A Novel Non- Invasive Index for Thyroid Cancer Diagnosis Based on Nuclear Matrix Protein-1, Angiogenic Factor-1, and Hyaluronic Acid

Background: The most typical endocrine cancer is thyroid cancer. Tumor biomarkers are genetic or protein-level compounds or specific evaluable traits. They assist in improving patient management. The goal of this study was to assess the ability of individual and combined potential markers (hyaluronic acid (HA), nuclear matrix protein (NMP-1), and angiopoietin-1) for thyroid cancer diagnosis. Patients and methods: This study registered 145 people (n=145), including 60 thyroid cancer, 65 benign group and 20 healthy controls. According to fine-needle aspiration (FNA) biopsy, Histopathological findings were divided into benign and thyroid cancer groups. The latter was further staged using the TNM approach, where (T) stands for tumor size and local invasion, (N) for nodal metastases, and (m) for distant metastases. We used biochemical routine profile tests like Total triiodoyhyronine (T3), Total thyroxine (T4), free Triiodothyronine (FT3), Free thyroxine (FT4), and thyroid-stimulating hormone (TSH). These measurements were done using Mini Vidas, Biomerieux, and ST-200 plus electrolyte analyzer (ELFA). We also measured HA, NMP-1 and ANG-1 by using Sandwich Enzyme-Linked Immunosorbent Assay (ELISA) technique .Results: The diagnostic performances of single and combined markers were evaluated using area under Roc curve. An area under the Roc curve of 0.81, 0.62, and 0.67, respectively, was observed for hyaluronic acid, NMP, and ANG. The best marker for identifying thyroid is HA, A three-marker index called thyroid markers (hyaluronic acid, NMP, ANG) was developed. The thyroid mark's diagnostic performance at a selected cutoff index of 6.2. The thyroid marker's AUC was 0.87, its sensitivity was 86%, and its specificity was 80% when it came to distinguishing thyroid cancer from benign conditions. When distinguishing thyroid cancer from healthy individuals, the thyroid mark's AUC was 0.96, its sensitivity was 96%, and its specificity was 100%. Conclusion: HA, NMP-1 and ANG-1 are effective biomarkers to distinguish between thyroid cancer and benign with acceptable sensitivity and specifity.

Authors

Institutions

Publication Details

Journal
Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology/Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology
Published
2024-12-26
DOI
https://doi.org/10.21608/eajbsc.2024.399221
Primary Topic
Thyroid Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Novel Non- Invasive Index for Thyroid Cancer Diagnosis Based on Nuclear Matrix Protein-1, Angiogenic Factor-1, and Hyaluronic Acid

Magdy M. Youssef, Mohamed M. Omran, Tarek M. Emran, Amr Abouzid et al.
Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology/Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology
Thyroid Cancer Diagnosis and Treatment
article

A Novel Non- Invasive Index for Thyroid Cancer Diagnosis Based on Nuclear Matrix Protein-1, Angiogenic Factor-1, and Hyaluronic Acid

Magdy M. Youssef, Mohamed M. Omran, Tarek M. Emran, Amr Abouzid, Basima Hassan, Manar Refaat
article en

Abstract

Background: The most typical endocrine cancer is thyroid cancer. Tumor biomarkers are genetic or protein-level compounds or specific evaluable traits. They assist in improving patient management. The goal of this study was to assess the ability of individual and combined potential markers (hyaluronic acid (HA), nuclear matrix protein (NMP-1), and angiopoietin-1) for thyroid cancer diagnosis. Patients and methods: This study registered 145 people (n=145), including 60 thyroid cancer, 65 benign group and 20 healthy controls. According to fine-needle aspiration (FNA) biopsy, Histopathological findings were divided into benign and thyroid cancer groups. The latter was further staged using the TNM approach, where (T) stands for tumor size and local invasion, (N) for nodal metastases, and (m) for distant metastases. We used biochemical routine profile tests like Total triiodoyhyronine (T3), Total thyroxine (T4), free Triiodothyronine (FT3), Free thyroxine (FT4), and thyroid-stimulating hormone (TSH). These measurements were done using Mini Vidas, Biomerieux, and ST-200 plus electrolyte analyzer (ELFA). We also measured HA, NMP-1 and ANG-1 by using Sandwich Enzyme-Linked Immunosorbent Assay (ELISA) technique .Results: The diagnostic performances of single and combined markers were evaluated using area under Roc curve. An area under the Roc curve of 0.81, 0.62, and 0.67, respectively, was observed for hyaluronic acid, NMP, and ANG. The best marker for identifying thyroid is HA, A three-marker index called thyroid markers (hyaluronic acid, NMP, ANG) was developed. The thyroid mark's diagnostic performance at a selected cutoff index of 6.2. The thyroid marker's AUC was 0.87, its sensitivity was 86%, and its specificity was 80% when it came to distinguishing thyroid cancer from benign conditions. When distinguishing thyroid cancer from healthy individuals, the thyroid mark's AUC was 0.96, its sensitivity was 96%, and its specificity was 100%. Conclusion: HA, NMP-1 and ANG-1 are effective biomarkers to distinguish between thyroid cancer and benign with acceptable sensitivity and specifity.

Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology/Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular BiologyVol. 16(2)
Al-Azhar University (EG), Helwan University (EG)
Good health and well-being
Openalex Percentile: Top 63%
Thyroid Cancer Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.