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OPTC-1. Proteomic analysis of genetically stratified low-grade meningioma

INTRODUCTION: Meningioma are the most common primary intracranial tumour. According to WHO, ~80% tumours are benign grade I. Although, some grade I tumour clinically show aggressive behaviour. Radio-surgery are the main therapeutic approaches, chemotherapies are ineffective. Accurate biomarkers for...

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Autores principales: Akther, Yeasmin, Adams, Claire, Sharma, Vikram, Barros, Claudia, Banton, Matthew, Hanemann, Oliver
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8255455/
http://dx.doi.org/10.1093/noajnl/vdab070.022
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author Akther, Yeasmin
Adams, Claire
Sharma, Vikram
Barros, Claudia
Banton, Matthew
Hanemann, Oliver
author_facet Akther, Yeasmin
Adams, Claire
Sharma, Vikram
Barros, Claudia
Banton, Matthew
Hanemann, Oliver
author_sort Akther, Yeasmin
collection PubMed
description INTRODUCTION: Meningioma are the most common primary intracranial tumour. According to WHO, ~80% tumours are benign grade I. Although, some grade I tumour clinically show aggressive behaviour. Radio-surgery are the main therapeutic approaches, chemotherapies are ineffective. Accurate biomarkers for clinical management are lacking. The mutational profile of low-grade meningioma is well-defined, with non-NF2 mutated tumours harbouring recurrent mutations in genes including TRAF7, KLF4, AKT1 and SMO. Here, we aim to identify novel biomarkers and therapeutic targets of genetically stratified low-grade meningioma by characterising the proteomic landscape. MATERIALS AND METHODS: Meningioma specimens were stratified according to mutational background: AKT1(E17K)/TRAF7, KLF4K409Q/TRAF7 and NF2(-/-). Proteins were separated by SDS-PAGE followed by in-gel tryptic digestion and sample preparation for LC-MS/MS analysis. Raw mass spectrometry data files were processed by MaxQuant and Perseus software. Quantitative phospho-proteomics was performed using TMT-10plex labelling approach followed by motif analysis using motif-X algorithm. GO enrichment analyses were performed using DAVID against all human proteins. RESULTS AND CONCLUSIONS: We have quantified 4162 proteins across all mutational meningioma subgroups and normal meninges (n=31). Hierarchical clustering analysis showed distinct proteomic profiles of mutational subgroups revealing clusters of differentially expressed proteins (DEPs). Comparative analysis showed 10 proteins were commonly significantly upregulated (log2 fold-change≥1; p<0.05) among all mutational subtypes vs. normal meninges, indicating proteomic landscapes of mutational subtypes to be highly variable. In contrast, 257 proteins were commonly significantly downregulated (log2 fold-change≤-1; p<0.05) and enriched with molecular functions including aldehyde dehydrogenase and oxido-reductase. Mutational subtype-specific analysis identified 162 proteins significantly upregulated in AKT1(E17K)/TRAF7 vs. remaining sample groups to be enriched in the oxidative phosphorylation pathway. Lastly, analyses of 6600 phospho-sites (n=8) predicted regulatory kinases including EGFR and PKCα. Several of these up-regulated proteins and kinases already verified via WB. Further validation and functional verification will allow us to identify potential drug targets/biomarkers for meningioma.
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spelling pubmed-82554552021-07-06 OPTC-1. Proteomic analysis of genetically stratified low-grade meningioma Akther, Yeasmin Adams, Claire Sharma, Vikram Barros, Claudia Banton, Matthew Hanemann, Oliver Neurooncol Adv Supplement Abstracts INTRODUCTION: Meningioma are the most common primary intracranial tumour. According to WHO, ~80% tumours are benign grade I. Although, some grade I tumour clinically show aggressive behaviour. Radio-surgery are the main therapeutic approaches, chemotherapies are ineffective. Accurate biomarkers for clinical management are lacking. The mutational profile of low-grade meningioma is well-defined, with non-NF2 mutated tumours harbouring recurrent mutations in genes including TRAF7, KLF4, AKT1 and SMO. Here, we aim to identify novel biomarkers and therapeutic targets of genetically stratified low-grade meningioma by characterising the proteomic landscape. MATERIALS AND METHODS: Meningioma specimens were stratified according to mutational background: AKT1(E17K)/TRAF7, KLF4K409Q/TRAF7 and NF2(-/-). Proteins were separated by SDS-PAGE followed by in-gel tryptic digestion and sample preparation for LC-MS/MS analysis. Raw mass spectrometry data files were processed by MaxQuant and Perseus software. Quantitative phospho-proteomics was performed using TMT-10plex labelling approach followed by motif analysis using motif-X algorithm. GO enrichment analyses were performed using DAVID against all human proteins. RESULTS AND CONCLUSIONS: We have quantified 4162 proteins across all mutational meningioma subgroups and normal meninges (n=31). Hierarchical clustering analysis showed distinct proteomic profiles of mutational subgroups revealing clusters of differentially expressed proteins (DEPs). Comparative analysis showed 10 proteins were commonly significantly upregulated (log2 fold-change≥1; p<0.05) among all mutational subtypes vs. normal meninges, indicating proteomic landscapes of mutational subtypes to be highly variable. In contrast, 257 proteins were commonly significantly downregulated (log2 fold-change≤-1; p<0.05) and enriched with molecular functions including aldehyde dehydrogenase and oxido-reductase. Mutational subtype-specific analysis identified 162 proteins significantly upregulated in AKT1(E17K)/TRAF7 vs. remaining sample groups to be enriched in the oxidative phosphorylation pathway. Lastly, analyses of 6600 phospho-sites (n=8) predicted regulatory kinases including EGFR and PKCα. Several of these up-regulated proteins and kinases already verified via WB. Further validation and functional verification will allow us to identify potential drug targets/biomarkers for meningioma. Oxford University Press 2021-07-05 /pmc/articles/PMC8255455/ http://dx.doi.org/10.1093/noajnl/vdab070.022 Text en © The Author(s) 2021. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Supplement Abstracts
Akther, Yeasmin
Adams, Claire
Sharma, Vikram
Barros, Claudia
Banton, Matthew
Hanemann, Oliver
OPTC-1. Proteomic analysis of genetically stratified low-grade meningioma
title OPTC-1. Proteomic analysis of genetically stratified low-grade meningioma
title_full OPTC-1. Proteomic analysis of genetically stratified low-grade meningioma
title_fullStr OPTC-1. Proteomic analysis of genetically stratified low-grade meningioma
title_full_unstemmed OPTC-1. Proteomic analysis of genetically stratified low-grade meningioma
title_short OPTC-1. Proteomic analysis of genetically stratified low-grade meningioma
title_sort optc-1. proteomic analysis of genetically stratified low-grade meningioma
topic Supplement Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8255455/
http://dx.doi.org/10.1093/noajnl/vdab070.022
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