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      Extending expressed RNA genomics from surgical decision making for cytologically indeterminate thyroid nodules to targeting therapies for metastatic thyroid cancer

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The Afirma Genomic Sequencing Classifier (GSC) is a rule‐out test for malignancy/noninvasive follicular thyroid neoplasms with papillary‐like nuclear features among patients with Bethesda category III/IV nodules, whereas the complimentary Xpression Atlas provides genomic insights from a curated panel of 511 genes among GSC suspicious and Bethesda category V/VI nodules. Together, they facilitate personalized treatment decisions based on genomic insights derived from the transcriptome of the biopsied target and extend the diagnostic and therapeutic reach of cytopathologists and fine‐needle aspiration biopsy sample collection.

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          Most cited references 80

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          Integrated genomic characterization of papillary thyroid carcinoma.

            (2014)
          Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Here, we describe the genomic landscape of 496 PTCs. We observed a low frequency of somatic alterations (relative to other carcinomas) and extended the set of known PTC driver alterations to include EIF1AX, PPM1D, and CHEK2 and diverse gene fusions. These discoveries reduced the fraction of PTC cases with unknown oncogenic driver from 25% to 3.5%. Combined analyses of genomic variants, gene expression, and methylation demonstrated that different driver groups lead to different pathologies with distinct signaling and differentiation characteristics. Similarly, we identified distinct molecular subgroups of BRAF-mutant tumors, and multidimensional analyses highlighted a potential involvement of oncomiRs in less-differentiated subgroups. Our results propose a reclassification of thyroid cancers into molecular subtypes that better reflect their underlying signaling and differentiation properties, which has the potential to improve their pathological classification and better inform the management of the disease.
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            Preoperative diagnosis of benign thyroid nodules with indeterminate cytology.

            Approximately 15 to 30% of thyroid nodules evaluated by means of fine-needle aspiration are not clearly benign or malignant. Patients with cytologically indeterminate nodules are often referred for diagnostic surgery, though most of these nodules prove to be benign. A novel diagnostic test that measures the expression of 167 genes has shown promise in improving preoperative risk assessment. We performed a 19-month, prospective, multicenter validation study involving 49 clinical sites, 3789 patients, and 4812 fine-needle aspirates from thyroid nodules 1 cm or larger that required evaluation. We obtained 577 cytologically indeterminate aspirates, 413 of which had corresponding histopathological specimens from excised lesions. Results of a central, blinded histopathological review served as the reference standard. After inclusion criteria were met, a gene-expression classifier was used to test 265 indeterminate nodules in this analysis, and its performance was assessed. Of the 265 indeterminate nodules, 85 were malignant. The gene-expression classifier correctly identified 78 of the 85 nodules as suspicious (92% sensitivity; 95% confidence interval [CI], 84 to 97), with a specificity of 52% (95% CI, 44 to 59). The negative predictive values for "atypia (or follicular lesion) of undetermined clinical significance," "follicular neoplasm or lesion suspicious for follicular neoplasm," or "suspicious cytologic findings" were 95%, 94%, and 85%, respectively. Analysis of 7 aspirates with false negative results revealed that 6 had a paucity of thyroid follicular cells, suggesting insufficient sampling of the nodule. These data suggest consideration of a more conservative approach for most patients with thyroid nodules that are cytologically indeterminate on fine-needle aspiration and benign according to gene-expression classifier results. (Funded by Veracyte.).
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              The Bethesda System for Reporting Thyroid Cytopathology: a meta-analysis.

              We aimed to investigate the validity of the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) through meta-analysis. All publications between January 1, 2008 and September 1, 2011 that studied TBSRTC and had available histological follow-up data were retrieved. To calculate the sensitivity, specificity and diagnostic accuracy, the cases diagnosed as follicular neoplasm, suspicious for malignancy and malignant which were histopathologically confirmed as malignant were defined as true-positive. True-negative included benign cases confirmed as benign on histopathology. The nondiagnostic category was excluded from the statistical calculation. The correlations between the 6 diagnostic categories were investigated. The publications review resulted in a case cohort of 25,445 thyroid fine-needle aspirations, 6,362 (25%) of which underwent surgical excision; this group constituted the basis of the study. The sensitivity, specificity and diagnostic accuracy were 97, 50.7 and 68.8%, respectively. The positive predictive value and negative predictive value were 55.9 and 96.3%, respectively. The rates of false negatives and false positives were low: 3 and 0.5%, respectively. The results of meta-analysis showed high overall accuracy, indicating that TBSRTC represents a reliable and valid reporting system for thyroid cytology. Copyright © 2012 S. Karger AG, Basel.
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                Author and article information

                Contributors
                sali@jhmi.edu
                Journal
                Cancer Cytopathol
                Cancer Cytopathol
                10.1002/(ISSN)1934-6638
                CNCY
                Cancer Cytopathology
                John Wiley and Sons Inc. (Hoboken )
                1934-662X
                1934-6638
                24 April 2019
                June 2019
                : 127
                : 6 ( doiID: 10.1002/cncy.v127.6 )
                : 362-369
                Affiliations
                [ 1 ] Department of Pathology The Johns Hopkins Hospital Baltimore Maryland
                [ 2 ] Department of Radiology The Johns Hopkins Hospital Baltimore Maryland
                [ 3 ] Department of Endocrine Surgery Cleveland Clinic Cleveland Ohio
                [ 4 ] Department of Pathology Massachusetts General Hospital, Harvard Medical School Boston Massachusetts
                [ 5 ] Department of Medicine Florida International University, Memorial Healthcare System Hollywood Florida
                [ 6 ] Department of Clinical Affairs Veracyte Inc South San Francisco California
                [ 7 ] Department of Medical Affairs Veracyte Inc South San Francisco California
                [ 8 ] Department of Research and Development Veracyte Inc South San Francisco California
                [ 9 ] Division of Endocrinology, Diabetes, and Metabolism Department of Medicine Johns Hopkins University School of Medicine Baltimore Maryland
                Author notes
                [* ] Corresponding author: Syed Z. Ali, MD, FRCPath, FIAC, Department of Pathology, Rm 406, Pathology Building, The Johns Hopkins Hospital, 600 N. Wolfe St, Baltimore, MD 21287; sali@ 123456jhmi.edu

                Article
                CNCY22132
                10.1002/cncy.22132
                6618055
                31017745
                © 2019 The Authors. Cancer Cytopathology published by Wiley Periodicals, Inc. on behalf of American Cancer Society

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

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                Figures: 2, Tables: 0, Pages: 8, Words: 16527
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                cncy22132
                June 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.5 mode:remove_FC converted:10.07.2019

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