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Dataset of differential gene expression between total normal human thyroid and histologically normal thyroid adjacent to papillary thyroid carcinoma.

ABSTRACT: This article contains further data and information from our published manuscript [1]. We aim to identify significant transcriptome alterations of total normal human thyroid vs. histologically normal thyroid adjacent to papillary thyroid carcinoma. We performed a systematic meta-analysis of all the available gene expression profiles for the whole organ also collecting gene expression data for the normal thyroid adjacent to papillary thyroid carcinoma. A differential quantitative transcriptome reference map was generated by using TRAM (Transcriptome Mapper) software able to combine, normalize and integrate a total of 35 datasets from total normal thyroid and 40 datasets from histologically normal thyroid adjacent to papillary thyroid carcinoma from different sources. This analysis identified genes and genome segments that significantly discriminated the two groups of samples. Differentially expressed genes were grouped and enrichment function analyses were performed identifying the main features of the differentially expressed genes between total normal thyroid and histologically normal thyroid adjacent to papillary thyroid carcinoma. The search for housekeeping genes retrieved 414 loci.

SUBMITTER: Vitale L

PROVIDER: S-EPMC6479735 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Dataset of differential gene expression between total normal human thyroid and histologically normal thyroid adjacent to papillary thyroid carcinoma.

Vitale Lorenza L Piovesan Allison A Antonaros Francesca F Strippoli Pierluigi P Pelleri Maria Chiara MC Caracausi Maria M

Data in brief 20190315

This article contains further data and information from our published manuscript [1]. We aim to identify significant transcriptome alterations of total normal human thyroid vs. histologically normal thyroid adjacent to papillary thyroid carcinoma. We performed a systematic meta-analysis of all the available gene expression profiles for the whole organ also collecting gene expression data for the normal thyroid adjacent to papillary thyroid carcinoma. A differential quantitative transcriptome ref ...[more]

PMID: 31049370

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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

Dataset of differential gene expression between total normal human thyroid and histologically normal thyroid adjacent to papillary thyroid carcinoma.

Publications

Dataset of differential gene expression between total normal human thyroid and histologically normal thyroid adjacent to papillary thyroid carcinoma.

Similar Datasets

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