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Open AccessArticle

Gene Expression Patterns Unveil New Insights in Papillary Thyroid Cancer

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Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 40015 Cluj-Napoca, Romania
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Research Center for Functional Genomics and Translational Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 23 Marinescu Street, 40015 Cluj-Napoca, Romania
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MEDFUTURE-Research Center for Advanced Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania, 23 Marinescu Street, 40015 Cluj-Napoca, Romania
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Department of Surgery, The Oncology Institute “Prof. Dr. Ion Chiricuta”, 40015 Cluj-Napoca, Romania
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Department of Surgical Oncology and Gynecological Oncology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania, 40015 Cluj-Napoca, Romania
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Department of Nuclear Medicine and Endocrinology, The Oncology Institute “Prof. Dr. Ion Chiricuta”, 40015 Cluj-Napoca, Romania
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Department of Oncology, Iuliu Hatieganu University of Medicine and Pharmacy, 40015 Cluj-Napoca, Romania
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Department of Functional Genomics and Experimental Pathology, The Oncology Institute “Prof. Dr. Ion Chiricuta”, Republicii 34th street, 400015 Cluj-Napoca, Romania
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Author to whom correspondence should be addressed.
Medicina 2019, 55(8), 500; https://doi.org/10.3390/medicina55080500
Received: 16 May 2019 / Revised: 22 July 2019 / Accepted: 13 August 2019 / Published: 19 August 2019
Background and objectives: Papillary thyroid carcinoma is the most frequent variety of all malignant endocrine tumors. It represents a heterogeneous malignancy with various clinical outcomes, emphasizing the need to identify powerful biomarkers with clinical relevance. Materials and Methods: Available gene expression data (level 3) for thyroid cancers were downloaded from the Cancer Genome Atlas (TCGA), followed by bioinformatic analyses performed on the data set. Results: Based on gene expression analysis, we were able to identify common and specific gene signatures for the three main types of papillary thyroid carcinoma (classical, follicular variant, and tall-cell). The survival rate was not significantly different among the main subtypes, but we were able to identify a biological adhesion signature with impact in patient prognostic. Conclusions: Taken together, the gene expression signature and particular adhesion signature, along with ITGA10 and MSLN in particular, could be used as a prognostic tool with important clinical relevance. View Full-Text
Keywords: thyroid papillary cancer; Cancer Genome Atlas (TCGA); gene expression and biological adhesion signature thyroid papillary cancer; Cancer Genome Atlas (TCGA); gene expression and biological adhesion signature
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MDPI and ACS Style

Saftencu, M.; Braicu, C.; Cojocneanu, R.; Buse, M.; Irimie, A.; Piciu, D.; Berindan-Neagoe, I. Gene Expression Patterns Unveil New Insights in Papillary Thyroid Cancer. Medicina 2019, 55, 500. https://doi.org/10.3390/medicina55080500

AMA Style

Saftencu M, Braicu C, Cojocneanu R, Buse M, Irimie A, Piciu D, Berindan-Neagoe I. Gene Expression Patterns Unveil New Insights in Papillary Thyroid Cancer. Medicina. 2019; 55(8):500. https://doi.org/10.3390/medicina55080500

Chicago/Turabian Style

Saftencu, Mihai; Braicu, Cornelia; Cojocneanu, Roxana; Buse, Mihail; Irimie, Alexandru; Piciu, Doina; Berindan-Neagoe, Ioana. 2019. "Gene Expression Patterns Unveil New Insights in Papillary Thyroid Cancer" Medicina 55, no. 8: 500. https://doi.org/10.3390/medicina55080500

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