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Differential expression of a set of genes in follicular and classic variants of papillary thyroid carcinoma
- Source :
- Endocrine pathology. 22(2)
- Publication Year :
- 2011
-
Abstract
- Fine-needle aspiration biopsy (FNA) is currently the best initial diagnostic test for evaluation of a thyroid nodule. FNA cytology cannot discriminate between benign and malignant thyroid nodules in up to 30% of thyroid nodules. Therefore, an adjunct to FNA is needed to clarify these lesions as benign or malignant. Using differential display-polymerase chain reaction method, the gene expression differences between follicular and classic variants of papillary thyroid carcinoma (PTC) and benign thyroid nodules were evaluated in a group of 42 patients. Computational gene function analyses via Cytoscape, FuncBASE, and GeneMANIA led us to a functional network of 17 genes in which a core sub-network of five genes coexists. Although the exact mechanisms underlying in thyroid cancer biogenesis are not currently known, our data suggest that the pattern of transformation from healthy cells to cancer cells of PTC is different in follicular variant than in classic variant.
- Subjects :
- Thyroid nodules
Adult
Male
endocrine system
Pathology
medicine.medical_specialty
endocrine system diseases
Adolescent
Endocrinology, Diabetes and Metabolism
Biopsy, Fine-Needle
Carcinoma, Papillary, Follicular
Pathology and Forensic Medicine
Thyroid carcinoma
Young Adult
Endocrinology
Cytology
medicine
Humans
Thyroid Neoplasms
Thyroid Nodule
Thyroid cancer
Aged
Aged, 80 and over
business.industry
Reverse Transcriptase Polymerase Chain Reaction
Thyroid
Carcinoma
Nodule (medicine)
General Medicine
Middle Aged
medicine.disease
Carcinoma, Papillary
Gene Expression Regulation, Neoplastic
medicine.anatomical_structure
Thyroid Cancer, Papillary
Cancer cell
Female
medicine.symptom
business
PAX8
Subjects
Details
- ISSN :
- 15590097
- Volume :
- 22
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Endocrine pathology
- Accession number :
- edsair.doi.dedup.....282ead106f3a4e4bb5869f3ca5a4b7cb