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Gene expression profiling of normal thyroid tissue from patients with thyroid carcinoma.

ABSTRACT: Gene expression profiling (GEP) of normal thyroid tissue from 43 patients with thyroid carcinoma, 6 with thyroid adenoma, 42 with multinodular goiter, and 6 with Graves-Basedow disease was carried out with the aim of achieving a better understanding of the genetic mechanisms underlying the role of normal cells surrounding the tumor in the thyroid cancer progression. Unsupervised and supervised analyses were performed to compare samples from neoplastic and non-neoplastic diseases. GEP and subsequent RT-PCR analysis identified 28 differentially expressed genes. Functional assessment revealed that they are involved in tumorigenesis and cancer progression. The distinct GEP is likely to reflect the onset and/or progression of thyroid cancer, its molecular classification, and the identification of new potential prognostic factors, thus allowing to pinpoint selective gene targets with the aim of realizing more precise preoperative diagnostic procedures and novel therapeutic approaches.This study is focused on the gene expression profiling analysis followed by RT-PCR of normal thyroid tissues from patients with neoplastic and non-neoplastic thyroid diseases. Twenty-eight genes were found to be differentially expressed in normal cells surrounding the tumor in the thyroid cancer. The genes dysregulated in normal tissue samples from patients with thyroid tumors may represent new molecular markers, useful for their diagnostic, prognostic and possibly therapeutic implications.

SUBMITTER: Ria R

PROVIDER: S-EPMC5045425 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Gene expression profiling of normal thyroid tissue from patients with thyroid carcinoma.

Ria Roberto R Simeon Vittorio V Melaccio Assunta A Di Meo Giovanna G Trino Stefania S Mazzoccoli Carmela C Saltarella Ilaria I Lamanuzzi Aurelia A Morano Annalisa A Gurrado Angela A Pasculli Alessandro A Lastilla Gaetano G Musto Pellegrino P Reale Antonia A Dammacco Franco F Vacca Angelo A Testini Mario M

Oncotarget 20160501 20

Gene expression profiling (GEP) of normal thyroid tissue from 43 patients with thyroid carcinoma, 6 with thyroid adenoma, 42 with multinodular goiter, and 6 with Graves-Basedow disease was carried out with the aim of achieving a better understanding of the genetic mechanisms underlying the role of normal cells surrounding the tumor in the thyroid cancer progression. Unsupervised and supervised analyses were performed to compare samples from neoplastic and non-neoplastic diseases. GEP and subsequ ...[more]

PMID: 27105534

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Project description:To identify differences in gene expression profiles of infected cells between thyroid carcinoma (C), thyroid adenoma (A) and normal thyroid (N) epithelial cells, differentially expressed genes were identified using three pairwise comparisons with the GEO2R online tool. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were used to classify them at the functional level. The most significant cluster in the N vs. A pairwise comparison had four hub genes: Insulin-like growth factor 2, Von Willebrand factor (VWF), multimerin 1 (MMRN1) and complement factor D (CFD). In N vs. C, the most significant cluster had 19 genes: IGF2, early growth response 2, transcription factor 3, KIT proto‑oncogene receptor tyrosine kinase, SMAD family member 9, MLLT3 super elongation complex subunit, runt related transcription factor 1, CFD, actinin α 1, SWI/SNF related matrix associated actin dependent regulator of chromatin subfamily a member 4, JunD proto‑oncogene AP‑1 transcription factor subunit, serum response factor (SRF), FosB proto‑oncogene, AP‑1 transcription factor subunit, connective tissue growth factor (CTGF), SRC proto‑oncogene, non‑receptor tyrosine kinase, MMRN1, SRY‑box 9, early growth response 3 and ETS variant 4. In A vs. C, the most significant cluster had 14 genes: BCL2-like 1, galectin 3, MCL1 BCL2 family apoptosis regulator, DNA damage inducible transcript 3, BCL2 apoptosis regulator, CTGF, matrix metallopeptidase 7, early growth response 1, kinase insert domain receptor, TIMP metallopeptidase inhibitor 1, apolipoprotein E, VWF, cyclin D1 and placental growth factor. Histological evidence was presented to confirm the makeup of the hubs prior to logistic regression analysis to differentiate benign and malignant neoplasms. The results of the present study may aid in the search for novel potential biomarkers for the differential diagnosis, prognosis and development of drug targets of thyroid neoplasm.

Project description:In order to better understand basic mechanisms of tumor development and identify potential new biomarkers, we have performed difference gel electrophoresis (DIGE) and peptide mass fingerprinting on pooled protein extracts from patients with papillary thyroid carcinoma (PTC) compared with matched normal thyroid tissue. Image analysis of DIGE gels comparing PTC and matched normal thyroid tissue protein indicated that 25% of the protein spots were differentially expressed at a 2.5-fold cutoff and 35% at two-fold. Comparison between two different pools of protein from normal thyroid tissues revealed differential protein expression of only 4% at 2.5-fold and 6% at two-fold cutoff. One hundred ninety-two protein spots were identified by MALDI-TOFMS, representing 90 distinct proteins. Excluding albumin, globins and thyroglobulin, imaging software determined 31 proteins to be differentially expressed at the two-fold (or greater) level. Individual gel comparisons (PTC vs. matched normal) from five patients established that 15/31 (48%) of these proteins exhibited statistically significant differential expression. Previously identified molecular markers in this group of proteins include cathepsin B, cytokeratin 19, and galectin-3. Novel differentially expressed proteins include S100A6, moesin, HSP70 (BiP), peroxiredoxin 2, protein phosphatase 2, selenium binding protein 1, vitamin D binding protein, and proteins involved in mitochondrial function. The use of two-dimensional gel electrophoresis (2DGE) revealed a significantly altered protein mass and/or pI in 10%-15% of proteins, suggesting alternatively spliced forms and other posttranslational modification of proteins revealed by this approach. We confirmed S100A6 as a potentially useful biomarker using immunohistochemical analysis (85% sensitivity and 69% specificity for distinguishing benign from malignant thyroid neoplasms). In summary, proteomic analysis of PTC using DIGE and mass spectrometry has confirmed several known biomarkers, uncovered novel potential biomarkers, and provided insights into global pathophysiologic changes in PTC. Many of the differences observed would not have been detected by genomic or other proteomic approaches.

Dataset Information

Gene expression profiling of normal thyroid tissue from patients with thyroid carcinoma.

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Gene expression profiling of normal thyroid tissue from patients with thyroid carcinoma.

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