Clinicopathological subgroups of glioblastoma patients are characterized by specific lncRNA expression patterns

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F27661989%3A_____%2F18%3AN0000012" target="_blank" >RIV/27661989:_____/18:N0000012 - isvavai.cz</a>

Výsledek na webu

<a href="https://aacrjournals.org/cancerres/article/78/13_Supplement/2459/626972/Abstract-2459-Clinicopathological-subgroups-of" target="_blank" >https://aacrjournals.org/cancerres/article/78/13_Supplement/2459/626972/Abstract-2459-Clinicopathological-subgroups-of</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1158/1538-7445.AM2018-2459" target="_blank" >10.1158/1538-7445.AM2018-2459</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Clinicopathological subgroups of glioblastoma patients are characterized by specific lncRNA expression patterns

Popis výsledku v původním jazyce

Introduction: Glioblastoma (GBM) is the most frequent primary brain tumor of astrocytic origin. The prognosis is unfavourable with the median overall survival (OS) being between 12 and 15 months from diagnosis. Identification of new therapeutic targets, as well as new prognostic and predictive biomarkers for more accurate stratification of patients presents significant unmet medical needs. Long non-coding RNAs (lncRNAs) are regulators of gene expression playing important roles in the molecular pathology of GBM, indicating their potential as biomarkers and therapeutics targets. Material and Methods: Our study included 80 GBM patients treated with Stupp protocol and 16 patients with non-dominant anterior temporal cortexes resected during surgery for intractable epilepsy. Informed consent approved by the local Ethical Commission was obtained from each patient. IDH1 mutations and MGMT methylation status were evaluated in all GBMs. RNA (RIN > 8) from 96 specimens was used for next-generation RNA sequencing (RNAseq). rRNA depletion and cDNA library preparation were performed with RiboCop rRNA Depletion Kit V1.2 (Lexogen) and NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (NEB), respectively. RNAseq was done using NextSeq 500 High Output Kit and NextSeq 500 instrument (both Illumina). 24,087 protein-coding and 8,414 non-coding RNAs and their sequential variants with non-zero RPKM at least in one sample underwent statistical evaluation. CLC genomic workbench was used for the alignment and target counts. Results: Statistical analysis revealed 84 (P < 0.001) dysregulated lncRNAs in GBMs compared to non-tumor brain tissue samples. The results also showed 485 dysregulated protein-coding RNAs with P < 0.001 and 24 protein-coding RNAs with P < 0.000001. 35 lncRNAs showed significant dysregulation when lncRNA profiles of GBM tissues with methylated MGMT promoter (≥ 25% methylation) were compared to those with unmethylated promoter (P < 0.01). When lncRNA patterns of GBM samples with mutated IDH1 were compared to those with wild-type IDH1, 60 lncRNAs were found to be significantly dysregulated (P < 0.001). Correlating lncRNA expression patterns with OS uncovered 6 lncRNA signature which enabled identifying patients with significantly worse prognosis (OS < 6 months). Conclusion: We described significant dysregulation of lncRNAs and protein-coding RNAs in GBM tissue compared to non-tumor brain tissue and specific lncRNA patterns linked to MGMT methylation and IDH1 mutation status. We also identified 6 lncRNA signature allowing sensitive prognostic stratification of GBM patients. Our study indicates that lncRNAs could serve as promising diagnostic and prognostic biomarkers in GBM. This work was supported by Ministry of Health of the Czech Republic, grant nr. 15-33158A, 15-34553A, 15-31627A, 15-34678A, 16-31314A, 16-31765A and by grant of Czech Grant Agency nr. 16-18257S. Citation Format: Marek Vecera, Romana Butova, Radim Lipina, Stefan Reguli, Martin Smrcka, Radim Jancalek, Michal Filip, Marketa Hermanova, Leos Kren, Pavol Mojak, Jaroslav Juracek, Tana Machackova, Natalia A. Gablo, Jiri Sana, Ondrej Slaby. Clinicopathological subgroups of glioblastoma patients are characterized by specific lncRNA expression patterns [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2459.

Název v anglickém jazyce

Clinicopathological subgroups of glioblastoma patients are characterized by specific lncRNA expression patterns

Popis výsledku anglicky

Introduction: Glioblastoma (GBM) is the most frequent primary brain tumor of astrocytic origin. The prognosis is unfavourable with the median overall survival (OS) being between 12 and 15 months from diagnosis. Identification of new therapeutic targets, as well as new prognostic and predictive biomarkers for more accurate stratification of patients presents significant unmet medical needs. Long non-coding RNAs (lncRNAs) are regulators of gene expression playing important roles in the molecular pathology of GBM, indicating their potential as biomarkers and therapeutics targets. Material and Methods: Our study included 80 GBM patients treated with Stupp protocol and 16 patients with non-dominant anterior temporal cortexes resected during surgery for intractable epilepsy. Informed consent approved by the local Ethical Commission was obtained from each patient. IDH1 mutations and MGMT methylation status were evaluated in all GBMs. RNA (RIN > 8) from 96 specimens was used for next-generation RNA sequencing (RNAseq). rRNA depletion and cDNA library preparation were performed with RiboCop rRNA Depletion Kit V1.2 (Lexogen) and NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (NEB), respectively. RNAseq was done using NextSeq 500 High Output Kit and NextSeq 500 instrument (both Illumina). 24,087 protein-coding and 8,414 non-coding RNAs and their sequential variants with non-zero RPKM at least in one sample underwent statistical evaluation. CLC genomic workbench was used for the alignment and target counts. Results: Statistical analysis revealed 84 (P < 0.001) dysregulated lncRNAs in GBMs compared to non-tumor brain tissue samples. The results also showed 485 dysregulated protein-coding RNAs with P < 0.001 and 24 protein-coding RNAs with P < 0.000001. 35 lncRNAs showed significant dysregulation when lncRNA profiles of GBM tissues with methylated MGMT promoter (≥ 25% methylation) were compared to those with unmethylated promoter (P < 0.01). When lncRNA patterns of GBM samples with mutated IDH1 were compared to those with wild-type IDH1, 60 lncRNAs were found to be significantly dysregulated (P < 0.001). Correlating lncRNA expression patterns with OS uncovered 6 lncRNA signature which enabled identifying patients with significantly worse prognosis (OS < 6 months). Conclusion: We described significant dysregulation of lncRNAs and protein-coding RNAs in GBM tissue compared to non-tumor brain tissue and specific lncRNA patterns linked to MGMT methylation and IDH1 mutation status. We also identified 6 lncRNA signature allowing sensitive prognostic stratification of GBM patients. Our study indicates that lncRNAs could serve as promising diagnostic and prognostic biomarkers in GBM. This work was supported by Ministry of Health of the Czech Republic, grant nr. 15-33158A, 15-34553A, 15-31627A, 15-34678A, 16-31314A, 16-31765A and by grant of Czech Grant Agency nr. 16-18257S. Citation Format: Marek Vecera, Romana Butova, Radim Lipina, Stefan Reguli, Martin Smrcka, Radim Jancalek, Michal Filip, Marketa Hermanova, Leos Kren, Pavol Mojak, Jaroslav Juracek, Tana Machackova, Natalia A. Gablo, Jiri Sana, Ondrej Slaby. Clinicopathological subgroups of glioblastoma patients are characterized by specific lncRNA expression patterns [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2459.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

—

OECD FORD obor

30200 - Clinical medicine

Projekt

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Cancer Research

ISSN

0008-5472

e-ISSN

1538-7445

Svazek periodika

78

Číslo periodika v rámci svazku

13 Supplement S

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

1

Strana od-do

Meeting Abstract 2459

Kód UT WoS článku

000468818905320

EID výsledku v databázi Scopus

—