Proteomic profiling of follicular and papillary thyroid tumors

Anastasios Sofiadis, Susanne Becker, Ulf Hellman, Lina Hultin-Rosenberg, Andrii Dinets, Mykola Hulchiy, Jan Zedenius, Göran Wallin, Theodoros Foukakis, Anders Höög, Gert Auer, Janne Lehtiö, Catharina Larsson, Anastasios Sofiadis, Susanne Becker, Ulf Hellman, Lina Hultin-Rosenberg, Andrii Dinets, Mykola Hulchiy, Jan Zedenius, Göran Wallin, Theodoros Foukakis, Anders Höög, Gert Auer, Janne Lehtiö, Catharina Larsson

Abstract

Objective: Thyroid proteomics is a new direction in thyroid cancer research aiming at etiological understanding and biomarker identification for improved diagnosis.

Methods: Two-dimensional electrophoresis was applied to cytosolic protein extracts from frozen thyroid samples (ten follicular adenomas, nine follicular carcinomas, ten papillary carcinomas, and ten reference thyroids). Spots with differential expression were revealed by image and multivariate statistical analyses, and identified by mass spectrometry.

Results: A set of 25 protein spots significant for discriminating between the sample groups was identified. Proteins identified for nine of these spots were studied further including 14-3-3 protein beta/alpha, epsilon, and zeta/delta, peroxiredoxin 6, selenium-binding protein 1, protein disulfide-isomerase precursor, annexin A5 (ANXA5), tubulin alpha-1B chain, and α1-antitrypsin precursor. This subset of protein spots carried the same predictive power in differentiating between follicular carcinoma and adenoma or between follicular and papillary carcinoma, as compared with the larger set of 25 spots. Protein expression in the sample groups was demonstrated by western blot analyses. For ANXA5 and the 14-3-3 proteins, expression in tumor cell cytoplasm was demonstrated by immunohistochemistry both in the sample groups and an independent series of papillary thyroid carcinomas.

Conclusion: The proteins identified confirm previous findings in thyroid proteomics, and suggest additional proteins as dysregulated in thyroid tumors.

Figures

Figure 1
Figure 1
Graphical presentation of the performance of the PLS-DA models built for the comparison between FTA and FTC (A) and between FTC and PTC (B). The continuous lines correspond to spots selected after vip-score ranking, whereas dotted lines correspond to random spot selection. (lat.var., latent variable; vip, variable importance on projection; and rnd, random).
Figure 2
Figure 2
Image of a silver-stained 2-DE gel. The 25 spots selected from the FTA–FTC model are indicated by circles (total overlap with the 18 spots from the FTC–PTC model). The numbers shown correspond to the standard spot number automatically assigned to each spot by the image analysis software (PDQuest). Spot numbers followed by an asterisk refer to the nine spots selected for further validation.
Figure 3
Figure 3
Graphical representation of individual spot intensities for the 25 spots identified by PLS-DA across all separate gels included in the study. Below each graph is given either the full or the abbreviated name of the corresponding protein identified by MALDI-TOF-MS (see Table 1). FTA, follicular thyroid adenoma; FTC, follicular thyroid carcinoma; Ref thyr, reference thyroid; and PTC, papillary thyroid carcinoma.
Figure 4
Figure 4
Western blots illustrating expression of the nine selected proteins in samples from each study group (reference thyroid, FTA, FTC, and PTC). β-Actin was used as control of protein loading and quality in all analyses.
Figure 5
Figure 5
Immunohistochemical analysis of protein expression for 14-3-3 (isoforms: β/α, ϵ and ζ/δ) and ANXA5. (A) Photomicrographs in 40× magnification of paraffin sections where predominantly cytosolic staining is visualized for 14-3-3 and ANXA5 in the different sample groups. (B) Photomicrographs in 10× magnification for 14-3-3 and 16× magnification for ANXA5 analysis on paraffin sections of PTC with CLT visualizing non-stained lymphocytes together with positively stained tumor cells.

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