The multilayered transcriptional architecture of glioblastoma ecosystems [* Cross-Reference *]

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Masashi Nomura; Avishay Spitzer; Kevin C. Johnson; Luciano Garofano; Djamel Nehar-Belaid; Noam Galili Darnell; Alissa Greenwald; Lillian Bussema; Young Taek Oh; Frederick S. Varn; Fulvio D’Angelo; Simon Gritsch; Kevin Anderson; Simona Migliozzi; L. Nicolas Gonzalez Castro; Tamrin ChowdhFury; Nicolas Robine; Catherine Reeves; Jong Bae Park; Anuja Lipsa; Frank Hertel; Anna Golebiewska; Simone P. Niclou; Labeeba Nusrat; Sorcha Kellet; Sunit Das; Hyo Eun Moon; Sun Ha Paek; Franck Bielle; Alice Laurenge; Anna Luisa Di Stefano; Bertrand Mathon; Alberto Pïcca; Marc Sanson; Shota Tanaka; Nobuhito Saito; David M. Ashley; Stephen T. Keir; Keith L. Ligon; Jason T. Huse; W.K. Alfred Yung; Anna Lasorella; Roel G.W. Verhaak; Antonio Iavarone; Mario L. Suvà; Itay Tirosh, 2025, "The multilayered transcriptional architecture of glioblastoma ecosystems [* Cross-Reference *]", https://lore.list.lu/citation?persistentId=perma:LIST.AMWNSU, LIST Open Repository, V1

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Description	In isocitrate dehydrogenase wildtype glioblastoma (GBM), cellular heterogeneity across and within tumors may drive therapeutic resistance. Here we analyzed 121 primary and recurrent GBM samples from 59 patients using single-nucleus RNA sequencing and bulk tumor DNA sequencing to characterize GBM transcriptional heterogeneity. First, GBMs can be classified by their broad cellular composition, encompassing malignant and nonmalignant cell types. Second, in each cell type we describe the diversity of cellular states and their pathway activation, particularly an expanded set of malignant cell states, including glial progenitor cell-like, neuronal-like and cilia-like. Third, the remaining variation between GBMs highlights three baseline gene expression programs. These three layers of heterogeneity are interrelated and partially associated with specific genetic aberrations, thereby defining three stereotypic GBM ecosystems. This work provides an unparalleled view of the multilayered transcriptional architecture of GBM. How this architecture evolves during disease progression is addressed in the companion manuscript by Spitzer et al. (2025-05-01) *This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to https://doi.org/10.1038/s41588-025-02167-5 for the original and latest version of the publication* (2026-07-01)
Subject	Chemistry; Medicine, Health and Life Sciences
Keyword	Biology, Glioblastoma, Ecosystem, Architecture, Computational biology, Evolutionary biology, Ecology, Genetics, Cancer research, Archaeology
License/Data Use Agreement	Custom Dataset Terms


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Persistent Identifier	perma:LIST.AMWNSU
Publication Date	2026-07-06
Title	The multilayered transcriptional architecture of glioblastoma ecosystems [* Cross-Reference *]
Other Identifier	https://doi.org/10.1038/s41588-025-02167-5 OpenAlex ID: https://openalex.org/W4410242531
Author	(Broad Institute, Harvard University, Massachusetts General Hospital, Center for Cancer Research, The University of Tokyo)https://orcid.org/0000-0001-6095-7849 (Tel Aviv University, Tel Aviv Sourasky Medical Center, Weizmann Institute of Science)https://orcid.org/0000-0001-6551-9338 (Yale University)https://orcid.org/0000-0003-0016-5158 (University of Miami, Sylvester Comprehensive Cancer Center)https://orcid.org/0000-0001-8582-0865 (Jackson Laboratory)https://orcid.org/0000-0001-6002-5021 Noam Galili Darnell (Weizmann Institute of Science) (Weizmann Institute of Science)https://orcid.org/0000-0001-5428-9645 (Broad Institute, Harvard University, Massachusetts General Hospital, Center for Cancer Research)https://orcid.org/0000-0001-5469-3816 (University of Miami, Sylvester Comprehensive Cancer Center)https://orcid.org/0000-0001-8356-2428 (University of Connecticut, Jackson Laboratory, UConn Health)https://orcid.org/0000-0001-6307-016X (University of Miami, Sylvester Comprehensive Cancer Center, Neurological Surgery)https://orcid.org/0000-0002-4940-4693 (Broad Institute, Harvard University, Massachusetts General Hospital, Center for Cancer Research)https://orcid.org/0000-0001-5682-5712 (Jackson Laboratory)https://orcid.org/0000-0002-2362-273X Simona Migliozzi (University of Miami, Sylvester Comprehensive Cancer Center) (Broad Institute, Brigham and Women's Hospital, Harvard University, Massachusetts General Hospital, Center for Neuro-Oncology, Dana-Farber Cancer Institute, Center for Cancer Research)https://orcid.org/0000-0001-7699-5188 Tamrin ChowdhFury (Yale University) (New York Genome Center)https://orcid.org/0000-0001-5698-8183 (New York Genome Center)https://orcid.org/0000-0002-9942-8909 (National Cancer Center)https://orcid.org/0000-0003-0207-0697 (Luxembourg Institute of Health)https://orcid.org/0000-0002-9668-6048 Frank Hertel (Luxembourg Institute of Health) (Luxembourg Institute of Health)https://orcid.org/0000-0002-4160-2521 (University of Luxembourg, Luxembourg Institute of Health, Luxembourg Institute of Science and Technology)https://orcid.org/0000-0002-3417-9534 Labeeba Nusrat (St. Michael's Hospital, University of Toronto) Sorcha Kellet (St. Michael's Hospital, University of Toronto) (St. Michael's Hospital, University of Toronto)https://orcid.org/0000-0002-2146-4168 Hyo Eun Moon (Cancer Research Institute) (Seoul National University, Cancer Research Institute, Advanced Institute of Convergence Technology)https://orcid.org/0000-0003-3007-8653 (Centre National de la Recherche Scientifique, Inserm, Sorbonne Université, Sorbonne Paris Cité, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital)https://orcid.org/0000-0001-6564-6388 (Centre National de la Recherche Scientifique, Inserm, Sorbonne Université, Sorbonne Paris Cité, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital)https://orcid.org/0000-0002-0058-3176 (Ospedale di Livorno, Hôpital Foch)https://orcid.org/0000-0003-1746-0647 (Sorbonne Université, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital)https://orcid.org/0000-0002-9182-5846 (Centre National de la Recherche Scientifique, Inserm, Sorbonne Université, Sorbonne Paris Cité, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital)https://orcid.org/0000-0001-7807-5393 (Centre National de la Recherche Scientifique, Inserm, Brain Tumour Charity, Sorbonne Université, Sorbonne Paris Cité, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital)https://orcid.org/0000-0002-1813-8476 Shota Tanaka (The University of Tokyo) (The University of Tokyo)https://orcid.org/0000-0001-9756-781X (Pediatric Brain Tumor Foundation)https://orcid.org/0000-0002-4754-5900 (Pediatric Brain Tumor Foundation)https://orcid.org/0000-0001-8630-3587 (Brigham and Women's Hospital, Dana-Farber Cancer Institute)https://orcid.org/0000-0002-7733-600X (The University of Texas MD Anderson Cancer Center)https://orcid.org/0000-0003-4514-0640 (The University of Texas MD Anderson Cancer Center)https://orcid.org/0000-0002-1669-0793 (University of Miami, Sylvester Comprehensive Cancer Center)https://orcid.org/0000-0002-1839-5421 (Yale University, Amsterdam University Medical Centers, University of Amsterdam)https://orcid.org/0000-0003-2773-0436 (University of Miami, Sylvester Comprehensive Cancer Center)https://orcid.org/0000-0002-0683-4634 (Broad Institute, Massachusetts General Hospital, Center for Cancer Research)https://orcid.org/0000-0001-9898-5351 (Weizmann Institute of Science)https://orcid.org/0000-0001-5477-2987
Point of Contact	Use email button above to contact. LIST QDKM (LIST)
Description	In isocitrate dehydrogenase wildtype glioblastoma (GBM), cellular heterogeneity across and within tumors may drive therapeutic resistance. Here we analyzed 121 primary and recurrent GBM samples from 59 patients using single-nucleus RNA sequencing and bulk tumor DNA sequencing to characterize GBM transcriptional heterogeneity. First, GBMs can be classified by their broad cellular composition, encompassing malignant and nonmalignant cell types. Second, in each cell type we describe the diversity of cellular states and their pathway activation, particularly an expanded set of malignant cell states, including glial progenitor cell-like, neuronal-like and cilia-like. Third, the remaining variation between GBMs highlights three baseline gene expression programs. These three layers of heterogeneity are interrelated and partially associated with specific genetic aberrations, thereby defining three stereotypic GBM ecosystems. This work provides an unparalleled view of the multilayered transcriptional architecture of GBM. How this architecture evolves during disease progression is addressed in the companion manuscript by Spitzer et al. (2025-05-01) *This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to https://doi.org/10.1038/s41588-025-02167-5 for the original and latest version of the publication* (2026-07-01)
Subject	Chemistry; Medicine, Health and Life Sciences
Keyword	Biology Glioblastoma Ecosystem Architecture Computational biology Evolutionary biology Ecology Genetics Cancer research Archaeology
Topic Classification	Single-cell and spatial transcriptomics Genomics and Chromatin Dynamics Glioma Diagnosis and Treatment
Deposit Date	2025-05-01
Data Type	Article
Data Source	Nature Genetics

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