Ducena Kristine, Abols Arturs, Vilmanis Janis, Narbuts Zenons, Tārs Juris, Andrējeva Diana, Linē Aija, Pīrāgs Valdis
Faculty of Medicine, University of Latvia, Raina Bulvaris 19, Riga, LV1586, Latvia.
Thyroid Res. 2011 Jun 27;4(1):11. doi: 10.1186/1756-6614-4-11.
Currently the cytological examination of fine needle aspiration (FNA) biopsies is the standard technique for the pre-operative differential diagnosis of thyroid nodules. However, the results may be non-informative in ~20% of cases due to an inadequate sampling and the lack of highly specific, measurable cytological criteria, therefore ancillary biomarkers that could aid in these cases are clearly needed. The aim of our study was to evaluate the mRNA expression levels of 8 candidate marker genes as the diagnostic biomarkers for the discrimination of benign and malignant thyroid nodules and to find a combination of biomarkers with the highest diagnostic value.
mRNA expression levels of eight candidate marker genes - BIRC5, CCND1, CDH1, CITED1, DPP4, LGALS3, MET and TFF3 was measured by real-time RT-PCR in paired nodular and surrounding normal thyroid tissue specimens of 105 consecutive patients undergoing thyroid surgery and compared between different types of thyroid lesions.
Significant differences in the mRNA expression levels between the normal and malignant thyroid tissues and between benign and malignant nodules were found for BIRC5, CCND1, CITED1, DPP4, LGALS3, MET and TFF3, but not CDH1. On a single gene basis, relative quantity (RQ) of LGALS3 had the highest diagnostic value for the discrimination of malignant and benign thyroid nodules (AUC = 0.832, P < 0.0001 and 90.9% sensitivity and 65.6% specificity at the optimal cut-off on ROC curve). The only two-marker set that outperformed LGALS3 was RQ sum of LGALS3 and BIRC5 (AUC = 0.841, P < 0.0001). An application of multivariate logistic regression analysis resulted in the generation of a multiplex biomarker model based on LGALS3, BIRC5, TFF3, CCND1, MET and CITED1 that had considerably higher specificity than a single marker or two marker gene-based models (AUC = 0.895, P < 0.0001, 70.5% sensitivity and 93.4% specificity).
This study confirmed that mRNA expression levels of 7 out of 8 candidate genes analysed have a diagnostic value for the distinction of benign and malignant thyroid nodules. The multiplex biomarker model based on 6 genes outperformed a single marker or two marker-based models and warrants feasibility studies on FNA biopsies and the validation in a larger cohort of patients.
目前，细针穿刺（FNA）活检的细胞学检查是甲状腺结节术前鉴别诊断的标准技术。然而，由于采样不足以及缺乏高度特异性、可测量的细胞学标准，约20%的病例结果可能无法提供有效信息，因此显然需要有助于这些病例诊断的辅助生物标志物。我们研究的目的是评估8个候选标记基因的mRNA表达水平，将其作为鉴别甲状腺良恶性结节的诊断生物标志物，并找到具有最高诊断价值的生物标志物组合。
通过实时逆转录聚合酶链反应（RT-PCR）测量105例连续接受甲状腺手术患者的成对结节性和周围正常甲状腺组织标本中8个候选标记基因——BIRC5、CCND1、CDH1、CITED1、DPP4、LGALS3、MET和TFF3的mRNA表达水平，并在不同类型的甲状腺病变之间进行比较。
发现BIRC5、CCND1、CITED1、DPP4、LGALS3、MET和TFF3在正常与恶性甲状腺组织之间以及良性与恶性结节之间的mRNA表达水平存在显著差异，但CDH1无差异。基于单个基因，LGALS3的相对定量（RQ）对鉴别甲状腺良恶性结节具有最高诊断价值（曲线下面积[AUC]=0.832，P<0.0001，在ROC曲线上的最佳截断值时灵敏度为90.9%，特异性为65.6%）。唯一优于LGALS3的双标记组合是LGALS3和BIRC5的RQ总和（AUC=0.841，P<0.0001）。多元逻辑回归分析的应用产生了一个基于LGALS3、BIRC5、TFF3、CCND1、MET和CITED1的多重生物标志物模型，其特异性明显高于基于单个标记或两个标记基因的模型（AUC=0.895，P<0.0001，灵敏度为70.5%，特异性为93.4%）。
本研究证实，所分析的8个候选基因中的7个基因的mRNA表达水平对鉴别甲状腺良恶性结节具有诊断价值。基于6个基因的多重生物标志物模型优于基于单个标记或两个标记的模型，值得对FNA活检进行可行性研究并在更大患者队列中进行验证。
