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

Area of Science:

• Molecular Biology
• Genomics
• Endocrinology

Background:

• MicroRNA (miRNA) profiling is crucial for understanding diseases like non-functioning pituitary adenomas (NFPA).
• High-throughput technologies such as microarray, RT-qPCR based arrays, and next-generation sequencing (NGS) are available for comprehensive miRNA analysis (miRNome).

Purpose of the Study:

• To evaluate the analytical and biological performance of different high-throughput miRNA profiling methods.
• To identify biologically relevant miRNAs in NFPA and assess platform-specific variations.

Main Methods:

• miRNome profiling of normal pituitary (NP) and NFPA samples using microarray, TaqMan-array, and NGS.
• Bioinformatic analysis of detected miRNAs and differential expression analysis.
• Technical validation using individual RT-qPCR and biological validation on an extended sample set.

Main Results:

• 25 differentially expressed miRNAs (fold change > 2) were identified between NP and NFPA samples.
• Microarray and TaqMan-array showed stronger correlation compared to NGS, which exhibited more discordant data.
• Technical validation confirmed varying degrees of miRNA detection accuracy across platforms, with 76.2% and 71.4% validation for TLDA and microarray, respectively.
• Biological validation demonstrated high correlation (p < 0.001; R = 0.96) between technical and biological findings.
• Pathway analysis implicated developmental pathways in NFPA genesis based on platform-independent miRNAs.

Conclusions:

• Significant differences exist among high-throughput miRNA profiling platforms, impacting experimental outcomes.
• Platform selection is critical, and cross-validation using an independent method is essential to minimize platform-specific errors in NFPA research.
• Developmental pathways are key functional categories in NFPA pathogenesis.