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Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences
Post-resection radiologic monitoring to identify areas of new or progressive enhancement concerning for cancer recurrence is critical during patients with glioblastoma follow-up. However, treatment-related pseudoprogression presents with similar imaging features but requires different clinical manag...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694987/ https://www.ncbi.nlm.nih.gov/pubmed/38049893 http://dx.doi.org/10.1186/s40478-023-01587-w |
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author | Wang, Wesley Tugaoen, Jonah Domingo Fadda, Paolo Toland, Amanda Ewart Ma, Qin Elder, J. Brad Giglio, Pierre Otero, José Javier |
author_facet | Wang, Wesley Tugaoen, Jonah Domingo Fadda, Paolo Toland, Amanda Ewart Ma, Qin Elder, J. Brad Giglio, Pierre Otero, José Javier |
author_sort | Wang, Wesley |
collection | PubMed |
description | Post-resection radiologic monitoring to identify areas of new or progressive enhancement concerning for cancer recurrence is critical during patients with glioblastoma follow-up. However, treatment-related pseudoprogression presents with similar imaging features but requires different clinical management. While pathologic diagnosis is the gold standard to differentiate true progression and pseudoprogression, the lack of objective clinical standards and admixed histologic presentation creates the needs to (1) validate the accuracy of current approaches and (2) characterize differences between these entities to objectively differentiate true disease. We demonstrated using an online RNAseq repository of recurrent glioblastoma samples that cancer-immune cell activity levels correlate with heterogenous clinical outcomes in patients. Furthermore, nCounter RNA expression analysis of 48 clinical samples taken from second neurosurgical resection supports that pseudoprogression gene expression pathways are dominated with immune activation, whereas progression is predominated with cell cycle activity. Automated image processing and spatial expression analysis however highlight a failure to apply these broad expressional differences in a subset of cases with clinically challenging admixed histology. Encouragingly, applying unsupervised clustering approaches over our segmented histologic images provides novel understanding of morphologically derived differences between progression and pseudoprogression. Spatially derived data further highlighted polarization of myeloid populations that may underscore the tumorgenicity of novel lesions. These findings not only help provide further clarity of potential targets for pathologists to better assist stratification of progression and pseudoprogression, but also highlight the evolution of tumor-immune microenvironment changes which promote tumor recurrence. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40478-023-01587-w. |
format | Online Article Text |
id | pubmed-10694987 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106949872023-12-05 Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences Wang, Wesley Tugaoen, Jonah Domingo Fadda, Paolo Toland, Amanda Ewart Ma, Qin Elder, J. Brad Giglio, Pierre Otero, José Javier Acta Neuropathol Commun Research Post-resection radiologic monitoring to identify areas of new or progressive enhancement concerning for cancer recurrence is critical during patients with glioblastoma follow-up. However, treatment-related pseudoprogression presents with similar imaging features but requires different clinical management. While pathologic diagnosis is the gold standard to differentiate true progression and pseudoprogression, the lack of objective clinical standards and admixed histologic presentation creates the needs to (1) validate the accuracy of current approaches and (2) characterize differences between these entities to objectively differentiate true disease. We demonstrated using an online RNAseq repository of recurrent glioblastoma samples that cancer-immune cell activity levels correlate with heterogenous clinical outcomes in patients. Furthermore, nCounter RNA expression analysis of 48 clinical samples taken from second neurosurgical resection supports that pseudoprogression gene expression pathways are dominated with immune activation, whereas progression is predominated with cell cycle activity. Automated image processing and spatial expression analysis however highlight a failure to apply these broad expressional differences in a subset of cases with clinically challenging admixed histology. Encouragingly, applying unsupervised clustering approaches over our segmented histologic images provides novel understanding of morphologically derived differences between progression and pseudoprogression. Spatially derived data further highlighted polarization of myeloid populations that may underscore the tumorgenicity of novel lesions. These findings not only help provide further clarity of potential targets for pathologists to better assist stratification of progression and pseudoprogression, but also highlight the evolution of tumor-immune microenvironment changes which promote tumor recurrence. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40478-023-01587-w. BioMed Central 2023-12-04 /pmc/articles/PMC10694987/ /pubmed/38049893 http://dx.doi.org/10.1186/s40478-023-01587-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wang, Wesley Tugaoen, Jonah Domingo Fadda, Paolo Toland, Amanda Ewart Ma, Qin Elder, J. Brad Giglio, Pierre Otero, José Javier Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences |
title | Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences |
title_full | Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences |
title_fullStr | Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences |
title_full_unstemmed | Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences |
title_short | Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences |
title_sort | glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694987/ https://www.ncbi.nlm.nih.gov/pubmed/38049893 http://dx.doi.org/10.1186/s40478-023-01587-w |
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