Coexistent Anaplastic and Differentiated Thyroid Carcinoma.

ArticleinAmerican Journal of Clinical Pathology 125(3):399-406 · April 2006with4 Reads
DOI: 10.1309/LF3Q-1NQK-MT2N-9KNV · Source: PubMed
Abstract
The aim of the present study was to clarify the underlying molecules that might contribute to the highly aggressive behavior of anaplastic thyroid carcinoma. We selected 5 cases of anaplastic thyroid carcinoma that had a differentiated area to determine differences in the molecules of undifferentiated and differentiated cancer cells. We immunohistochemically examined the localization of nuclear antigen (Ki-67), proliferating cell nuclear antigen (PCNA), p53, apoptotic protease-activating factor-1 (Apaf-1), CD26, galectin-3, E-cadherin, and CD147. We found an increased Ki-67, PCNA, and p53 labeling indices; decreased levels of Apaf-1, CD26, galectin-3, and E-cadherin; and overexpression of CD147 in the undifferentiated area compared with the differentiated area. These findings indicate high proliferative properties, suppression of apoptosis, disruption of cell-cell interaction, and induction of matrix metalloproteinases in the undifferentiated areas. Thus the molecules examined might be useful for evaluating the aggressive nature of this tumor and the prognosis.
    • "This gene expression pattern has been found in clinical and pathological samples and indicates a stepwise progression of thyroid cancer from WDTC to UTC or ATC [24]. An area of PTC in ATCs has been shown to undergo dedifferentiation, and this process has been reported to be correlated with gaining an additional p53 mutation in BRAF-mutated PTCs [25, 26]. However, how the tumour cells dedifferentiate and how these genes mutate during thyroid cancer progression remains unknown. "
    [Show abstract] [Hide abstract] ABSTRACT: Purpose 131I therapy is regularly used following surgery as a part of thyroid cancer management. Despite an overall relatively good prognosis, recurrent or metastatic thyroid cancer is not rare. CD133-expressing cells have been shown to mark thyroid cancer stem cells that possess the characteristics of stem cells and have the ability to initiate tumours. However, no studies have addressed the influence of CD133-expressing cells on radioiodide therapy of the thyroid cancer. The aim of this study was to investigate whether CD133+ cells contribute to the radioresistance of thyroid cancer and thus potentiate future recurrence and metastasis. Methods Thyroid cancer cell lines were analysed for CD133 expression, radiosensitivity and gene expression. Results The anaplastic thyroid cancer cell line ARO showed a higher percentage of CD133+ cells and higher radioresistance. After γ-irradiation of the cells, the CD133+ population was enriched due to the higher apoptotic rate of CD133− cells. In vivo 131I treatment of ARO tumour resulted in an elevated expression of CD133, Oct4, Nanog, Lin28 and Glut1 genes. After isolation, CD133+ cells exhibited higher radioresistance and higher expression of Oct4, Nanog, Sox2, Lin28 and Glut1 in the cell line or primarily cultured papillary thyroid cancer cells, and lower expression of various thyroid-specific genes, namely NIS, Tg, TPO, TSHR, TTF1 and Pax8. Conclusion This study demonstrates the existence of CD133-expressing thyroid cancer cells which show a higher radioresistance and are in an undifferentiated status. These cells possess a greater potential to survive radiotherapy and may contribute to the recurrence of thyroid cancer. A future therapeutic approach for radioresistant thyroid cancer may focus on the selective eradication of CD133+ cells.
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  • [Show abstract] [Hide abstract] ABSTRACT: Selection of novel molecular markers is an important goal of cancer genomics studies. The aim of our analysis was to apply the multivariate bioinformatical tools to rank the genes - potential markers of papillary thyroid cancer (PTC) according to their diagnostic usefulness. We also assessed the accuracy of benign/malignant classification, based on gene expression profiling, for PTC. We analyzed a 180-array dataset (90 HG-U95A and 90 HG-U133A oligonucleotide arrays), which included a collection of 57 PTCs, 61 benign thyroid tumors, and 62 apparently normal tissues. Gene selection was carried out by the support vector machines method with bootstrapping, which allowed us 1) ranking the genes that were most important for classification quality and appeared most frequently in the classifiers (bootstrap-based feature ranking, BBFR); 2) ranking the samples, and thus detecting cases that were most difficult to classify (bootstrap-based outlier detection). The accuracy of PTC diagnosis was 98.5% for a 20-gene classifier, its 95% confidence interval (CI) was 95.9-100%, with the lower limit of CI exceeding 95% already for five genes. Only 5 of 180 samples (2.8%) were misclassified in more than 10% of bootstrap iterations. We specified 43 genes which are most suitable as molecular markers of PTC, among them some well-known PTC markers (MET, fibronectin 1, dipeptidylpeptidase 4, or adenosine A1 receptor) and potential new ones (UDP-galactose-4-epimerase, cadherin 16, gap junction protein 3, sushi, nidogen, and EGF-like domains 1, inhibitor of DNA binding 3, RUNX1, leiomodin 1, F-box protein 9, and tripartite motif-containing 58). The highest ranking gene, metallophosphoesterase domain-containing protein 2, achieved 96.7% of the maximum BBFR score.
    Full-text · Article · Oct 2007
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    Article · Jul 2008
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