Small RNA Sequencing Identifies a Six-MicroRNA Signature Enabling Classification of Brain Metastases According to their Origin

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F23%3A00077844" target="_blank" >RIV/00159816:_____/23:00077844 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14740/23:00131080 RIV/65269705:_____/23:00077844 RIV/00179906:_____/23:10458139 RIV/00209805:_____/23:00079122

Result on the web

<a href="https://cgp.iiarjournals.org/content/cgp/20/1/18.full.pdf" target="_blank" >https://cgp.iiarjournals.org/content/cgp/20/1/18.full.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.21873/cgp.20361" target="_blank" >10.21873/cgp.20361</a>

Result language

angličtina

Original language name

Small RNA Sequencing Identifies a Six-MicroRNA Signature Enabling Classification of Brain Metastases According to their Origin

Original language description

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&lt;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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30204 - Oncology

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Cancer Genomics &amp; Proteomics

ISSN

1109-6535

e-ISSN

1790-6245

Volume of the periodical

20

Issue of the periodical within the volume

1

Country of publishing house

GR - GREECE

Number of pages

12

Pages from-to

18-29

UT code for WoS article

000907315600003

EID of the result in the Scopus database

2-s2.0-85145114489