Analytical and clinical validation of pairwise microRNA expression analysis to identify medullary thyroid cancer in thyroid fine-needle aspiration samples.
Analytical and clinical validation of pairwise microRNA expression analysis to identify medullary thyroid cancer in thyroid fine-needle aspiration samples.
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对成对microRNA表达分析的分析和临床验证，以鉴定甲状腺细针吸入样品中髓样甲状腺癌。
DOI：
10.1002/cncy.22365
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发表时间：
2021-03
影响因子：
3.4
通讯作者：
Kumar G
中科院分区：
文献类型：
--
作者：
Ciarletto AM;Narick C;Malchoff CD;Massoll NA;Labourier E;Haugh K;Mireskandari A;Finkelstein SD;Kumar G
甲状腺髓样癌(MTC)是一种起源于滤泡旁C细胞的侵袭性恶性肿瘤。术前，甲状腺结节细针吸取细胞学(FNAC)和致病基因突变在大约一半的病例中是明确的。MicroRNAs(MiRNAs)是一种内源性的、非编码的单链RNA，它调节基因的表达，这一特征赋予了识别恶性肿瘤的可能性。在目前的研究中，作者假设对miRNA表达水平的差异配对(diff对)分析可以可靠地识别FNA样本中的MTC。从ThyraMIR测试结果中获得了10种不同miRNAs在总核酸中的相对丰度。通过从其他miRNAs的临界阈值中减去一个miRNA的临界阈值进行Diff配对分析。ThyGeNEXT小组的下一代测序确定了致癌基因的变化。发现的队列包括30例福尔马林固定、石蜡包埋的良性和恶性甲状腺肿瘤，其中包括4例MTC。在分析验证之后，使用3个不同的队列(总共7557个样本)进行临床验证。在发现队列中，使用Kruskal-Wallis检验(P<；T.0001)将MTC样本与非MTC样本区分开来，确定了9个差异对具有显著的能力。该方法正确地将分析验证研究和3个临床验证队列中的所有MTC和非MTC样本分类。总体测试准确率为100%(95%可信区间，99%~100%)。在不确定的FNAC样本中，差异对分析的敏感性高于MTC特异性突变分析(100%比25%；P=10.03)。ThyraMIR结果的成对miRNA表达分析被发现可以准确地预测甲状腺FNA样本中的MTC，包括那些FNAC结果不确定的样本。作者开发并验证了一种微小RNA(MiRNA)检测方法，用于检测术前甲状腺结节标本中的甲状腺髓样癌(MTC)。该方法基于对使用ThyraMIR甲状腺miRNA分类器生成的miRNA表达数据的差异配对分析，能够以100%的灵敏度和100%的特异度准确预测甲状腺细针活检的MTC。
Medullary thyroid carcinoma (MTC) is an aggressive malignancy originating from the parafollicular C cells. Preoperatively, thyroid nodule fine‐needle aspiration cytology (FNAC) and pathogenic gene mutations are definitive in approximately one‐half of cases. MicroRNAs (miRNAs) are endogenous, noncoding, single‐stranded RNAs that regulate gene expression, a characteristic that confers the potential for identifying malignancy. In the current study, the authors hypothesized that differential pairwise (diff‐pair) analysis of miRNA expression levels would reliably identify MTC in FNA samples. The relative abundance of 10 different miRNAs in total nucleic acids was obtained from ThyraMIR test results. Diff‐pair analysis was performed by subtracting the critical threshold value of one miRNA from the critical threshold values of other miRNAs. Next‐generation sequencing with the ThyGeNEXT panel identified oncogenic gene alterations. The discovery cohort consisted of 30 formalin‐fixed, paraffin‐embedded benign and malignant thyroid neoplasms, including 4 cases of MTC. After analytical validation, clinical validation was performed using 3 distinct cohorts (total of 7557 specimens). In the discovery cohort, 9 diff‐pairs were identified as having significant power using the Kruskal‐Wallis test (P < .0001) to distinguish MTC samples from non‐MTC samples. The assay correctly classified all MTC and non‐MTC samples in the analytical validation study and in the 3 clinical validation cohorts. The overall test accuracy was 100% (95% confidence interval, 99%‐100%). In indeterminate FNAC samples, the sensitivity of the diff‐pair analysis was greater than that of the MTC‐specific mutation analysis (100% vs 25%; P = .03). Pairwise miRNA expression analysis of ThyraMIR results were found to accurately predict MTC in thyroid FNA samples, including those with indeterminate FNAC findings. The authors have developed and validated a microRNA (miRNA) test for the detection of medullary thyroid cancer (MTC) in preoperative thyroid nodule samples. The method, based on differential pairwise analysis of miRNA expression data generated using the ThyraMIR Thyroid miRNA Classifier, accurately predicts MTC with 100% sensitivity and 100% specificity in thyroid fine‐needle aspiration biopsies.
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影响因子：
64.5
作者：
Cancer Genome Atlas Research Network
通讯作者：
Cancer Genome Atlas Research Network
影响因子：
3.6
作者：
Hudson, Jena;Duncavage, Eric;Tamburrino, Anna;Salerno, Paolo;Xi, Liqiang;Raffeld, Mark;Moley, Jeffrey;Chernock, Rebecca D.
通讯作者：
Chernock, Rebecca D.
DOI：
10.1093/jnci/95.8.625
发表时间：
2003-04-16
期刊：
JOURNAL OF THE NATIONAL CANCER INSTITUTE
影响因子：
--
作者：
Cohen, J;Xing, MZ;Sidransky, D
通讯作者：
Sidransky, D
影响因子：
1.3
作者：
Jackson, Sara;Kumar, Gyanendra;Finkelstein, Sydney D.
通讯作者：
Finkelstein, Sydney D.
影响因子：
3.4
作者：
Benjamin, Hila;Schnitzer-Perlman, Temima;Meiri, Eti
通讯作者：
Meiri, Eti