Aldred MA, Huang Y, Liyanarachchi S, Pellegata NS, Gimm O, Jhiang S et al.. Papillary and follicular thyroid carcinomas show distinctly different microarray expression profiles and can be distinguished by a minimum of five genes. J Clin Oncol 22: 3531-3539
ABSTRACT We have previously conducted independent microarray expression analyses of the two most common types of nonmedullary thyroid carcinoma, namely papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC). In this study, we sought to combine our data sets to shed light on the similarities and differences between these tumor types.
Microarray data from six PTCs, nine FTCs, and 13 normal thyroid samples were normalized to remove interlaboratory variability and then analyzed by unsupervised clustering, t test, and by comparison of absolute and change calls. Expression changes in four genes not previously implicated in thyroid carcinogenesis were verified by reverse transcriptase polymerase chain reaction on these same samples, together with eight additional FTC tumors.
PTCs showed two distinct groups of genes that were either over- or underexpressed compared with normal thyroid, whereas the predominant changes in FTCs were of decreased expression. Five genes could collectively distinguish the two tumor types. PTCs showed overexpression of CITED1, claudin-10 (CLDN10), and insulin-like growth factor binding protein 6 (IGFBP6) but showed no change in expression of caveolin-1 (CAV1) or -2 (CAV2); conversely, FTCs did not express CLDN10 and had decreased expression of IGFBP6 and/or CAV1 and CAV2.
PTC and FTC show distinctive microarray expression profiles, suggesting that either they have different molecular origins or they diverge distinctly from a common origin. Furthermore, if verified in a larger series of tumors, these genes could, in combination with known tumor-specific chromosome translocations, form the basis of a valuable diagnostic tool.
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- "1 ) . Similarly , microarrays have helped explain the develop - ment of benign pheochoromocytomas , medullary thyroid cancers , and skeletal abnormalities in multiple endocrine neoplasia syndromes ( Jain et al . , 2004 ) and have identi - fied gene expression differences in papillary and follicular thyroid cancers that may be useful in diagnosis ( Aldred et al . , 2004 ) ."
ABSTRACT: Purpose: The article aims to introduce nurses to how genetics-genomics is currently integrated into cancer care from prevention to treatment and influencing oncology nursing practice. Organizing Construct: An overview of genetics-genomics is described as it relates to cancer etiology, hereditary cancer syndromes, epigenetics factors, and management of care considerations. Methods: Peer-reviewed literature and expert professional guidelines were reviewed to address concepts of genetics-genomics in cancer care. Findings: Cancer is now known to be heterogeneous at the molecular level, with genetic and genomic factors underlying the etiology of all cancers. Understanding how these factors contribute to the development and treatment of both sporadic and hereditary cancers is important in cancer risk assessment, prevention, diagnosis, treatment, and long-term management and surveillance. Conclusions: Rapidly developing advances in genetics-genomics are changing all aspects of cancer care, with implications for nursing practice. Clinical Relevance: Nurses can educate cancer patients and their families about genetic-genomic advances and advocate for use of evidence-based genetic-genomic practice guidelines to reduce cancer risk and improve outcomes in cancer management.Journal of Nursing Scholarship 01/2013; 45(1). DOI:10.1111/j.1547-5069.2012.01465.x · 1.77 Impact Factor
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- "FTA–FTC–CPTC–FVPTC–normal thyroid data set. Seven normal thyroid samples (N) and nine follicular thyroid carcinomas (FTCs) were profiled by microarray as referenced in Aldred et al. (2004). We downloaded them from the authors' web site. "
ABSTRACT: Differentiation is central to development, while dedifferentiation is central to cancer progression. Hence, a quantitative assessment of differentiation would be most useful. We propose an unbiased method to derive organ-specific differentiation indices from gene expression data and demonstrate its usefulness in thyroid cancer diagnosis. We derived a list of thyroid-specific genes by selecting automatically those genes that are expressed at higher level in the thyroid than in any other organ in a normal tissue's genome-wide gene expression compendium. The thyroid index of a tissue was defined as the median expression of these thyroid-specific genes in that tissue. As expected, the thyroid index was inversely correlated with meta-PCNA, a proliferation metagene, across a wide range of thyroid tumors. By contrast, the two indices were positively correlated in a time course of thyroid-stimulating hormone (TSH) activation of primary thyrocytes. Thus, the thyroid index captures biological information not integrated by proliferation rates. The differential diagnostic of follicular thyroid adenomas and follicular thyroid carcinoma is a notorious challenge for pathologists. The thyroid index discriminated them as accurately as did machine-learning classifiers trained on the genome-wide cancer data. Hence, although it was established exclusively from normal tissue data, the thyroid index integrates the relevant diagnostic information contained in tumoral transcriptomes. Similar results were obtained for the classification of the follicular vs classical variants of papillary thyroid cancers, that is, tumors dedifferentiating along a different route. The automated procedures demonstrated in the thyroid are applicable to other organs.Oncogene 01/2012; 31(41):4490-8. DOI:10.1038/onc.2011.626 · 8.56 Impact Factor
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- "Online version via http://www.endocrinology-journals.org (CITED1) protein expression (Aldred et al. 2004, Prasad et al. 2004). Microarray analysis has also been utilized to identify the possible genomic mutations related to the thyroid carcinoma (Yano et al. 2004, Finley et al. 2005). "
ABSTRACT: Papillary thyroid carcinoma (PTC) frequently presents as a multifocal process. To study the importance of separating independent primary (IP) from intrathyroid metastatic (ITM) PTC, we examined 19 molecular markers on 42 separate tumors from 18 multifocal PTC cases. In 12 of 18 (66.7%) cases, including 6 of 12 (50%) papillary microcarcinoma cases, the same or similar profile of loss of heterozygosities (LOH) and v-raf murine sarcoma viral oncogene homolog B1 (BRAF) mutation was demonstrated, indicating that they were from the same primary and represented ITM. Different profiles of LOHs and BRAF mutation were detected in separate tumors of 6 of 18 cases, indicating that they represented IP. Patients with ITM, including papillary microcarcinoma, had significantly increased lymph node metastasis. The frequencies of LOHs of 17q21, 17p13, 10q23, and 22q13 were higher in tumors with lymph node metastasis, suggesting that these LOHs may be important in increased lymph node metastasis. LOH of 9p21 was found at the highest frequency in PTC (53.8%), followed by 1p36 (46.2%), 10q23 (34.6%), and 22q13 (34.6%). Papillary microcarcinoma had acquired similar genomic mutations as conventional PTC, but higher frequencies of mutations of BRAF, 1p36, 18q, and 22q13 were found in the larger PTC, suggesting that they might play a role in the aggressiveness of PTC. Different profiles of mutations were observed in conventional, follicular variants, and diffuse sclerosing variant of PTC, which might influence the different morphological appearances and clinical courses. In conclusion, molecular analysis can separate multifocal IP PTC from ITM PTC, and may be more important than tumor size in predicting lymph node metastasis, aggressiveness, and prognosis of PTC.Journal of Molecular Endocrinology 10/2008; 41(4):195-203. DOI:10.1677/JME-08-0063 · 3.62 Impact Factor