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

Kód výsledku v 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>

Nalezeny alternativní kódy

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

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30204 - Oncology

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Cancer Genomics &amp; Proteomics

ISSN

1109-6535

e-ISSN

1790-6245

Svazek periodika

20

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GR - Řecká republika

Počet stran výsledku

12

Strana od-do

18-29

Kód UT WoS článku

000907315600003

EID výsledku v databázi Scopus

2-s2.0-85145114489