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LGG-02. DRUG-CLASS SPECIFIC GENE-BASED MAPK SENSITIVITY SCORES (MSS) PREDICT SENSITIVITY TO MAPK INHIBITORS AND IDENTIFY IMMUNE INFILTRATION AS PUTATIVE TARGET IN PEDIATRIC LOW-GRADE GLIOMAS

INTRODUCTION: Pediatric low-grade gliomas (pLGG), the most common brain tumors in children, are driven by alterations in the MAPK pathway. Several clinical trials have shown the potential for MAPK inhibitors (MAPKi) treatment in pLGG. However, the range of response is broad, even within entities sha...

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Autores principales: Sigaud, Romain, Albert, Thomas K, Heß, Caroline, Hielscher, Thomas, Winkler, Nadine, Walter, Carolin, Münter, Daniel, Selt, Florian, Usta, Diren, Ecker, Jonas, Brentrup, Angela, Hasselblatt, Martin, Thomas, Christian, Varghese, Julian, Capper, David, Thomale, Ulrich W, Driever, Pablo Hernáiz, Simon, Michèle, Horn, Svea, Herz, Nina Annika, Koch, Arend, Sahm, Felix, Hamelmann, Stefan, Andrade, Augusto Faria, Jabado, Nada, Schouten-van Meeteren, Antoinette Y N, Hoving, Eelco, Brummer, Tilman, van Tilburg, Cornelis M, Pfister, Stefan M, Witt, Olaf, Jones, David T W, Kerl, Kornelius, Milde, Till
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10260027/
http://dx.doi.org/10.1093/neuonc/noad073.212
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author Sigaud, Romain
Albert, Thomas K
Heß, Caroline
Hielscher, Thomas
Winkler, Nadine
Walter, Carolin
Münter, Daniel
Selt, Florian
Usta, Diren
Ecker, Jonas
Brentrup, Angela
Hasselblatt, Martin
Thomas, Christian
Varghese, Julian
Capper, David
Thomale, Ulrich W
Driever, Pablo Hernáiz
Simon, Michèle
Horn, Svea
Herz, Nina Annika
Koch, Arend
Sahm, Felix
Hamelmann, Stefan
Andrade, Augusto Faria
Jabado, Nada
Schouten-van Meeteren, Antoinette Y N
Hoving, Eelco
Brummer, Tilman
van Tilburg, Cornelis M
Pfister, Stefan M
Witt, Olaf
Jones, David T W
Kerl, Kornelius
Milde, Till
author_facet Sigaud, Romain
Albert, Thomas K
Heß, Caroline
Hielscher, Thomas
Winkler, Nadine
Walter, Carolin
Münter, Daniel
Selt, Florian
Usta, Diren
Ecker, Jonas
Brentrup, Angela
Hasselblatt, Martin
Thomas, Christian
Varghese, Julian
Capper, David
Thomale, Ulrich W
Driever, Pablo Hernáiz
Simon, Michèle
Horn, Svea
Herz, Nina Annika
Koch, Arend
Sahm, Felix
Hamelmann, Stefan
Andrade, Augusto Faria
Jabado, Nada
Schouten-van Meeteren, Antoinette Y N
Hoving, Eelco
Brummer, Tilman
van Tilburg, Cornelis M
Pfister, Stefan M
Witt, Olaf
Jones, David T W
Kerl, Kornelius
Milde, Till
author_sort Sigaud, Romain
collection PubMed
description INTRODUCTION: Pediatric low-grade gliomas (pLGG), the most common brain tumors in children, are driven by alterations in the MAPK pathway. Several clinical trials have shown the potential for MAPK inhibitors (MAPKi) treatment in pLGG. However, the range of response is broad, even within entities sharing the same driving genetic MAPK alteration. A predictive stratification tool is needed to identify patients that will be more likely to benefit from MAPKi therapy. METHODS: We generated gene-expression-based MAPKi sensitivity scores (MSS) for each MAPKi class (BRAFi, MEKi, ERKi), based on MAPK-related genes differentially regulated between MAPKi sensitive and non-sensitive cell lines from the Genomics of Drug Sensitivity in Cancer (GDSC) dataset. Single sample Gene Set Enrichment Analysis (ssGSEA) was used to measure and validate our MSSs in the GDSC dataset and an independent PDX dataset (XevaDB). The validated signatures were tested in a pLGG-specific background, using gene expression data from PA cell lines and primary pLGG samples. RESULTS: Our MSS could differentiate MAPKi sensitive cells in the GDSC dataset, and significantly correlated with MAPKi response in the XevaDB PDX dataset. The MSS were able to differentiate glioma entities with differing MAPK alterations from non-MAPK altered entities, and showed the highest scores in pLGG. The MSSs were heterogeneous within pLGG entities with a common MAPK alteration, as observed in MAPKi clinical studies. Intriguingly, a strong correlation between our MSS and the predicted immune cell infiltration rate, as determined by the Estimate score, was observed and confirmed in a pLGG scRNA sequencing dataset. CONCLUSION: These data demonstrate the relevance of gene-expression signatures to predict response to MAPKi treatment in pLGG, and will be further investigated in a prospective manner in upcoming clinical trials. In addition, our data could suggest a role of immune infiltration in the response to MAPKi in pLGG that warrants further validation.
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spelling pubmed-102600272023-06-13 LGG-02. DRUG-CLASS SPECIFIC GENE-BASED MAPK SENSITIVITY SCORES (MSS) PREDICT SENSITIVITY TO MAPK INHIBITORS AND IDENTIFY IMMUNE INFILTRATION AS PUTATIVE TARGET IN PEDIATRIC LOW-GRADE GLIOMAS Sigaud, Romain Albert, Thomas K Heß, Caroline Hielscher, Thomas Winkler, Nadine Walter, Carolin Münter, Daniel Selt, Florian Usta, Diren Ecker, Jonas Brentrup, Angela Hasselblatt, Martin Thomas, Christian Varghese, Julian Capper, David Thomale, Ulrich W Driever, Pablo Hernáiz Simon, Michèle Horn, Svea Herz, Nina Annika Koch, Arend Sahm, Felix Hamelmann, Stefan Andrade, Augusto Faria Jabado, Nada Schouten-van Meeteren, Antoinette Y N Hoving, Eelco Brummer, Tilman van Tilburg, Cornelis M Pfister, Stefan M Witt, Olaf Jones, David T W Kerl, Kornelius Milde, Till Neuro Oncol Final Category: Low Grade Gliomas - LGG INTRODUCTION: Pediatric low-grade gliomas (pLGG), the most common brain tumors in children, are driven by alterations in the MAPK pathway. Several clinical trials have shown the potential for MAPK inhibitors (MAPKi) treatment in pLGG. However, the range of response is broad, even within entities sharing the same driving genetic MAPK alteration. A predictive stratification tool is needed to identify patients that will be more likely to benefit from MAPKi therapy. METHODS: We generated gene-expression-based MAPKi sensitivity scores (MSS) for each MAPKi class (BRAFi, MEKi, ERKi), based on MAPK-related genes differentially regulated between MAPKi sensitive and non-sensitive cell lines from the Genomics of Drug Sensitivity in Cancer (GDSC) dataset. Single sample Gene Set Enrichment Analysis (ssGSEA) was used to measure and validate our MSSs in the GDSC dataset and an independent PDX dataset (XevaDB). The validated signatures were tested in a pLGG-specific background, using gene expression data from PA cell lines and primary pLGG samples. RESULTS: Our MSS could differentiate MAPKi sensitive cells in the GDSC dataset, and significantly correlated with MAPKi response in the XevaDB PDX dataset. The MSS were able to differentiate glioma entities with differing MAPK alterations from non-MAPK altered entities, and showed the highest scores in pLGG. The MSSs were heterogeneous within pLGG entities with a common MAPK alteration, as observed in MAPKi clinical studies. Intriguingly, a strong correlation between our MSS and the predicted immune cell infiltration rate, as determined by the Estimate score, was observed and confirmed in a pLGG scRNA sequencing dataset. CONCLUSION: These data demonstrate the relevance of gene-expression signatures to predict response to MAPKi treatment in pLGG, and will be further investigated in a prospective manner in upcoming clinical trials. In addition, our data could suggest a role of immune infiltration in the response to MAPKi in pLGG that warrants further validation. Oxford University Press 2023-06-12 /pmc/articles/PMC10260027/ http://dx.doi.org/10.1093/neuonc/noad073.212 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Final Category: Low Grade Gliomas - LGG
Sigaud, Romain
Albert, Thomas K
Heß, Caroline
Hielscher, Thomas
Winkler, Nadine
Walter, Carolin
Münter, Daniel
Selt, Florian
Usta, Diren
Ecker, Jonas
Brentrup, Angela
Hasselblatt, Martin
Thomas, Christian
Varghese, Julian
Capper, David
Thomale, Ulrich W
Driever, Pablo Hernáiz
Simon, Michèle
Horn, Svea
Herz, Nina Annika
Koch, Arend
Sahm, Felix
Hamelmann, Stefan
Andrade, Augusto Faria
Jabado, Nada
Schouten-van Meeteren, Antoinette Y N
Hoving, Eelco
Brummer, Tilman
van Tilburg, Cornelis M
Pfister, Stefan M
Witt, Olaf
Jones, David T W
Kerl, Kornelius
Milde, Till
LGG-02. DRUG-CLASS SPECIFIC GENE-BASED MAPK SENSITIVITY SCORES (MSS) PREDICT SENSITIVITY TO MAPK INHIBITORS AND IDENTIFY IMMUNE INFILTRATION AS PUTATIVE TARGET IN PEDIATRIC LOW-GRADE GLIOMAS
title LGG-02. DRUG-CLASS SPECIFIC GENE-BASED MAPK SENSITIVITY SCORES (MSS) PREDICT SENSITIVITY TO MAPK INHIBITORS AND IDENTIFY IMMUNE INFILTRATION AS PUTATIVE TARGET IN PEDIATRIC LOW-GRADE GLIOMAS
title_full LGG-02. DRUG-CLASS SPECIFIC GENE-BASED MAPK SENSITIVITY SCORES (MSS) PREDICT SENSITIVITY TO MAPK INHIBITORS AND IDENTIFY IMMUNE INFILTRATION AS PUTATIVE TARGET IN PEDIATRIC LOW-GRADE GLIOMAS
title_fullStr LGG-02. DRUG-CLASS SPECIFIC GENE-BASED MAPK SENSITIVITY SCORES (MSS) PREDICT SENSITIVITY TO MAPK INHIBITORS AND IDENTIFY IMMUNE INFILTRATION AS PUTATIVE TARGET IN PEDIATRIC LOW-GRADE GLIOMAS
title_full_unstemmed LGG-02. DRUG-CLASS SPECIFIC GENE-BASED MAPK SENSITIVITY SCORES (MSS) PREDICT SENSITIVITY TO MAPK INHIBITORS AND IDENTIFY IMMUNE INFILTRATION AS PUTATIVE TARGET IN PEDIATRIC LOW-GRADE GLIOMAS
title_short LGG-02. DRUG-CLASS SPECIFIC GENE-BASED MAPK SENSITIVITY SCORES (MSS) PREDICT SENSITIVITY TO MAPK INHIBITORS AND IDENTIFY IMMUNE INFILTRATION AS PUTATIVE TARGET IN PEDIATRIC LOW-GRADE GLIOMAS
title_sort lgg-02. drug-class specific gene-based mapk sensitivity scores (mss) predict sensitivity to mapk inhibitors and identify immune infiltration as putative target in pediatric low-grade gliomas
topic Final Category: Low Grade Gliomas - LGG
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10260027/
http://dx.doi.org/10.1093/neuonc/noad073.212
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