Diagnosis and Prognosis of Thyroid Cancer

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 373

Special Issue Editor


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Guest Editor
Department of Otorhinolaryngology—Head and Neck Surgery, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
Interests: thyroid; oncology; head and neck surgery; surgical oncology; cancer surgery minimally invasive surgery; surgical anatomy; operative surgery; robotic surgery

Special Issue Information

Dear Colleagues,

Thyroid cancer, a prevalent endocrine malignancy, poses a significant health burden. This Special Issue delves into the diagnosis and prognosis of thyroid cancer, exploring advancements in imaging techniques, biomarker discovery, and molecular profiling.

We invite you to contribute to our upcoming Special Issue dedicated to “Diagnosis and Prognosis of Thyroid Cancer”. This platform aims to gather the latest research advancements, innovative diagnostic methods, and prognostic tools in this field. We welcome submissions addressing all aspects of thyroid cancer, including imaging techniques, molecular markers, genetic profiling, and clinical outcomes. Your contributions can significantly advance the understanding and management of this complex condition. Submit your original research, reviews, or case studies to join our esteemed group of authors and contribute to the global effort in thyroid cancer research.

We are looking forward to receiving your valuable contributions.

Dr. Chang Myeon Song
Guest Editor

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Keywords

  • thyroid cancer
  • diagnostic methods
  • prognostic tools
  • molecular markers
  • clinical outcomes
  • imaging

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Published Papers (1 paper)

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Research

18 pages, 2713 KiB  
Article
In Search of Relevant Urinary Biomarkers for Thyroid Papillary Carcinoma and Benign Thyroid Nodule Differentiation, Targeting Metabolic Profiles and Pathways via UHPLC-QTOF-ESI+-MS Analysis
by Gabriela Maria Berinde, Andreea Iulia Socaciu, Mihai Adrian Socaciu, Gabriel Emil Petre, Armand Gabriel Rajnoveanu, Maria Barsan, Carmen Socaciu and Doina Piciu
Diagnostics 2024, 14(21), 2421; https://doi.org/10.3390/diagnostics14212421 - 30 Oct 2024
Viewed by 190
Abstract
Background: Identification of specific urine metabolic profiles for patients diagnosed with papillary thyroid carcinoma (TC) vs. benign nodules (B) to identify specific biomarkers and altered pathways compared to those of healthy controls (C). Methods: Patient urine samples were collected, before surgery and after [...] Read more.
Background: Identification of specific urine metabolic profiles for patients diagnosed with papillary thyroid carcinoma (TC) vs. benign nodules (B) to identify specific biomarkers and altered pathways compared to those of healthy controls (C). Methods: Patient urine samples were collected, before surgery and after a histological confirmation of TC (n = 30) and B (n = 30), in parallel with sample collection from healthy controls (n = 20). The untargeted and semi-targeted metabolomic protocols were applied using UPLC-QTOF-ESI+-MS analysis, and the statistical analysis was performed using the Metaboanalyst 6.0 platform. The results for the blood biomarkers, previously published, were compared with the data obtained from urine sampling using the Venny algorithm and multivariate statistics. Results: Partial least squares discrimination, including VIP values, random forest graphs, and heatmaps (p < 0.05), together with biomarker analysis (AUROC ranking) and pathway analysis, suggested a specific model for the urinary metabolic profile and pathway alterations in TC and B vs. C, based on 190 identified metabolites in urine that were compared with the serum metabolites. By semi-targeted metabolomics, 10 classes of metabolites, considered putative biomarkers, were found to be responsible for specific alterations in the metabolic pathways, from polar molecules to lipids. Specific biomarkers for discrimination were identified in each class of metabolites that were either upregulated or downregulated when compared to those of the controls. Conclusions: The lipidomic window was the most relevant for identifying biomarkers related to thyroid cancer and benign conditions, since this study detected a stronger involvement of lipids and selenium-related molecules for metabolic discrimination. Full article
(This article belongs to the Special Issue Diagnosis and Prognosis of Thyroid Cancer)
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