Project title
以基因體、代謝體與電腦影像分析改善甲狀腺結節細針穿刺細胞學檢查之診斷準確度與預後評估
Internal ID
MOST104-2314-B002-214
Principal Investigator
Start Date
August 1, 2015
End Date
July 12, 2016
Investigators
Organizations
Partner Organizations
Improving the Diagnostic Accuracy and Prognostic Prediction of Thyroid Nodules with Genomics, Metabolomics and Computerized Morphometry of Cytology Samples Obtained by Fine-Needle Aspiration = 以基因體、代謝體與電腦影像分析改善甲狀腺結節細針穿刺細胞學檢查之診斷準確度與預後評估
Keywords
曱狀腺結節
曱狀腺癌
基因體
代謝體
曱狀腺細胞之電腦程式影像分析
次世代定序
thyroid nodules
thyroid carcinoma
genomics
computerized morphometry
next-generation sequencing
metabolomics
Description
The prevalence of thyroid nodules is high and five to fifteen percent of these nodules are malignant; most of them are well-differentiated thyroid cancer, including papillary thyroid cancer (PTC) and follicular thyroid cancer (FTC). The current standard diagnostic tool is fine needle aspiration cytological (FNAC) examination of the nodules. The overall sensitivity and specificity is about 90%, which is far from perfect. Besides, 15% of the nodules evaluated by FNAC are indeterminate, especially in cases of follicular neoplasm. All of the obstacles become a thorny problem for both healthcare-givers and patients. In addition, study of the changes at molecular levels with the diagnosis and prognosis of thyroid cancer is very interesting and important. The goal of this study is to propose a reliable method for diagnosis and prognosis of papillary thyroid cancer and follicular thyroid cancer through analyzing genetic mutations, metabolites feature, and cellular morphologic characteristics. Clinical presentation, metabolites features, and cellular morphology are all important phenotypes of thyroid cancer. To improve the diagnostic and prognosis accuracy, this project integrates functional genomic approaches including genomics and metabolomics to establish a causal link between select biomarkers and disease pathogenesis. Among all the candidate genes, BRAFV600E and RAS mutation has been well-known detected in differentiated thyroid carcinoma. Mutation of BRAFV600E and RAS result in the activation of mitogen-activated protein kinase (MAPK) pathway and thus cell proliferation. They have also been associated with aggressive clinical behavior and poor prognosis. TERT promoter mutation was just discovered in thyroid cancer for one year, but has turned into the focus because of its risk in aggressive clinical behavior and higher prevalence in advanced thyroid cancer. Genetic mutations of several other genes were also reported. Sodium iodide symporter (NIS) is an important but under-explored target gene. BRAF mutation induces NIS regression and promotes epithelial to mesenchymal transition and invasion. We would like to examine the mutations of NIS, BRAFV600E, RAS, TERT, and other possible genes in FNAC specimens and explore the correlation of mutations, diagnosis, and prognosis. Sanger sequencing will be the method of choice for the known somatic mutation hotspots, but next-generation sequencing (NGS) will be used to more comprehensively search for disease-causing genes. NGS also has the potential to shed light on new pathophysiological pathways. Metabolomics has been demonstrated as a powerful tool to differentiate different types of thyroid nodules. However, previous studies mainly used tissue biopsy as study materials which limited its application in presurgical screening of thyroid nodules. This study uses a more sensitivity mass spectrometry based metabolomics platform to investigate tumor markers in FNAC specimens. We use a two steps approach by first identification of the metabolic differences between thyroid neoplasms, benign or malignant, and normal thyroid tissue in operative specimens and then test those differences on cells obtained through FNAC. According to our previous studies, cytological features of PTC, analyzed with computerized morphometry, are correlated with prognosis significantly. It helps to predict prognosis pre-operatively and to establish a risk-stratified treatment plan. In this current project, we plan to extend this tool to the diagnosis and/or prognosis of FTC and to nodules with uncertain FNAC reports to assist clinical management. In summary, this study applies a multi- and inter-disciplinary approach to improve the accuracy and sensitivity for diagnosis and prognosis of thyroid cancer using FNAC specimens. We will examine 120 samples, including groups of (a). PTC or FTC (40 samples), (b). Indeterminate (40 samples) and (c). Benign (40 samples). From our study with the comparison of phenotypes and genotypes, we anticipate to break the current diagnostic dilemma and limitation of poor prognostic prediction of thyroid nodules. Furthermore, we are longing to improve our understanding in thyroid cancer genesis which could disclosure novel diagnostic markers and treatment targets.