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Barki M, Xue H. GABRB2, a key player in neuropsychiatric disorders and beyond. Gene 2022; 809:146021. [PMID: 34673206 DOI: 10.1016/j.gene.2021.146021] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 08/05/2021] [Accepted: 09/14/2021] [Indexed: 01/11/2023]
Abstract
The GABA receptors represent the main inhibitory system in the central nervous system that ensure synaptogenesis, neurogenesis, and the regulation of neuronal plasticity and learning. GABAA receptors are pentameric in structure and belong to the Cys-loop superfamily. The GABRB2 gene, located on chromosome 5q34, encodes the β2 subunit that combines with the α and γ subunits to form the major subtype of GABAA receptors, which account for 43% of all GABAA receptors in the mammalian brain. Each subunit probably consists of an extracellular N-terminal domain, four membrane-spanning segments, a large intracellular loop between TM3 and TM4, and an extracellular C-terminal domain. Alternative splicing of the RNA transcript of the GABRB2 gene gives rise at least to four long and short isoforms with dissimilar electrophysiological properties. Furthermore, GABRB2 is imprinted and subjected to epigenetic regulation and positive selection. It has been associated with schizophrenia first in Han Chinese, and subsequently validated in other populations. Gabrb2 knockout mice also exhibited schizophrenia-like behavior and neuroinflammation that were ameliorated by the antipsychotic drug risperidone. GABRB2 was also associated with other neuropsychiatric disorders including bipolar disorder, epilepsy, autism spectrum disorder, Alzheimer's disease, frontotemporal dementia, substance dependence, depression, internet gaming disorder, and premenstrual dysphoric disorder. Recently, it has been postulated that GABRB2 might be a potential marker for different cancer types. As GABRB2 has a pivotal role in the central nervous system and is increasingly recognized to contribute to human diseases, further understanding of its structure and function may expedite the generation of new therapeutic approaches.
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Affiliation(s)
- Manel Barki
- Center for Cancer Genomics, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China
| | - Hong Xue
- Center for Cancer Genomics, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China; Division of Life Science and Applied Genomics Center, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China.
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2
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Liu C, Zhang L, Liu Y, Zhao Q, Pan Y, Zhang Y. Value of Pyruvate Carboxylase in Thyroid Fine-Needle Aspiration Wash-Out Fluid for Predicting Papillary Thyroid Cancer Lymph Node Metastasis. Front Oncol 2021; 11:643416. [PMID: 34136384 PMCID: PMC8202284 DOI: 10.3389/fonc.2021.643416] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 04/19/2021] [Indexed: 01/21/2023] Open
Abstract
The incidence of papillary thyroid carcinoma (PTC) is increasing. Lymph node metastatic status of PTC is a major factor for decision marking of surgery and surgical extend, however, no reliable tool exists for prediction of PTC nodal metastasis, for example, ultrasound cannot qualitatively diagnose and effectively detect central lymph node metastasis (CLNM). Therefore, the development of a new diagnostic biomarker is crucial for CLNM. Metabolic dysregulation is an important factor associated with malignancy and metastasis of tumors. Pyruvate carboxylase (PC) is a major anaplerotic enzyme that catalyzes the carboxylation of pyruvate to form oxaloacetate, which has been suggested to be involved in the tumorigenesis of several cancers, including PTC. This study aimed to explore the role of PC expression in thyroid fine-needle aspiration (FNA) wash-out fluid for predicting CLNM in PTC, and to explore how PC is involved in PTC development. The expression levels of PC in PTC tissues and normal thyroid tissues were first compared based on bioinformatics analysis of public databases, including the Gene Expression Profiling (GEPIA), Oncomine and Gene Expression Omnibus (GEO) databases. Then, the PC mRNA and protein expression levels were measured by RT-PCR and Immunohistochemistry (IHC) in surgical tissues from a total of 42 patients with surgically confirmed PTC, and compared in patients with and without CLNM. Further, to assess PC expression in diagnostic biopsies, a total of 71 thyroid nodule patients with ultrasound-guided FNA wash-out fluid samples and cytological diagnosis were prospectively enrolled in the study. Then, we analyzed the mechanism of PC-mediated PTC progression in vitro. This study showed that PC expression was higher in PTC tissues and thyroid FNA wash-out fluid samples from patients with CLNM than those from patients without CLNM, and that PC-induced PTC metastasis may occur through the TGF-β/Smad-regulated epithelial-mesenchymal transition (EMT) pathway.
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Affiliation(s)
- Chang Liu
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lu Zhang
- Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yang Liu
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qingqing Zhao
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Pan
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yifan Zhang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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3
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Lopez-Campistrous A, Adewuyi EE, Williams DC, McMullen TPW. Gene expression profile of epithelial-mesenchymal transition mediators in papillary thyroid cancer. Endocrine 2021; 72:452-461. [PMID: 32914379 DOI: 10.1007/s12020-020-02466-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 08/19/2020] [Indexed: 01/06/2023]
Abstract
PURPOSE Platelet derived growth receptor alpha (PDGFRA) promotes the epithelial-mesenchymal transition (EMT) in thyroid follicular cells and is linked to lymphatic metastases in papillary thyroid cancer (PTC). We probed the regulatory network of genes linked to PDGFRA and EMT, comparing matched patient primary tumor and metastatic specimens, as well as engineered cell lines and ex vivo primary cultures with and without PDGFRA. METHODS Freshly isolated thyroid tumors with or without metastases, with matching neighboring benign or normal tissue, was isolated for comparative transcriptional analysis using a TaqMan Low Density array (TLDA) assay with genes representing important markers of EMT, cellular adhesion, apoptosis, differentiation, senescence, and signal transduction pathways in thyroid cancer. Transfected primary cultures and immortalized cell lines were also analyzed with respect to PDGFRA expression and cell phenotype. RESULTS We reveal the consistent upregulation of serine protease DPP4 and structural protein SPP1 with the progression of PTC to metastatic disease, as well as with PDGFRA expression. Conversely, epithelial integrity gene TFF3 and transcription factor SOX10 were strongly down-regulated. This gene network also includes important mediators of EMT including DSG1, MMP3, MMP9, and BECN. We observed similar genomic changes in ex vivo normal thyroid cells transfected with PDGFRA that also exhibited a partially dedifferentiated phenotype. In particular, we observed lamellopodia with induction of PDGFRA and illustrate that DPP4 and SPP1 were upregulated in this process, with decreased TFF3 and SOX10 as seen in tissue specimens. PDGFRA did decrease nuclear protein levels of differentiation factor TTF1, but not the transcription of TTF1 and PAX8. CONCLUSIONS We demonstrate that PDGFRA activates EMT pathways and decreases expression of genes favoring epithelial integrity, pushing follicular cells toward a dedifferentiated phenotype. SPP1 and DPP4, previously linked with adverse outcomes in thyroid cancer, appear to be regulated by PDGFRA. PDGFRA expression promotes metastatic disease through multiple EMT levers that favor formation of an invasive phenotype and increased metalloproteinase expression.
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Affiliation(s)
| | | | | | - Todd P W McMullen
- Department of Surgery, University of Alberta, Edmonton, Canada.
- Department of Oncology, University of Alberta, Edmonton, Canada.
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Sun M, Meng Q, Wang T, Liu T, Zhu Y, Qiu J, Lu W. Removal of manually induced artifacts in ultrasound images of thyroid nodules based on edge-connection and Criminisi image restoration algorithm. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 200:105868. [PMID: 33261943 DOI: 10.1016/j.cmpb.2020.105868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 11/14/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND AND OBJECTIVE There are various artificial markers in ultrasound images of thyroid nodules, which have impact on subsequent processing and computer-aided diagnosis. The purpose of this study was to develop an approach to automatically remove artifacts and restore ultrasound images of thyroid nodules. METHODS Fifty ultrasound images with manually induced artifacts were selected from publicly available and self-collected datasets. A combined approach was developed which consisted of two steps, artifacts detection and removal of the detected artifacts. Specifically, a novel edge-connection algorithm was used for artifact detection, detection accuracy and false discovery rate were used to evaluate the performance of artifact detection approaches. Criminisi algorithm was used for image restoration with peak signal-to-noise ratio (PSNR) and mean gradient difference to evaluate its performance. In addition, computation complexity was evaluated by execution time of relevant algorithms. RESULTS Results revealed that the proposed joint approach with edge-connection and Criminisi algorithm could achieve automatic artifacts removal. Mean detection accuracy and mean false discovery rate of the proposed edge-connection algorithm for the 50 ultrasound images were 0.86 and 1.50. Mean PSNR of the 50 restored images by Criminisi algorithm was 36.64 dB, and mean gradient difference of the restored images was -0.002 compared with the original images. CONCLUSIONS The proposed combined approach had a good detection accuracy for different types of manually induced artifacts, and could significantly improve PSNR of the ultrasound images. The proposed combined approach may have potential use for the repair of ultrasound images with artifacts.
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Affiliation(s)
- Ming Sun
- Medical Engineering and Technology Research Center, Shandong First Medical University & Shandong Academy of Medical Sciences; Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences
| | - Qinglong Meng
- Medical Engineering and Technology Research Center, Shandong First Medical University & Shandong Academy of Medical Sciences; Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences
| | - Ting Wang
- Medical Engineering and Technology Research Center, Shandong First Medical University & Shandong Academy of Medical Sciences; Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences
| | - Tianci Liu
- Medical Engineering and Technology Research Center, Shandong First Medical University & Shandong Academy of Medical Sciences; Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences
| | - Ye Zhu
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences
| | - Jianfeng Qiu
- Medical Engineering and Technology Research Center, Shandong First Medical University & Shandong Academy of Medical Sciences; Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences
| | - Weizhao Lu
- Medical Engineering and Technology Research Center, Shandong First Medical University & Shandong Academy of Medical Sciences; Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences.
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Barros-Filho MC, Dos Reis MB, Beltrami CM, de Mello JBH, Marchi FA, Kuasne H, Drigo SA, de Andrade VP, Saieg MA, Pinto CAL, Kowalski LP, Rogatto SR. DNA Methylation-Based Method to Differentiate Malignant from Benign Thyroid Lesions. Thyroid 2019; 29:1244-1254. [PMID: 31328658 DOI: 10.1089/thy.2018.0458] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background: The differential diagnosis of thyroid nodules using fine-needle aspiration biopsy (FNAB) is challenging due to the inherent limitation of the cytology tests. The use of molecular markers has potential to complement the FNAB-based diagnosis and avoid unnecessary surgeries. In this study, we aimed to identify DNA methylation biomarkers and to develop a diagnostic tool useful for thyroid lesions. Methods: Genome-wide DNA methylation profiles (Illumina 450K) of papillary thyroid carcinoma (PTC = 60) and follicular thyroid carcinoma (FTC = 10) were compared with non-neoplastic thyroid tissue samples (NT = 50) and benign thyroid lesions (BTL = 17). The results were confirmed in publicly available databases from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) using the same DNA methylation platform. Two classifiers were trained to discriminate FTC and PTC from BTL. To increase the applicability of the method, six differentially methylated CpGs were selected and evaluated in 161 thyroid tumors and 69 BTL postsurgical specimens and 55 prospectively collected FNAB using bisulfite-pyrosequencing. Results: DNA methylation analysis revealed 2130 and 19 differentially methylated CpGs in PTC and FTC, respectively. The CpGs confirmed by GEO and TCGA databases showing high areas under the receiver operating characteristic curve in all sample sets were used to train our diagnostic classifier. The model based on six CpGs was able to differentiate benign from malignant thyroid lesions with 94.3% sensitivity and 82.4% specificity. A similar performance was found applying the algorithm to TCGA and GEO external data sets (91.3-97.4% sensitivity and 87.5% specificity). We successfully evaluated the classifiers using a bisulfite-pyrosequencing technique, achieving 90.7% sensitivity and 75.4% specificity in surgical specimens (five of six CpGs). The study comprising FNAB cytology materials corroborated the applicability and performance of the methodology, demonstrating 86.7% sensitivity and 89.5% specificity in confirmed malignant tumors, and 100% sensitivity and 89% specificity in cases with indeterminate cytology. Conclusions: A novel diagnostic tool with potential application in preoperative screening of thyroid nodules is reported here. The proposed protocol has the potential to avoid unnecessary thyroidectomies.
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Affiliation(s)
| | - Mariana Bisarro Dos Reis
- International Research Center - CIPE-A.C.Camargo Cancer Center, São Paulo, Brazil
- Faculty of Medicine, University of Sao Paulo State-UNESP, Botucatu, Brazil
| | | | | | | | - Hellen Kuasne
- International Research Center - CIPE-A.C.Camargo Cancer Center, São Paulo, Brazil
| | | | | | - Mauro Ajaj Saieg
- Department of Pathology, A.C.Camargo Cancer Center, São Paulo, Brazil
| | | | - Luiz Paulo Kowalski
- Department of Head and Neck Surgery and Otorhinolaryngology, A.C.Camargo Cancer Center, São Paulo, Brazil
| | - Silvia Regina Rogatto
- Department of Clinical Genetics, Vejle Hospital, Institute of Regional Health Research, University of Southern Denmark, Vejle, Denmark
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Zhao R, Zhang R, Tang T, Feng X, Li J, Liu Y, Zhu R, Wang G, Li K, Zhou W, Yang Y, Wang Y, Ba Y, Zhang J, Liu Y, Zhou F. TriZ-a rotation-tolerant image feature and its application in endoscope-based disease diagnosis. Comput Biol Med 2018; 99:182-190. [PMID: 29936284 DOI: 10.1016/j.compbiomed.2018.06.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Revised: 05/30/2018] [Accepted: 06/08/2018] [Indexed: 12/11/2022]
Abstract
Endoscopy is becoming one of the widely-used technologies to screen the gastric diseases, and it heavily relies on the experiences of the clinical endoscopists. The location, shape, and size are the typical patterns for the endoscopists to make the diagnosis decisions. The contrasting texture patterns also suggest the potential lesions. This study designed a novel rotation-tolerant image feature, TriZ, and demonstrated the effectiveness on both the rotation invariance and the lesion detection of three gastric lesion types, i.e., gastric polyp, gastric ulcer, and gastritis. TriZ achieved 87.0% in the four-class classification problem of the three gastric lesion types and the healthy controls, averaged over the twenty random runs of 10-fold cross-validations. Due to that biomedical imaging technologies may capture the lesion sites from different angles, the symmetric image feature extraction algorithm TriZ may facilitate the biomedical image based disease diagnosis modeling. Compared with the 378,434 features of the HOG algorithm, TriZ achieved a better accuracy using only 126 image features.
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Affiliation(s)
- Ruixue Zhao
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Ruochi Zhang
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Tongyu Tang
- First Hospital, Jilin University, Changchun, Jilin, 130012, China
| | - Xin Feng
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Jialiang Li
- College of Software, Jilin University, Changchun, Jilin, 130012, China
| | - Yue Liu
- College of Communication Engineering, Jilin University, Changchun, Jilin, 130012, China
| | - Renxiang Zhu
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Guangze Wang
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Kangning Li
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Wenyang Zhou
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Yunfei Yang
- College of Software, Jilin University, Changchun, Jilin, 130012, China
| | - Yuzhao Wang
- College of Software, Jilin University, Changchun, Jilin, 130012, China
| | - Yuanjie Ba
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Jiaojiao Zhang
- College of Software, Jilin University, Changchun, Jilin, 130012, China
| | - Yang Liu
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Fengfeng Zhou
- College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China.
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Sorrenti S, Baldini E, Tartaglia F, Catania A, Arcieri S, Pironi D, Calò PG, Filippini A, Ulisse S. Nodular thyroid disease in the elderly: novel molecular approaches for the diagnosis of malignancy. Aging Clin Exp Res 2017; 29:7-13. [PMID: 27832468 DOI: 10.1007/s40520-016-0654-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 10/12/2016] [Indexed: 12/14/2022]
Abstract
Epithelial thyroid cancers (TC) comprise two differentiated histotypes (DTC), the papillary (PTC) and the follicular (FTC) thyroid carcinomas which, following dedifferentiation, are assumed to give rise to the poorly differentiated thyroid carcinomas and the rare, but highly aggressive and invariably fatal, anaplastic thyroid carcinomas. Although thyroid cancer mortality has not been changed, its annual incidence has increased over the last two decades, mainly because of the improved ability to diagnose malignant transformation in small non-palpable thyroid nodules. Despite DTC patients have a favorable prognosis, aggressive disease is more frequently observed in the elderly showing a higher disease-specific mortality. Of relevance is the high prevalence of nodular thyroid disease in aged patients being higher than 90%, in women older than 60 year, and 60% in men older than 80 year. This implies a careful evaluation of thyroid nodules in this group of patients in order to exclude malignancy. In fact, despite the tremendous progress in the comprehension of the underlying molecular mechanisms deregulated in DTC progression, several aspects of their clinical management remain to be solved and novel diagnostic strategies are sorely needed. Here, we will attempt to review new molecular approaches, which are currently being exploited in order to ameliorate the diagnosis of thyroid nodules.
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Ren G, Krawetz R. Applying computation biology and "big data" to develop multiplex diagnostics for complex chronic diseases such as osteoarthritis. Biomarkers 2016; 20:533-9. [PMID: 26809774 PMCID: PMC4819822 DOI: 10.3109/1354750x.2015.1105499] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The data explosion in the last decade is revolutionizing diagnostics research and the healthcare industry, offering both opportunities and challenges. These high-throughput “omics” techniques have generated more scientific data in the last few years than in the entire history of mankind. Here we present a brief summary of how “big data” have influenced early diagnosis of complex diseases. We will also review some of the most commonly used “omics” techniques and their applications in diagnostics. Finally, we will discuss the issues brought by these new techniques when translating laboratory discoveries to clinical practice.
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Affiliation(s)
- Guomin Ren
- a McCaig Institute for Bone & Joint Health, University of Calgary , Calgary , AB , Canada
| | - Roman Krawetz
- a McCaig Institute for Bone & Joint Health, University of Calgary , Calgary , AB , Canada .,b Department of Surgery , University of Calgary , Calgary , AB , Canada , and.,c Department of Anatomy and Cell Biology , University of Calgary , Calgary , AB , Canada
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Ferris RL, Baloch Z, Bernet V, Chen A, Fahey TJ, Ganly I, Hodak SP, Kebebew E, Patel KN, Shaha A, Steward DL, Tufano RP, Wiseman SM, Carty SE. American Thyroid Association Statement on Surgical Application of Molecular Profiling for Thyroid Nodules: Current Impact on Perioperative Decision Making. Thyroid 2015; 25:760-8. [PMID: 26058403 PMCID: PMC4519104 DOI: 10.1089/thy.2014.0502] [Citation(s) in RCA: 157] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
BACKGROUND Recent advances in research on thyroid carcinogenesis have yielded applications of diagnostic molecular biomarkers and profiling panels in the management of thyroid nodules. The specific utility of these novel, clinically available molecular tests is becoming widely appreciated, especially in perioperative decision making by the surgeon regarding the need for surgery and the extent of initial resection. METHODS A task force was convened by the Surgical Affairs Committee of the American Thyroid Association and was charged with writing this article. RESULTS/CONCLUSIONS This review covers the clinical scenarios by cytologic category for which the thyroid surgeon may find molecular profiling results useful, particularly for cases with indeterminate fine-needle aspiration cytology. Distinct strengths of each ancillary test are highlighted to convey the current status of this evolving field, which has already demonstrated the potential to streamline decision making and reduce unnecessary surgery, with the accompanying benefits. However, the performance of any diagnostic test, that is, its positive predictive value and negative predictive value, are exquisitely influenced by the prevalence of cancer in that cytologic category, which is known to vary widely at different medical centers. Thus, it is crucial for the clinician to know the prevalence of malignancy within each indeterminate cytologic category, at one's own institution. Without this information, the performance of the diagnostic tests discussed below may vary substantially.
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Affiliation(s)
- Robert L. Ferris
- Division of Head and Neck Surgery, Department of Otolaryngology, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania
| | - Zubair Baloch
- Department of Pathology, University of Pennsylvania Medical Center, Philadelphia, Pennsylvania
| | - Victor Bernet
- Department of Endocrinology, Mayo Clinic, Jacksonville, Florida
| | - Amy Chen
- Department of Otolaryngology/Head and Neck Surgery, Emory University, Atlanta, Georgia
| | - Thomas J. Fahey
- Department of Surgery, New York Presbyterian Hospital, New York, New York
| | - Ian Ganly
- Head and Neck Service, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Steven P. Hodak
- Division of Endocrinology, New York University Medical Center, New York, New York
| | - Electron Kebebew
- Endocrine Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
| | - Kepal N. Patel
- Division of Endocrine Surgery, New York University Medical Center, New York, New York
| | - Ashok Shaha
- Head and Neck Service, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - David L. Steward
- Department of Otolaryngology/Head and Neck Surgery, University of Cincinnati Medical Center, Cincinnati, Ohio
| | - Ralph P. Tufano
- Department of Otolaryngology/Head and Neck Surgery, Johns Hopkins University, Baltimore, Maryland
| | - Sam M. Wiseman
- Department of Surgery, Division of General Surgery, St. Paul's Hospital and University of British Columbia, Vancouver, Canada
| | - Sally E. Carty
- Division of Endocrine Surgery, Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
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Patel HH, Goyal N, Goldenberg D. Imaging, genetic testing, and biomarker assessment of follicular cell-derived thyroid cancer. Ann Med 2014; 46:409-16. [PMID: 24987865 DOI: 10.3109/07853890.2014.923739] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Thyroid carcinoma is the most common endocrine malignancy worldwide, and its incidence continues to increase. As such the approach to a recently identified thyroid nodule is important to understand. The relevant imaging, examination, and need for fine-needle aspiration biopsy (FNA) are discussed. In approximately 25% of nodules, the diagnosis cannot be established with FNA-based cytology, and surgical excision is necessary for definitive diagnosis. Recent advances in genetic and molecular testing may increase the diagnostic accuracy of FNA in managing thyroid nodules.
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Affiliation(s)
- Hetal H Patel
- Penn State Milton S. Hershey Medical Center, Department of Surgery, Division of Otolaryngology-Head and Neck Surgery , Hershey, Pennsylvania , USA
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Eszlinger M, Hegedüs L, Paschke R. Ruling in or ruling out thyroid malignancy by molecular diagnostics of thyroid nodules. Best Pract Res Clin Endocrinol Metab 2014; 28:545-57. [PMID: 25047205 DOI: 10.1016/j.beem.2014.01.011] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Routine morphologic cytology is the basis for any kind of (integrated) molecular FNA diagnostics. The rule out (gene expression classifier) approach requires confirmation by independent studies, whereas the rule in approach (detection of BRAF, NRAS, HRAS, and KRAS and PAX8/PPARG- and RET/PTC rearrangements) has been investigated by several groups with overall reproducible results. Moreover, molecular screening for point mutations and rearrangements is feasible in routine air-dried FNA smears, offering several advantages over obtaining additional fresh FNA material. The current panel of somatic mutations (rule in approach) for indeterminate FNAs clarifies only a subgroup of indeterminate FNAs. Therefore, further markers are urgently needed that can reliably identify the malignant, but mutation negative and especially the many benign nodules, among the indeterminate FNAs. miRNA markers and the targeted next generation sequencing (NGS) technology do have the potential to identify those nodules that are mutation negative by current approaches.
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Affiliation(s)
- Markus Eszlinger
- Division of Endocrinology and Nephrology, University of Leipzig, Liebigstr. 21, D-04103 Leipzig, Germany.
| | - László Hegedüs
- Department of Endocrinology and Metabolism, Odense University Hospital, Odense, Denmark.
| | - Ralf Paschke
- Division of Endocrinology and Nephrology, University of Leipzig, Liebigstr. 20, D-04103 Leipzig, Germany.
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13
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Carbonic anhydrase 4 and crystallin α-B immunoreactivity may distinguish benign from malignant thyroid nodules in patients with indeterminate thyroid cytology. J Surg Res 2014; 190:565-74. [PMID: 24880201 DOI: 10.1016/j.jss.2014.03.042] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2014] [Revised: 03/07/2014] [Accepted: 03/14/2014] [Indexed: 01/21/2023]
Abstract
BACKGROUND Thyroid nodules are present in 19%-67% of the population and carry a 5%-10% risk of malignancy. Unfortunately, fine-needle aspiration biopsies are indeterminate in 20%-30% of patients, often necessitating thyroid surgery for diagnosis. Numerous DNA microarray studies including a recently commercialized molecular classifier have helped to better distinguish benign from malignant thyroid nodules. Unfortunately, these assays often require probes for >100 genes, are expensive, and only available at a few laboratories. We sought to validate these DNA microarray assays at the protein level and determine whether simple and widely available immunohistochemical biomarkers alone could distinguish benign from malignant thyroid nodules. METHODS A tissue microarray (TMA) composed of 26 follicular thyroid carcinomas (FTCs) and 53 follicular adenomas (FAs) from patients with indeterminate thyroid nodules was stained with 17 immunohistochemical biomarkers selected based on prior DNA microarray studies. Antibodies used included galectin 3, growth and differentiation factor 15, protein convertase 2, cluster of differentiation 44 (CD44), glutamic oxaloacetic transaminase 1 (GOT1), trefoil factor 3 (TFF3), Friedreich Ataxia gene (X123), fibroblast growth factor 13 (FGF13), carbonic anhydrase 4 (CA4), crystallin alpha-B (CRYAB), peptidylprolyl isomerase F (PPIF), asparagine synthase (ASNS), sodium channel, non-voltage gated, 1 alpha subunit (SCNN1A), frizzled homolog 1 (FZD1), tyrosine related protein 1 (TYRP1), E cadherin, type 1 (ECAD), and thyroid hormone receptor associated protein 220 (TRAP220). Of note, two of these biomarkers (GOT1 and CD44) are now used in the Afirma classifier assay. We chose to compare specifically FTC versus FA rather than include all histologic categories to create a more uniform immunohistochemical comparison. In addition, we have found that most papillary thyroid carcinoma could often be reasonably distinguished from benign disease by morphological cytology findings alone. RESULTS Increased immunoreactivity of CRYAB was associated with thyroid malignancy (c-statistic, 0.644; negative predictive value [NPV], 0.90) and loss of immunoreactivity of CA4 was also associated with malignancy (c-statistic, 0.715; NPV, 0.90) in indeterminate thyroid specimens. The combination of CA4 and CRYAB for discriminating FTC from FA resulted in a better c-statistic of 0.75, sensitivity of 0.76, specificity of 0.59, positive predictive value (PPV) of 0.32, and NPV of 0.91. When comparing widely angioinvasive FTC from FA, the resultant c-statistic improved to 0.84, sensitivity of 0.75, specificity of 0.76, PPV of 0.11, and NPV of 0.99. CONCLUSIONS Loss of CA4 and increase in CRYAB immunoreactivity distinguish FTC from FA in indeterminate thyroid nodules on a thyroid TMA with an NPV of 91%. Further studies in preoperative patient fine needle aspiration (FNAs) are needed to validate these results.
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