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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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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. |
format | Online Article Text |
id | pubmed-8255455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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