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Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients

Excessive deposition of extracellular matrix (ECM) is a hallmark of solid tumors; however, it remains poorly understood which cellular and molecular components contribute to the formation of ECM stroma in central nervous system (CNS) tumors. Here, we undertook a pan-CNS analysis of retrospective gen...

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Autores principales: Zarodniuk, Maksym, Steele, Alexander, Lu, Xin, Li, Jun, Datta, Meenal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246264/
https://www.ncbi.nlm.nih.gov/pubmed/37292803
http://dx.doi.org/10.21203/rs.3.rs-2931886/v1
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author Zarodniuk, Maksym
Steele, Alexander
Lu, Xin
Li, Jun
Datta, Meenal
author_facet Zarodniuk, Maksym
Steele, Alexander
Lu, Xin
Li, Jun
Datta, Meenal
author_sort Zarodniuk, Maksym
collection PubMed
description Excessive deposition of extracellular matrix (ECM) is a hallmark of solid tumors; however, it remains poorly understood which cellular and molecular components contribute to the formation of ECM stroma in central nervous system (CNS) tumors. Here, we undertook a pan-CNS analysis of retrospective gene expression datasets to characterize inter- and intra-tumoral heterogeneity of ECM remodeling signatures in both adult and pediatric CNS disease. We found that CNS lesions – glioblastoma in particular – can be divided into two ECM-based subtypes (ECM(hi) and ECM(lo)) that are influenced by the presence of perivascular cells resembling cancer-associated fibroblasts (CAFs). We show that perivascular fibroblasts activate chemoattractant signaling pathways to recruit tumor-associated macrophages, and promote an immune-evasive, stem-like cancer cell phenotype. Our analysis reveals that perivascular fibroblasts are correlated with unfavorable response to immune checkpoint blockade in glioblastoma and poor patient survival across a subset of CNS tumors. We provide insights into novel stroma-driven mechanisms underlying immune evasion and immunotherapy resistance in CNS tumors like glioblastoma, and discuss how targeting these perivascular fibroblasts may prove an effective approach to improving treatment response and patient survival in a variety of CNS tumors.
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spelling pubmed-102462642023-06-08 Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients Zarodniuk, Maksym Steele, Alexander Lu, Xin Li, Jun Datta, Meenal Res Sq Article Excessive deposition of extracellular matrix (ECM) is a hallmark of solid tumors; however, it remains poorly understood which cellular and molecular components contribute to the formation of ECM stroma in central nervous system (CNS) tumors. Here, we undertook a pan-CNS analysis of retrospective gene expression datasets to characterize inter- and intra-tumoral heterogeneity of ECM remodeling signatures in both adult and pediatric CNS disease. We found that CNS lesions – glioblastoma in particular – can be divided into two ECM-based subtypes (ECM(hi) and ECM(lo)) that are influenced by the presence of perivascular cells resembling cancer-associated fibroblasts (CAFs). We show that perivascular fibroblasts activate chemoattractant signaling pathways to recruit tumor-associated macrophages, and promote an immune-evasive, stem-like cancer cell phenotype. Our analysis reveals that perivascular fibroblasts are correlated with unfavorable response to immune checkpoint blockade in glioblastoma and poor patient survival across a subset of CNS tumors. We provide insights into novel stroma-driven mechanisms underlying immune evasion and immunotherapy resistance in CNS tumors like glioblastoma, and discuss how targeting these perivascular fibroblasts may prove an effective approach to improving treatment response and patient survival in a variety of CNS tumors. American Journal Experts 2023-05-15 /pmc/articles/PMC10246264/ /pubmed/37292803 http://dx.doi.org/10.21203/rs.3.rs-2931886/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. https://creativecommons.org/licenses/by/4.0/License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License (https://creativecommons.org/licenses/by/4.0/)
spellingShingle Article
Zarodniuk, Maksym
Steele, Alexander
Lu, Xin
Li, Jun
Datta, Meenal
Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients
title Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients
title_full Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients
title_fullStr Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients
title_full_unstemmed Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients
title_short Pan-cancer transcriptomic analysis of CNS tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients
title_sort pan-cancer transcriptomic analysis of cns tumor stroma identifies a population of perivascular fibroblasts that predict poor immunotherapy response in glioblastoma patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246264/
https://www.ncbi.nlm.nih.gov/pubmed/37292803
http://dx.doi.org/10.21203/rs.3.rs-2931886/v1
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