positive. Surgical and preoperative specimens were further tested for the presence of 17 validated oncogenic gene alterations in the BRAF , RAS , RET or PAX8 genes. The miRNA-based classifiers complemented and significantly improved the diagnostic performance of the 17-mutation panel ( p < 0.001 for McNemar's tests). In a subset of resected tissues ( n = 54) and in an independent set of thyroid nodules with indeterminate cytology ( n = 42), the optimized ThyraMIR Thyroid miRNA Classifier increased diagnostic sensitivity by 30?¢????39% and correctly classified 100% of benign nodules negative by the 17-mutation panel. In contrast, testing with broad targeted next-generation sequencing panels decreased diagnostic specificity by detecting additional mutations of unknown clinical significance in 19?¢????39% of benign lesions. Our results demonstrate that, independent of mutational status, miRNA expression profiles are strongly associated with altered molecular pathways underlying thyroid tumorigenesis. Combined testing for miRNA gene expression and well-established somatic gene alterations is a novel diagnostic strategy that can improve the preoperative diagnosis and surgical management of patients with indeterminate thyroid nodules.
机译:摘要多种分子标记物参与甲状腺癌的发病机制,可以为改善疾病诊断和患者管理提供有价值的信息。我们对多种甲状腺病变(n = 534)中的miRNA基因表达进行了全面评估,并开发了单独或结合基因分型的甲状腺结节分类预测模型。通过逆转录-定量聚合酶链反应在外科手术标本中的表达谱分析(n = 257)确定了在17种组织病理学类别中差异表达的特定miRNA。训练了八种监督机器学习算法,以区分良性和恶性病变,并评估其准确性和鲁棒性。所选模型在交叉验证(0.89)中显示了接受者工作特征曲线(AUC)下的不变区域,在一组独立的术前甲状腺结节穿刺物(n = 235)中显示了最佳AUC(0.94),并对92%的良性病变进行了分类低风险/阴性和92%的恶性病变为高风险/阳性。进一步测试了手术和术前标本的BRAF,RAS,RET或PAX8基因中是否存在17种经过验证的致癌基因改变。基于miRNA的分类器补充并显着改善了17个突变组的诊断性能(对于McNemar's测试,p <0.001)。在一部分切除的组织(n = 54)和独立的甲状腺结节中,细胞学检查不确定(n = 42),经过优化的ThyraMIR甲状腺miRNA分类器将诊断敏感性提高了30%,准确度提高了39%。 17个突变小组对100%的良性结节呈阴性。相比之下,使用广泛靶向的下一代测序小组进行的测试通过检测19%至39%的良性病变中的其他未知临床意义的突变而降低了诊断特异性。我们的结果表明,独立于突变状态,miRNA表达谱与甲状腺肿瘤发生的分子途径改变密切相关。结合检测miRNA基因表达和完善的体细胞基因改变是一种新颖的诊断策略,可改善不确定甲状腺结节患者的术前诊断和手术管理。

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