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Limitations of high throughput methods for miRNA expression profiles in non-functioning pituitary adenomas

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Pathology & Oncology Research

Abstract

Microarray, RT-qPCR based arrays and next-generation-sequencing (NGS) are available high-throughput methods for miRNA profiling (miRNome). Analytical and biological performance of these methods were tested in identification of biologically relevant miRNAs in non-functioning pituitary adenomas (NFPA). miRNome of 4 normal pituitary (NP) and 8 NFPA samples was determined by these platforms and expression of 21 individual miRNAs was measured on 30 (20 NFPA and 10 NP) independent samples. Complex bioinformatics was used. 132 and 137 miRNAs were detected by all three platforms in NP and NFPA, respectively, of which 25 were differentially expressed (fold change > 2). The strongest correlation was observed between microarray and TaqMan-array, while the data obtained by NGS were the most discordant despite of various bioinformatics settings. As a technical validation we measured the expression of 21 selected miRNAs by individual RT-qPCR and we were able to validate 35.1%, 76.2% and 71.4% of the miRNAs revealed by SOLiD, TLDA and microarray result, respectively. We performed biological validation using an extended number of samples (20 NFPAs and 8 NPs). Technical and biological validation showed high correlation (p < 0.001; R = 0.96). Pathway and network analysis revealed several common pathways but no pathway showed the same activation score. Using the 25 platform-independent miRNAs developmental pathways were the top functional categories relevant for NFPA genesis. The difference among high-throughput platforms is of great importance and selection of screening method can influence experimental results. Validation by another platform is essential in order to avoid or to minimalize the platform specific errors.

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Acknowledgements

This work has been funded by National Research, Development and Innovation Office – NKFIH PD116093 to Henriett Butz. Attila Patocs is a recipient of “Lendulet” grant from Hungarian Academy of Sciences.

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Authors and Affiliations

  1. Hereditary Endocrine Tumors Research Group, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary

    O. Darvasi, I. Liko & A. Patocs

  2. Molecular Medicine Research Group, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary

    P. M. Szabo, S. Spisak, K. Racz, P. Igaz & Henriett Butz

  3. 2nd Department of Medicine, Faculty of Medicine, Semmelweis University, Budapest, Hungary

    K. Nemeth, K. Szabo, K. Racz & P. Igaz

  4. National Institute of Neurosurgery, Budapest, Hungary

    S. Czirjak

  5. Semmelweis University, Department of Laboratory Medicine, 46 Szentkirályi Str, Budapest, H-1088, Hungary

    A. Patocs & Henriett Butz

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  1. O. Darvasi
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  2. P. M. Szabo
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Supplemental Table 1

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Supplemental Table 2

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Supplemental Table 3

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Supplementary Figure 1

Numbers of differentially expressed miRNAs in the same direction with a fold change cut-off 2 identified by different platforms (GIF 182 kb)

High Resolution Image (TIFF 2146 kb)

Supplementary Figure 2

a Pathway analysis of experimentally validated targets of differentially expressed miRNA lists obtained by different platforms b Comparison of most significant pathway activation z-scores of different platforms. Z-scores of pathways are presented where the scores showed the same direction at least two studies. Z-score infers the activation states of predicted pathway by investigating the activator or inhibitor function of the enriched genes in the particular pathway (GIF 43 kb)

High Resolution Image (TIFF 12135 kb)

Supplementary Figure 3

Pathway analysis of “platform independent” miRNAs (GIF 75 kb)

High Resolution Image (TIFF 14830 kb)

Supplementary Figure 4

Gene ontology analysis of “platform independent” miRNAs (GIF 183 kb)

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Darvasi, O., Szabo, P.M., Nemeth, K. et al. Limitations of high throughput methods for miRNA expression profiles in non-functioning pituitary adenomas. Pathol. Oncol. Res. 25, 169–182 (2019). https://doi.org/10.1007/s12253-017-0330-3

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  • DOI: https://doi.org/10.1007/s12253-017-0330-3

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