WO2022133738A1 - 一种术前鉴别甲状腺良恶性结节的生物标志物、试剂盒及其应用 - Google Patents
一种术前鉴别甲状腺良恶性结节的生物标志物、试剂盒及其应用 Download PDFInfo
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- WO2022133738A1 WO2022133738A1 PCT/CN2020/138369 CN2020138369W WO2022133738A1 WO 2022133738 A1 WO2022133738 A1 WO 2022133738A1 CN 2020138369 W CN2020138369 W CN 2020138369W WO 2022133738 A1 WO2022133738 A1 WO 2022133738A1
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- benign
- thyroid nodules
- malignant
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- thyroid
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Classifications
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- G01N30/02—Column chromatography
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
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- G01N30/02—Column chromatography
- G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
Definitions
- the invention belongs to the technical field of molecular biomedicine, in particular to the application of a serological biomarker for preoperative identification of benign and malignant thyroid nodules and a kit thereof in the diagnosis of benign and malignant thyroid nodules.
- Thyroid nodule refers to one or more masses with abnormal tissue structure caused by local abnormal proliferation of thyroid cells.
- the incidence of thyroid nodules has increased year by year, and the detection rate in the general population can be as high as 20%-76%.
- the commonly used nodule detection methods are ultrasonography and fine needle aspiration (FNA) of the thyroid.
- Ultrasonography is a non-invasive test that diagnoses nodules with suspicious malignant features such as microcalcifications, aspect ratio >1, etc. on ultrasonography.
- the TI-RADS ultrasound grading system recommended by the American Thyroid Association in 2015 divides thyroid nodules into 7 grades according to suspicious malignant features under ultrasound. Perform puncture examination or surgical treatment.
- ultrasonography is more dependent on the examiner's subjective cognition and diagnostic experience, and suspicious malignant signs of thyroid nodules are less likely to appear when the thyroid nodule is small. Therefore, ultrasonography is prone to misdiagnosis and misunderstanding in the diagnosis of benign and malignant nodules. Insufficient judgment.
- FNA has high requirements on puncture technique and sampling quality. After biopsy, it is still not possible to differentiate between benign and malignant.
- the detection of tumor molecular markers is a hot spot in tumor diagnostics.
- the 2015 ATA guidelines recommend the detection of molecular markers for thyroid tumors to assist in diagnosis and guide treatment.
- no single or multiple combined molecular markers have been found to effectively diagnose benign and malignant thyroid nodules.
- BRAF V600E is the most common somatic mutation in papillary thyroid carcinoma, but it is still less proven as a hematological tumor marker feasibility and reliability.
- the combination of markers such as DNA methylation, microRNA, and lncRNA is also limited by the small sample size and instability, which cannot effectively verify its diagnostic performance. Therefore, it is of great practical significance to find a simple and effective liquid biopsy method for differential diagnosis of benign and malignant nodules.
- the present invention carries out a related research on the application of metabolomics technology to explore the application of the combination of metabolic markers in the diagnosis of thyroid nodules.
- metabolomics technology there has been no report on the detection and analysis of metabolic markers by metabolomics in plasma samples, preoperative identification of benign and malignant thyroid nodules, and good diagnostic performance.
- the purpose of the present invention is to provide a kind of serological biomarkers for preoperative identification of benign and malignant thyroid nodules and the application of their kits in the diagnosis of benign and malignant thyroid nodules, to overcome the existing technology in the diagnosis of benign and malignant thyroid nodules. Defects and deficiencies improve the accuracy of the diagnosis of thyroid nodules.
- the present invention provides a serological biomarker for preoperative identification of benign and malignant thyroid nodules.
- the marker is 17 metabolites in preoperative serological specimens of patients with thyroid nodules, which are respectively gabapentin, caprylylglycine, and sulfuric acid.
- valeric acid triethanolamine
- imidazole acetic acid isohomovillic acid
- dexrazoxane phosphatidylcholine (18:3(6Z,9Z,12Z)/15:0)
- levetiracetam mono Ethylglycyl disaccharide
- panthenol panthenol
- azelaic acid ippamine
- alpha-tocopherol p-allylphenol
- isoprene isoprene.
- the present invention provides a kit comprising the above-mentioned serological biomarkers.
- the present invention also provides the application of the above-mentioned biomarker and its kit in the differential diagnosis of benign and malignant thyroid nodules.
- Plasma samples of patients with thyroid nodules are used to detect 17 metabolites, and the benign and malignant thyroid nodules can be identified according to the results.
- Diagnosis includes the following steps:
- peripheral blood samples were centrifuged at 4°C and 3500rpm for 12min;
- the 17 metabolites mentioned above were detected in plasma samples from patients with thyroid nodules.
- the plasma levels of gabapentin, capryloylglycine, androsterone sulfate, valeric acid, triethanolamine, dexrazoxane, imidazoacetic acid, isomovanillic acid, phosphatidylcholine ( 18:3(6Z,9Z,12Z)/15:0) levels were significantly increased, while levetiracetam, monoethylglycyl disaccharide, panthenol, azelaic acid, ippamine, alpha-tocopheryl
- levetiracetam monoethylglycyl disaccharide
- panthenol panthenol
- azelaic acid ippamine
- alpha-tocopheryl alpha-tocopheryl
- the present invention finds for the first time that the changes in the levels of the above 17 metabolites are related to benign and malignant thyroid nodules. Metabolomics analysis is used to find and detect the levels of 17 metabolites in peripheral blood plasma of patients with thyroid nodules. A machine learning method to construct a diagnostic model and use the receiver operating curve (ROC) to evaluate the efficacy of diagnosing thyroid cancer.
- the area under the ROC curve of the metabolic marker combination diagnostic model composed of the above metabolites in the diagnosis of thyroid nodules can reach 95.05%, and the sensitivity and specificity are both higher than 88%. And the diagnostic efficacy of this metabolic marker has no significant correlation with tumor diameter and the presence of lymph node metastasis, which can be applied to the diagnosis of micro nodules and early thyroid cancer.
- serological metabolic markers can be diagnosed by collecting peripheral blood samples, with significantly less trauma and avoiding adverse reactions such as hematoma at the puncture site and vagus nerve reaction. There is no need to obtain surgical specimens through invasive procedures, reducing the mental burden of patients and avoiding unnecessary treatments. Plasma metabolic markers can be used for further differential diagnosis when ultrasound suggests suspicious malignancy. The sensitivity and specificity for the identification of benign and malignant nodules are higher than those of ultrasound, which can effectively avoid unnecessary biopsy or diagnostic surgery.
- Inclusion criteria (1) Histopathologically diagnosed as papillary thyroid carcinoma or benign thyroid nodules; (2) No other malignant tumors or serious immune, neurological, digestive or hematological diseases; (3) ) to obtain preoperative or postoperative blood samples.
- Exclusion criteria (1) Combined with other types of malignant tumors; (2) Combined with severe immune, neurological, digestive, or blood system diseases; (3) Unable or unsuitable to obtain preoperative peripheral blood samples.
- postoperative paraffin pathology and immunohistochemical results were used as the gold standard for diagnosis.
- Preoperative plasma was collected in the early morning of the second day after admission, and was collected from the upper arm vein under fasting conditions. The plasma separation process was completed within 2 hours after blood collection, and the separated plasma was stored in a -80°C refrigerator until metabolomics detection.
- the reagents involved in the metabolite extraction of the present invention are the reagents used in the metabolite extraction known in the art;
- blood sample metabolomics detection methods are well known in the art, for example, based on non-target metabolomics detection technology and target metabolomics detection technology. Its specific technology platform can be based on gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and hydrogen nuclear magnetic resonance (1H-NMR);
- GC-MS gas chromatography-mass spectrometry
- LC-MS liquid chromatography-mass spectrometry
- 1H-NMR hydrogen nuclear magnetic resonance
- Liquid chromatography phase A is an aqueous phase, containing 25 mmol/L ammonium acetate and 25 mmol/L ammonia water
- phase B is acetonitrile
- Thermo Q Exactive HFX mass spectrometer can perform primary and secondary mass spectral data acquisition under the control of the control software (Xcalibur, Thermo).
- the detailed parameters are as follows: Sheath gas flow rate:50 Arb,Aux gas flow rate:10 Arb,Capillary temperature:320°C,Full ms resolution:60000,MS/MS resolution:7500,Collision energy:10/30/60in NCE mode, Spray Voltage: 3.5kV (positive) or -3.2kV (negative).
- the self-written R package (the kernel is XCMS) was used for peak identification, peak extraction, peak alignment and integration, etc.
- Database matching was performed for substance annotation, and the Cutoff value for algorithm scoring was set to 0.3.
- metabolic markers which were gabapentin, octanoylglycine, androsterone sulfate, valeric acid, triethanolamine, imidazole Acetic acid, isohomovanillic acid, dexrazoxane, phosphatidylcholine (18:3(6Z,9Z,12Z)/15:0), levetiracetam, monoethylglycyl disaccharide, panthenol, Azelaic acid, ippamine, alpha-tocopherol, p-allylphenol, isoprene.
- a single or multiple combinations of the above metabolic markers may be used as markers for diagnosing thyroid nodules.
- the caret package of R software input the differential metabolic marker matrix obtained by the above screening, and construct the SVM model.
- malignant types are coded as 1 and benign types as 0 during model building.
- the default threshold is set to 0.5.
- the constructed model also used 0.5 for the differential diagnosis of benign and malignant samples.
- the blood samples of the above-mentioned patients with thyroid cancer and benign thyroid nodules were used for metabolomics detection, and principal component and cluster analysis were performed according to the relative levels of metabolites in the detection results. There were significant differences in the plasma levels of these metabolites between patients with thyroid cancer and benign thyroid nodules.
- the SVM or random forest diagnostic model constructed based on the above-mentioned combination of metabolic markers is predicted in the discovery cohort and the validation cohort, and the output is the predicted disease probability, and the default score threshold is 0.5. There were 340 samples from the discovery cohort and 107 samples from the validation cohort.
- the discovery cohort and the validation cohort were diagnosed by the SVM diagnostic model, and the area under the curve (AUC) of the receiver operating curve (ROC) was drawn by the pROC package of the R software.
- the AUC of the discovery cohort was 95.05%, while the AUC of the validation cohort was 92.72%.
- the AUC was 88.07% for the discovery cohort and 86.66% for the validation cohort. It shows that the models established by random forest or support vector machine have better diagnostic performance.
- the t-test results are used if they meet the normal distribution, otherwise the rank-sum test results are used ("#" means that the variable uses the rank-sum test)
- the present invention studies the metabolic state differences of patients with benign and malignant thyroid nodules through the levels of metabolites in plasma, and screens out 17 metabolic markers with differences. Based on this metabolic marker group, a diagnostic model of benign and malignant thyroid nodules can be established through support vector machine or random forest method, which can effectively identify thyroid cancer and benign thyroid nodules. Compared with common inspection methods such as ultrasound or fine needle aspiration biopsy, the metabolic marker diagnostic model has higher sensitivity and specificity, and is easy to operate and less invasive, which is helpful for the accurate diagnosis and precise treatment of thyroid nodules. It is expected to be widely used in clinical practice.
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Abstract
涉及一种术前鉴别甲状腺良恶性结节的生物标志物、试剂盒及其应用，通过代谢组学分析发现检测甲状腺结节病人外周血血浆中17种代谢物的水平，结合组学分析以及机器学习方法，构建诊断模型并使用受试者工作曲线（ROC）评价诊断甲状腺癌的效能。由上述代谢物组成的代谢标志物组合诊断模型在甲状腺结节诊断中ROC曲线下的面积可达到95．05％，敏感度与特异度均高于88％，可应用于甲状腺良恶结节的鉴别。
Description
本发明属于分子生物医学技术领域，具体涉及一种术前鉴别甲状腺良恶性结节的血清学生物标志物及其试剂盒在甲状腺良恶性结节诊断方面的应用。
甲状腺结节是指甲状腺细胞在局部异常增生所引起的一个或者多个组织结构异常的团块。近年来，随着超声检查手段的普及，甲状腺结节的发病率逐年提升，一般人群中检出率可高达20％-76％。在发现甲状腺结节后，需要评估结节的良恶性以及功能，以进行合理的治疗。目前，常用的结节检测手段有超声检查和甲状腺细针穿刺活检(FNA)两种。超声检查为无创性检查，其通过超声下结节表现的可疑恶性特征如微小钙化、纵横比＞1等进行诊断。2015年美国甲状腺协会推荐使用的TI-RADS超声分级系统，根据超声下的可疑恶性特征将甲状腺结节分成7级，当判断分级为4级或以上时，即认为中度或以上可疑恶性，需要进行穿刺检查或者手术治疗。但超声检查较多依赖于检查者的主观认知以及诊断经验，且当甲状腺结节较小时可疑的恶性征象较少出现，因此超声检查目前在结节良恶性的诊断上存在容易漏判、误判等不足。其次，FNA作为术前甲状腺结节诊断的重要手段，对穿刺技术以及取样质量均有较高要求，对于≤1cm的结节取材成功率仅为37.5％，且有15％-41.6％的样本在活检后依然无法鉴别良恶性。而FNA作为有创操作，穿刺部位血肿或者血管迷走神经反应等并发症风险与之共存，这不仅对操作者技术有较高要求，且增加了患者的精神负担。因此在临床上，如何精准诊断甲状腺结节的良恶性成为甲状腺疾病治疗上的一大难题。
肿瘤分子标志物的检测是肿瘤诊断学中的一大热点。2015年ATA指南推荐对甲状腺肿瘤进行分子标志物的检测以辅助诊断以及指导治疗。但目前尚未找到单一或者多个联合的分子指标可以对甲状腺的良恶性结节进行有效诊断，BRAF
V600E作为甲状腺乳头状癌中最常见的体细胞突变，但仍较少证明其作为血液肿瘤标志物的可行性和可靠性。此外，DNA甲基化、microRNA和lncRNA等标志物组合，同样受限于较小的样本量以及不稳定性等问题未能有效验证其诊断效能。因此，寻找简便且有效的液体活检方法以鉴别诊断良恶性结节具有重要的现实意 义。
在既往基于组织标本的甲状腺癌代谢组学研究中，已经有多个研究证明了在甲状腺癌与甲状腺良性结节组织之间存在明显的代谢差异。但遗憾的是，基于血清学标本的多个研究则呈现出具有分歧的结果，仍缺少大样本量的发现队列用于代谢标志物挖掘以及后续的验证。因此，本发明开展了应用代谢组学技术探讨代谢标志物组合应用于甲状腺结节诊断的相关研究。而利用血浆标本代谢组学技术检测分析代谢标志物、术前鉴别甲状腺结节良恶性并取得较好诊断效能的研究尚未见报道。
发明内容
本发明的目的在于提供一种术前鉴别甲状腺良恶性结节的血清学生物标志物及其试剂盒在甲状腺良恶性结节诊断方面的应用，以克服现有技术在甲状腺良恶性结节诊断的缺陷和不足，提高甲状腺结节的诊断的精确率。
为了实现上述目的，本发明采用了以下技术方案：
本发明提供一种术前鉴别甲状腺良恶性结节的血清学生物标志物，所述标志物为甲状腺结节病人术前血清学标本中的17种代谢物，分别为加巴喷丁、辛酰甘氨酸、硫酸雄甾酮、戊酸、三乙醇胺、咪唑乙酸、异高香草酸、右雷佐生、磷脂酰胆碱(18:3(6Z,9Z,12Z)/15:0)、左乙拉西坦、单乙基甘氨酰二糖、泛醇、壬二酸、伊巴巴胺、α-生育酚、对烯丙基苯酚、异戊烯。
本发明提供一种试剂盒，所述试剂盒包括上述血清学生物标志物。
本发明还提供一种上述生物标志物及其试剂盒在甲状腺良恶性结节鉴别诊断中的应用，利用甲状腺结节病人的血浆标本检测17种代谢物，根据结果进行甲状腺良恶性结节的鉴别诊断，具体包括以下步骤：
(1)于空腹状态下用紫色EDTA-K2抗凝采血管采集甲状腺结节患者的外周血(上臂静脉)1-2ml；
(2)在采集后的两小时内，将外周血标本于4℃下，3500rpm离心12min；
(3)分离上层血浆于新的EP管中，在使用前保存于-80℃冰箱；
(4)移取100ul血浆样品至EP管中，按照流程提取血浆中的代谢物(甲醇、丁腈、含同位素标记内标混合物)；
(5)将提取后的样品放入瓶中上机检测，使用Vanquish (ThermoFisherScientific)超高效液相质谱仪进行测定，ThermoQExactiveHFX质谱仪在控制软件(Xcalibur，Thermo)控制下进行一级、二级质谱数据采集；原始数据经ProteoWizard软件转成mzXML格式后，使用R语言进行峰识别、提取、对齐、积分等处理，后与对应质谱数据库进行物质注释；
(6)应用R和线上工具MetaAnalyst进行代谢组学数据分析，应用支持向量机(SVM)建立诊断模型，绘制ROC曲线后使用Youden指数求最佳临界概率值为0.5，作为诊断甲状腺结节良恶性的截点。
在甲状腺结节患者的血浆样本中可以检测出上述17种代谢物。其中与甲状腺良性结节病人相比，在甲状腺癌患者血浆中加巴喷丁、辛酰甘氨酸、硫酸雄甾酮、戊酸、三乙醇胺、右雷佐生、咪唑乙酸、异高香草酸、磷脂酰胆碱(18:3(6Z,9Z,12Z)/15:0)的水平明显上升，而左乙拉西坦、单乙基甘氨酰二糖、泛醇、壬二酸、伊巴巴胺、α-生育酚、异戊烯、对烯丙基苯酚的水平明显降低。
与现有技术相比，本发明的有益效果如下：
(1)本发明首次发现上述17种代谢物的水平变化与甲状腺良恶性结节相关，采用代谢组学分析发现检测甲状腺结节病人外周血血浆中17种代谢物的水平，结合组学分析以及机器学习方法，构建诊断模型并使用受试者工作曲线(ROC)评价诊断甲状腺癌的效能。由上述代谢物组成的代谢标志物组合诊断模型在甲状腺结节诊断中ROC曲线下的面积可达到95.05％，敏感度与特异度均高于88％。并且该代谢标志物的诊断效能与肿瘤直径、是否存在淋巴结转移情况等无显著相关性，可应用于微小结节诊断以及早期甲状腺癌的诊断。
(2)与细针穿刺活检(FNA)相比，血清学代谢标志物通过采集外周血样即可进行诊断，创伤性明显更小，可避免穿刺部位血肿、迷走神经反应等不良反应。无需通过有创性操作获得手术标本，减少患者的精神负担和避免不必要的治疗。血浆代谢标志物可以在超声提示可疑恶性的情况下进行进一步的鉴别诊断，对于良恶性结节鉴别方面敏感度与特异度均较超声检查高，可有效避免不必要的活检或者诊断性手术。
下面结合实施例具体介绍本发明的技术方案。
使用循环代谢标志物组合检测甲状腺结节患者血浆标本以鉴别诊断良恶性 结节：
1、血浆取样
选取2018年1月至2019年12月于中山大学附属第一医院甲乳外科行甲状腺切除手术的甲状腺结节患者。入选共340名患者，入选标准：(1)组织病理学诊断为甲状腺乳头状癌或甲状腺良性结节；(2)无其他恶性肿瘤或无严重的免疫、神经、消化或血液系统疾病；(3)可获得术前或者术后的血液样本。排除标准：(1)合并其他类型的恶性肿瘤；(2)合并严重的免疫、神经、消化、或血液系统等疾病；(3)不能或者不适合获得术前外周血液标本。手术患者以术后石蜡病理以及免疫组化结果作为诊断金标准。术前血浆收集于患者入院后第二天清晨，于空腹状态下在上臂静脉采集，外周血标本经4℃3500rpm离心12min后分离上层血浆。分离血浆过程在采血后2小时内完成，分离后的血浆保存在-80℃冰箱内直至代谢组学检测。
2、代谢物提取和上机检测
(1)本发明涉及代谢物提取的试剂为本领域周知代谢物提取中所用的试剂；
(2)全程于冰上进行操作。通过天平移取100μL样品至EP管中，加入400μL提取液(甲醇：丁腈＝1：1(V/V)，含同位素标记内标混合物)，涡旋混匀30s；
(3)超声冰水浴10min后，于-40℃静置1h；
(4)将混合物样品于4℃离心机中12000rpm离心15min；
(5)取上清液于进样瓶中上机检测。
(6)所有样品另取等量的上清混合呈QC样品上机检测；
(7)本发明，血液标本代谢组学检测方法本领域周知，例如基于非靶标代谢组学检测技术、靶标代谢组学检测技术。其具体技术平台可基于气质联用质谱(GC-MS)、液质联用质谱(LC-MS)以及核磁共振氢谱(1H-NMR)；
(8)本实施例中代谢组学检测使用了Vanquish超高效液相质谱仪(ThermoFisherScientific)，以及WatersACQOUITYUPLCBEHAmide液相色谱柱对目标化合物进行色谱分离。液相色谱A相为水相，含25mmol/L乙酸铵和25mmol/L氨水，B相为乙腈。采用梯度洗脱：0～0.5min,95％B；0.5～7min,95％～65％B；7～8min,65％～40％B；8～9min,40％B；9～9.1min,40％～95％B；9.1～12min,95％B。流动相流速：0.5mL/min，柱温：30℃，样品盘温度：4℃，进样 体积3μL；
(9)Thermo Q Exactive HFX质谱仪能够在控制软件(Xcalibur，Thermo)控制下进行一级、二级质谱数据采集。详细参数如下：Sheath gas flow rate:50 Arb,Aux gas flow rate:10 Arb,Capillary temperature:320℃,Full ms resolution:60000,MS/MS resolution:7500,Collision energy:10/30/60in NCE mode,Spray Voltage:3.5kV(positive)或-3.2kV(negative)。
3、数据处理
原始数据经ProteoWizard软件转成mzXML格式后，使用自主编写的R程序包(内核为XCMS)进行峰识别、峰提取、峰对齐和积分等处理，然后与BiotreeDB(V2.1)自建二级质谱数据库匹配进行物质注释，算法打分的Cutoff值设为0.3。
4、代谢标志物诊断模型的建立
(1)对于MS二级质谱定性得出的代谢物数据，应用版本3.6.1的R和线上工具MetaAnalyst进行代谢组学学的分析。
(2)使用R软件的caret软件包，通过应用回归特征消除算法筛选出的17个差异代谢物作为代谢标志物，分别为加巴喷丁、辛酰甘氨酸、硫酸雄甾酮、戊酸、三乙醇胺、咪唑乙酸、异高香草酸、右雷佐生、磷脂酰胆碱(18:3(6Z,9Z,12Z)/15:0)、左乙拉西坦、单乙基甘氨酰二糖、泛醇、壬二酸、伊巴巴胺、α-生育酚、对烯丙基苯酚、异戊烯。以上代谢标志物的单个或多个组合都可能成为诊断甲状腺结节的标志物。
(3)为了验证代谢标志物进行甲状腺良恶性结节区分的能力，在发现队列中，基于筛选出的17个代谢标志物构建支持向量机(SVM)诊断模型。以及在验证队列中验证代谢标志物的诊断效果。
(4)应用R软件的caret软件包，输入由上述筛选得到的差异代谢标志物矩阵，构建SVM模型。通常，在构建模型过程中，将恶性类型编码为1，良性类型编码为0。训练模型过程中，默认阈值设定为0.5。构建出的模型也以0.5对样本进行良恶性的鉴别诊断。
(5)使用R软件pROC软件包绘制受试者操作曲线ROC以评估诊断模型效果。此外，应用随机森林分析方法亦可建立相应的诊断模型。
5、代谢标志物诊断模型的验证
利用上述甲状腺癌与甲状腺良性结节病人的血液样品进行代谢组学检测，根据检测结果中代谢物的相对水平，进行主成分、聚类等分析。上述代谢物在甲状腺癌与甲状腺良性结节患者的血浆水平对比间存在明显差异。
基于上述代谢标志物组合构建的SVM或随机森林诊断模型，在发现队列和验证队列中进行预测，输出的是预测疾病概率，默认评分阈值为0.5。发现队列样本340例，验证队列样本107例。
发现队列、验证队列经过SVM诊断模型的诊断，其受试者操作曲线(ROC)的曲线下面积(AUC)通过R软件的pROC软件包进行绘制。发现队列的AUC为95.05％，而验证队列的AUC为92.72％。而使用随机森林模型进行诊断，发现队列的AUC为88.07％，验证队列为86.66％。说明利用随机森林或者支持向量机建立的模型均有较好的诊断效能。
6、代谢标志物诊断效能的影响因素
纳入年龄、性别因素作为变量校正代谢标志物的SVM诊断模型，校正后发现队列的AUC(97.03％)与校正前无明显统计学差异，校正前后模型敏感度与特异度的改变也无统计学差异，说明该代谢标志物诊断模型的诊断效果不受年龄、性别的影响。其次根据淋巴结转移情况，对17个代谢标志物进行单一因素分析，发现17个代谢标志物在有淋巴结转移与无淋巴结转移患者之间水平无明显统计学差异，说明淋巴结转移情况对诊断模型无明显影响。最后，对发现队列与验证队列中≤1cm的结节进行诊断，AUC仍保持在较高水平，证明了该代谢标志物模型可以用于甲状腺癌的微小结节以及早期诊断。
| 校正年龄性别前 | 校正年龄性别后 | 统计学检验 | |
| AUC | 95.05％ | 97.03％ | p＝0.59 |
表1.校正前后AUC值
| 例数 | 17个生物标志物诊断曲线下面积(AUC) |
| 甲状腺结节340例(发现队列) | 95.05％ |
| 甲状腺结节107例(验证队列) | 92.72％ |
| 小于等于1cm的甲状腺结节132例 | 93.89％ |
表2.17个生物标志物诊断AUC值
对于连续性变量，如满足正态分布则采用t检验结果，否则采用秩和检验结果(“#”代表该变量采用秩和检验)
表3.有淋巴结转移与无淋巴结转移病人代谢物水平差异
本发明通过血浆中代谢物的水平来研究甲状腺良恶性结节病人的代谢状态差异，并筛选出17个具有差异的代谢标志物。基于此代谢标志物群，通过支持向量机或者随机森林方法，建立甲状腺良恶性结节诊断模型，可以有效鉴别甲状腺癌和甲状腺良性结节。与常用检查手段如超声、或者细针穿刺活检相比，代谢标志物诊断模型具有更高的灵敏度和特异度，且操作简便，创伤性小，有助于甲状腺结节的精确诊断与精准治疗，有望广泛应用于临床。
以上所述仅仅是本发明较优的实施方式，对于本技术领域的普通技术人员以及数据分析人员，在不脱离本发明方法的前提下，可以做出相应的改进和补充，这部分改进和补充也理应作为本发明的保护范围。
Claims (4)
- 一种术前鉴别甲状腺良恶性结节的血清学生物标志物，其特征在于，所述标志物为甲状腺结节病人术前血清学标本中的17种代谢物，分别为加巴喷丁、辛酰甘氨酸、硫酸雄甾酮、戊酸、三乙醇胺、咪唑乙酸、异高香草酸、右雷佐生、磷脂酰胆碱(18:3(6Z,9Z,12Z)/15:0)、左乙拉西坦、单乙基甘氨酰二糖、泛醇、壬二酸、伊巴巴胺、α-生育酚、对烯丙基苯酚、异戊烯。
- 一种试剂盒，其特征在于，所述试剂盒包括权利要求1所述的血清学生物标志物。
- 根据权利要求1或2所述生物标志物及其试剂盒在甲状腺良恶性结节鉴别诊断中的应用，其特征在于，利用甲状腺结节病人的血浆标本检测17种代谢物，根据结果进行甲状腺良恶性结节的鉴别诊断。
- 根据权利要求3所述生物标志物及其试剂盒在甲状腺良恶性结节鉴别诊断中的应用，其特征在于，包括以下步骤：(1)于空腹状态下用紫色EDTA-K2抗凝采血管采集甲状腺结节患者的上臂静脉血1-2ml；(2)在采集后的两小时内，将外周血标本于4℃下，3500rpm离心12min；(3)分离上层血浆于新的EP管中，在使用前保存于-80℃冰箱；(4)移取100ul血浆样品至EP管中，按照流程提取血浆中的代谢物，包括甲醇、丁腈、含同位素标记内标混合物；(5)将提取后的样品放入瓶中上机检测，使用Vanquish超高效液相质谱仪进行测定，ThermoQExactiveHFX质谱仪在控制软件Xcalibur控制下进行一级、二级质谱数据采集；原始数据经ProteoWizard软件转成mzXML格式后，使用R语言进行峰识别、提取、对齐、积分等处理，后与对应质谱数据库进行物质注释；(6)应用R软件和线上工具MetaAnalyst进行代谢组学数据分析，应用支持向量机建立诊断模型，绘制ROC曲线后使用Youden指数求最佳临界概率值为0.5，作为诊断甲状腺结节良恶性的截点。
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