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Spontaneous Murine Model of Anaplastic Thyroid Cancer
Published on: February 3, 2023
Microarray analysis refines classification of non-medullary thyroid tumours of uncertain malignancy
J-F Fontaine1, D Mirebeau-Prunier, B Franc
1INSERM U 694, Angers, France. frsavagner@chu-angers.fr
Oncogene
|October 31, 2007
Summary
This study identifies key genes to help classify thyroid tumours of uncertain malignancy (T-UM), distinguishing benign from malignant cases. Molecular analysis refines diagnosis for these challenging thyroid lesions.
Area of Science:
- Endocrinology
- Molecular Biology
- Oncology
Background:
- Histological classification of non-medullary thyroid lesions faces challenges, particularly with tumours of uncertain malignancy (T-UM).
- T-UM encompass atypical follicular adenomas and tumours of uncertain malignant potential, requiring refined diagnostic criteria.
- Existing diagnostic methods struggle to definitively categorize a subset of thyroid tumours.
Purpose of the Study:
- To refine the classification of tumours of uncertain malignancy (T-UM) in follicular thyroid tumours.
- To identify diagnostic markers for distinguishing benign from malignant T-UM using gene expression profiling.
- To correlate molecular profiles with pathological scoring for improved diagnostic accuracy.
Main Methods:
- Microarray analysis of gene expression in 93 follicular thyroid tumours (including T-UM, carcinomas, adenomas) and 73 controls.
- Validation of 16 selected genes using real-time quantitative RT-PCR on additional T-UM samples.
- Examination of gene expression profiles in relation to RET/PTC, BRAF, and RAS gene mutational status.
- Estimation of pathological scores (histological and immunohistochemical) for T-UM.
Main Results:
- Gene expression profiles revealed heterogeneity within T-UM, with some showing molecular similarities to true carcinomas.
- Correlation between T-UM gene profiles and pathological scores enabled separation into benign and malignant groups.
- Identification of specific marker genes with diagnostic potential for T-UM classification.
- Validation of gene expression signatures through RT-PCR confirmed their diagnostic utility.
Conclusions:
- Molecular profiling, particularly gene expression, offers valuable insights into the classification of T-UM.
- Certain marker genes can serve as diagnostic tools for differentiating benign from malignant T-UM.
- A comprehensive pathological scoring system, combined with molecular data, is essential for accurate T-UM diagnosis.
