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Small RNA Sequencing Identifies a Six-MicroRNA Signature Enabling Classification of Brain Metastases According to their Origin
I. Roskova, M. Vecera, L. Radova, K. Trachtova, F. Siegl, M. Hermanova, M. Hendrych, L. Kren, V. Vybihal, H. Valekova, P. Kasparova, I. Kolouskova, T. Kazda, O. Slaby, R. Jancalek, J. Sana, M. Smrcka
Jazyk angličtina Země Řecko
Typ dokumentu časopisecké články
Odkazy
PubMed
36581345
DOI
10.21873/cgp.20361
Knihovny.cz E-zdroje
- MeSH
- biologické markery MeSH
- dospělí MeSH
- lidé MeSH
- melanom * MeSH
- mikro RNA * genetika metabolismus MeSH
- nádory mozku * genetika MeSH
- nádory neznámé primární lokalizace * MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND/AIM: Brain metastases (BMs) are the most frequent intracranial tumors in adults and one of the greatest challenges for modern oncology. Most are derived from lung, breast, renal cell, and colorectal carcinomas and melanomas. Up to 14% of patients are diagnosed with BMs of unknown primary, which are commonly characterized by an early and aggressive metastatic spread. It is important to discover novel biomarkers for early identification of BM origin, allowing better management of patients with this disease. Our study focused on microRNAs (miRNAs), which are very stable in frozen native and FFPE tissues and have been shown to be sensitive and specific diagnostic biomarkers of cancer. We aimed to identify miRNAs with significantly different expression in the five most frequent groups of BMs and develop a diagnostic classifier capable of sensitive and specific classification of BMs. MATERIALS AND METHODS: Total RNA enriched for miRNAs was isolated using the mirVana miRNA Isolation Kit from 71 fresh-frozen histopathologically confirmed BM tissues originating in 5 cancer types. Sequencing libraries were prepared using the QIAseq miRNA Library Kit and sequenced on the NextSeq 500 platform. MiRNA expression was further validated by RT-qPCR. RESULTS: Differential analysis identified 373 miRNAs with significantly different expression between 5 BM groups (p<0.001). A classifier model was developed based on the expression of 6 miRNAs (hsa-miR-141-3p, hsa-miR-141-5p, hsa-miR-146a-5p, hsa-miR-194-5p, hsa-miR-200b-3p and hsa-miR-365b-5p) with the ability to correctly classify 91.5% of samples. Subsequent validation confirmed both significantly different expression of selected miRNAs in 5 BM groups as well as their diagnostic potential. CONCLUSION: To date, our study is the first to analyze miRNA expression in various types of BMs using small RNA sequencing to develop a diagnostic classifier and, thus, to help stratify BMs of unknown primary. The presented results confirm the importance of studying the dysregulated expression of miRNAs in BMs and the diagnostic potential of the validated 6-miRNA signature.
1st Department of Pathology St Anne's University Hospital Brno Czech Republic
Central European Institute of Technology Masaryk University Brno Czech Republic
Department of Biology Faculty of Medicine Masaryk University Brno Czech Republic
Department of Comprehensive Cancer Care Masaryk Memorial Cancer Institute Brno Czech Republic
Department of Neurosurgery St Anne's University Hospital Brno Czech Republic
Department of Neurosurgery University Hospital Brno Brno Czech Republic
Department of Pathology University Hospital Brno Brno Czech Republic
Department of Radiation Oncology Masaryk Memorial Cancer Institute Brno Czech Republic
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