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Barcoded viral tracing identifies immunosuppressive astrocyte–glioma interactions

Nature volume 644, pages 1097–1106 (2025)Cite this article

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Abstract

Glioblastoma (GBM) is the most lethal primary brain malignancy1. Immunosuppression in the GBM tumour microenvironment (TME) is an important barrier to immune-targeted therapies, but our understanding of the mechanisms of immune regulation in the GBM TME is limited2. Here we describe a viral barcode interaction-tracing approach3 to analyse TME cell–cell communication in GBM clinical samples and preclinical models at single-cell resolution. We combine it with single-cell and bulk RNA-sequencing analyses, human organotypic GBM cultures, in vivo cell-specific CRISPR–Cas9-driven genetic perturbations as well as human and mouse experimental systems to identify an annexin A1–formyl peptide receptor 1 (ANXA1–FPR1) bidirectional astrocyte–GBM communication pathway that limits tumour-specific immunity. FPR1 inhibits immunogenic necroptosis in tumour cells, and ANXA1 suppresses NF-κB and inflammasome activation in astrocytes. ANXA1 expression in astrocytes and FPR1 expression in cancer cells are associated with poor outcomes in individuals with GBM. The inactivation of astrocyte–glioma ANXA1–FPR1 signalling enhanced dendritic cell, T cell and macrophage responses, increasing infiltration by tumour-specific CD8+ T cells and limiting T cell exhaustion. In summary, we have developed a method to analyse TME cell–cell interactions at single-cell resolution in clinical samples and preclinical models, and used it to identify bidirectional astrocyte–GBM communication through ANXA1–FPR1 as a driver of immune evasion and tumour progression.

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Fig. 1: Patient-tissue RABID-seq identifies ANXA1+ astrocytes in human GBM.
Fig. 2: Tumour-anchored RABID-seq detects astrocyte–glioma communication.
Fig. 3: FPR1 expression in GBM suppresses necroptosis and is associated with worse prognosis.
Fig. 4: ANXA1 inhibits astrocyte immune responses.
Fig. 5: Disruption of astrocyte–glioma ANXA1–FPR1 crosstalk enhances anti-tumour immunity.

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Data availability

Sequencing data have been deposited in the Gene Expression Omnibus (GEO) under the respective SuperSeries accession codes: human data, GSE263612; mouse single cell data, GSE263613; mouse bulk RNA-seq data, GL261 sgFprl versus GL261 sgRandom, GSE263737; AAV sgGFAP-Anxal versus AAV GFAP-sgRosa, GSE263738. Publicly available datasets: scRNA-seq dataset from ref. 11, https://github.com/kpetrecca/NeuroOncology2022.git; spatial transcriptomics datasets from ref. 15, https://datadryad.org/dataset/doi:10.5061/dryad.h70rxwdmj; Ivy Glioblastoma Atlas (ref. 27), http://glioblastoma.alleninstitute.org; TCGA/GLASS, http://www.cbioportal.org; GRCh38 reference genome, https://ftp.ensembl.org/pub/release-113/fasta/homo_sapiens/dna/. All other data are available from the corresponding authors upon reasonable request. Correspondence and request for materials should be addressed to F.J.Q.

Source data are provided with this paper.

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Acknowledgements

We thank all Quintana lab members for discussion related. This work was supported by grants NS102807, ES02530, ES029136 and AI126880 from the NIH; RG4111A1 and JF2161-A-5 from the NMSS; RSG-14-198-01-LIB from the American Cancer Society; and PA-1604-08459 from the International Progressive MS Alliance. B.M.A. was supported by the Training Program in Nervous System Tumors (K12CA090354) from NCI/NIH; the Career Enhancement Program (CEP) for the NCI/NIH SPORE at Harvard Cancer Center (P50CA165962) from NCI/NIH; the Post-Doctoral Fellowship in Translational Medicine from the PhRMA Foundation; Cancer Neuroscience grant T32CA272386 from NCI/NIH; and 1IK2BX006568-01A1 from the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Biomedical Laboratory Research and Development. C.F.A. was supported by a scholarship from the German Academic Exchange Service (DAAD). M.D. was supported by the Swiss National Science Foundation (project number 199310) and the German Research Foundation (IMM‐PACT‐programme, 413517907). L.F. was funded by the Gemeinnützige Hertie-Stiftung (medMS-Doktorandenprogramm). M.A.W. was supported by NINDS, NIMH, NIDA and NCI (R01MH130458, R00NS114111, T32CA20720, R01MH132632 and R01DA061199). J.-H.L was supported by the Basic Science Research Program funded by the National Research Foundation of Korea (NRF)/Ministry of Education (2022R1A6A3A03071157), and a long-term postdoctoral fellowship funded by the Human Frontier Science Program (LT0015/2023-L). T.I. was supported by an EMBO postdoctoral fellowship (ALTF, 1009-2021). H.-G.L. was supported by a Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2021R1A6A3A14039088). K.L.L. was supported by NCI/NIH SPORE at Harvard Cancer Center P50CA165962. C.M.P. was supported by the National Multiple Sclerosis Society (FG-2307-42209) and the Mayer Foundation. We thank R. Krishnan for technical assistance with flow cytometry and FACS; L. Ding at the Brigham and Women’s Hospital NeuroTechnology Studio (NTS) for technical assistance with confocal microscopy; staff at the NTS for use of their 10× Chromium controller; K. Grieco and S. Valentin, the BWH pathologist assistants and staff at the Tissue and Blood Repository for tissue support.

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Author notes

  1. These authors contributed equally: Brian M. Andersen, Camilo Faust Akl

Authors and Affiliations

  1. Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Brian M. Andersen, Camilo Faust Akl, Michael A. Wheeler, Zhaorong Li, Michael Kilian, Joseph M. Rone, Jessica E. Kenison, Joon-Hyuk Lee, Hong-Gyun Lee, Carolina M. Polonio, Lillie Godinez, Gavin Piester, Tomer Illouz, Jessica J. Ye, Arianna Ghia, Jazmin Martinez, Elizabeth N. Chung, Lena Srun, Daniel Farrenkopf, Lucas E. Flausino, Anton M. Schüle, Liliana M. Sanmarco, Federico Giovannoni, Marc Charabati, Cristina Gutiérrez-Vázquez, Roni Nowarski & Francisco J. Quintana

  2. Department of Neurology, Veterans Affairs Medical Center, Harvard Medical School, Jamaica Plain, MA, USA

    Brian M. Andersen

  3. Faculty of Biology, University of Freiburg, Freiburg, Germany

    Camilo Faust Akl

  4. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Michael A. Wheeler, David Merrell, Jakob H. Weiss, Roni Nowarski, Gad Getz & Francisco J. Quintana

  5. The Gene Lay Institute of Immunology and Inflammation, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Michael A. Wheeler, Joseph M. Rone, Aditya Misra, Roni Nowarski & Francisco J. Quintana

  6. Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany

    Martin Diebold, Luca Fehrenbacher & Marco Prinz

  7. Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA

    Aditya Misra

  8. Department of Pathology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA

    Aditya Misra, Margaret M. Cusick, Prem S. Prabhakar, Connor C. Bossi, Emily Lapinskas & Keith L. Ligon

  9. Department of Pathology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Margaret M. Cusick, Prem S. Prabhakar, Connor C. Bossi, Emily Lapinskas & Keith L. Ligon

  10. Department of Pathology and Krantz Family Center for Cancer Research, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA

    Gad Getz

  11. Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany

    Marco Prinz

  12. Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    E. Antonio Chiocca

  13. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA

    David A. Reardon

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Contributions

B.M.A., C.F.A., M.A.W., D.A.R., E.A.C. and F.J.Q. designed the study. B.M.A., C.F.A., M.K., J.M.R., A.M., J.E.K., J-H.L., H-G.L., C.M.P., L.G., G.P., T.I., J.J.Y., A.G., J.M., E.N.C., L.S., D.F., L.E.F., A.M.S., L.M.S., F.G., M.C., C.G-V. and R.N. performed or assisted with in vitro and in vivo experiments. K.L.L., E.A.C., D.A.R., M.M.C., E.L., C.C.B. and P.S.P. provided neuropathology expertise, tissue resources and patient models. M.P., M.D. and L.F. performed GBM multiplex immunofluorescence. Z.L. and C.F.A. performed bioinformatic analysis. D.M., J.H.W., and G.G. performed multivariate survival analyses. B.M.A., C.F.A. and F.J.Q. wrote the manuscript with input from co-authors. F.J.Q. directed and supervised the study.

Corresponding author

Correspondence to Francisco J. Quintana.

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Competing interests

F.J.Q and M.A.W have filed a provisional patent regarding the RABID-seq technology used in this paper. The remaining authors declare no competing interests.

Peer review

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Nature thanks Michael Platten and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 scRNA-seq, spatial transcriptomic, and ptRABID-seq analysis of astrocytes in GBM.

(a) Biological relevance score of astrocyte DEGs; GBM vs. controls11. (b) Feature plot of ANXA1 in control and GBM scRNA-seq astrocytes. (c) Violin plot of ANXA1 expression by cell type in control and GBM. (d) Volcano plot of DEGs between ANXA1+ and ANXA1- astrocytes in human GBM scRNA-seq. (e) Control and GBM specimen staining of SOX2 to identify malignant cells. (f) Quantification of SOX2+ cells in control and GBM specimens. (n = 4 specimens each; p = 0.0286 by two-sided unpaired Mann-Whitney U-test). (g) ANXA1+ tumor cell (GFAP+ SOX2+) and astrocyte (GFAP+SOX2-) density at the infiltrating tumor zone (ITZ). Each point represents a separate brain, (n = 4 specimens each; p value from Mann-Whitney U-test). (h) ANXA1 staining in astrocytes in n = 5 GBMs in which malignant cells are distinguished by OLIG2 staining. Regions adjacent to tumor core (ITZ) were compared with regions distant from the tumor (leading edge; LE) when available. (i) ANXA1+ astrocyte density at LE vs. ITZ, using OLIG2 as a tumor marker. In total, n = 3,641 GBM-associated astrocytes at the ITZ and n = 1,213 GBM-associated astrocytes at the LE; two-tailed unpaired U-test. (j) ANXA1+ tumor cell (GFAP+ OLIG2+) and astrocyte (GFAP+OLIG2-) density at the ITZ. p = 0.0159 by Mann-Whitney U-test. (k,l) Spatial transcriptomics of the reactive astrocyte gene signature correlated to spatially defined layers programs (k) and to ANXA1 expression (l) in n = 13 GBMs. (m) Dot plot (top) and signature score (bottom) of cell type markers of cells analyzed by ptRABID-seq (n = 1,520 cells). (n) UMAP of CNV analysis (top, n = 3,157 malignant and 1,520 non-malignant cells), and cells grouped by patient (bottom) in ptRABID-seq. (o) Number of barcodes shared between astrocytes and other cell types (top) and divided by patient (bottom), as detected by RABID-seq. (p) Proportions of cell types in ptRABID-seq. (q, r) Average (q) and total (r) barcode numbers detected in each cell type in ptRABID-seq. (s) Shared barcodes between each cell type in ptRABID-seq. Data are mean and error bars show ± SEM (f, g, i, j).

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Extended Data Fig. 2 Detection of lentivirus transduction and rabies virus infection in human organotypic cultures.

(a) Quantification of GFP+ staining (indicating transduction by the helper lentivirus that delivers TVA and G) as determined by brightfield immunofluorescence detection (each dot represents a separate culture, and n = 6 organotypic cultures per condition from epilepsy surgery (non-GBM)). (b) Quantification of GFP+ cells by cell type. Each slide was co-stained for GFP, DAPI, and one cell type marker. Each dot represents a separate culture, and n = 5 organotypic cultures per condition from epilepsy surgery. (c) Quantification of apoptotic GFP+ cells by cell type using cleaved caspase-3 as a marker of apoptosis. Each slide was co-stained for GFP, one cell type marker, and cleaved caspase 3. Each dot represents a separate culture, and n = 5 organotypic cultures per condition from epilepsy surgery (non-GBM). (d) Quantification of mCherry+ staining (indicating rabies infection) as determined by brightfield immunofluorescence detection. Each dot represents a separate culture, and n = 6 organotypic cultures per condition. (e) Quantification of mCherry+ cells by cell type. Each slide was co-stained for mCherry, DAPI, and one cell type marker. Each dot represents a separate culture, and n = 5 organotypic cultures for astrocytes, n = 3 cultures for other cell types. (f) Quantification of apoptotic mCherry+ cells by cell type using cleaved caspase 3 as a marker of apoptosis. Each slide was co-stained for DAPI, mCherry, one cell type marker, and cleaved caspase 3. Each dot represents a separate culture, and N = 5 organotypic cultures for astrocytes and n = 3 for other cell types. (g-p) Representative images of control and lentivirus transduced cultures. (q-z) Representative images of control and rabies virus-infected cultures. Data are mean and error bars show ± SEM (a-f).

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Extended Data Fig. 3 Analysis of tumor-anchored RABID-seq.

GL261-TVA-G bearing mice were injected with 1,000 infectious units of rabies one week after tumor implantation; GL261-TVA-G bearing mice were used as controls (n = 5 each). (a-c) Quantification of total (a), cell-type specific (b) mCherry+ staining (indicating rabies infection), and cleaved caspase-3+ staining of mCherry+ cells (c) as determined by brightfield immunofluorescence detection. Each dot represents one animal, and in a, statistics were two sided unpaired t-test. (d) Overview images of control non-rabies injected tumor site (top) and rabies injected tumor site (bottom) from representative animals. Hematoxylin and eosin (H&E) reference images are taken from slices proximate to the immunofluorescence slices for reference purposes. (e-p) Representative images of rabies-injected and control staining by cell type. GFP-negative cells were used as controls when staining for GFAP and OLIG2 to exclude malignant cells. Data are mean and error bars show ± SEM (a-c).

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Extended Data Fig. 4 Tumor-anchored RABID-seq identifies regulators of glioma-TME interactions.

(a) Representative FACS plot of cells isolated from GL261-anchored RABID-seq one week after infection. (b) Dot plot showing cell type markers used for identification of cell types captured by taRABID-seq (n = 6 mice and 21,189 cells). (c) Cell type proportions by analyzed mouse sample. (d) Matrix showing shared barcodes between each cell type. (e) Anxa1 signature in mouse astrocytes isolated 14 or 21 days after tumor implantation. (f) Volcano plot showing DEGs of GL261 cells highly connected to astrocytes vs. lowly connected to astrocytes, with immunosuppression-related genes of interest labeled. (g) Kaplan-Meier plot of GL261 bearing mice with gRNA targeting Axl or a random gRNA sequence (n = 26 mice sgRandom and n = 16 mice sgAxl; p calculated from log-rank analysis; represents 3 pooled experiments). (h) Scatter plot of gene expression correlation between GL261 connected vs. not connected to activated microglia, by GL261 connected vs. not connected with infiltrating monocyte-derived macrophages.

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Extended Data Fig. 5 FPR expression in GBM and survival.

(a-c) FPR1 (a), FPR2 (b), and FPR3 (c) in a GBM scRNA-seq dataset11 (n = 25 patients). (d) Dot plot of FPR1 by cell type in GBM scRNA-seq data11. (e) RNA-seq of Fpr1,2,3 in GL261 cells. Each dot represents a mouse or cell culture replicate. n = 3 GL261 bearing mice, n = 3 cell culture replicates per group. (f) FPR1 expression in GBM cells (one dot per patient, and n = 18 patients; statistics by two-way ANOVA with Tukey’s multiple comparisons test; post-hoc unpaired two tailed t-tests were then performed). (g) Fpr1 inactivation in GL261-implanted mice (n = 3 mice per group; each dot represents average staining from a 9 high power field tile scan from one mouse’s tumor; statistics were from two-sided unpaired t-test). (h) Thymidine incorporation assay of GL261 sub-lines cultured for 6 h with thymidine. P values were calculated by unpaired two-sided t-test. (i) Survival of mice bearing CT2A harboring Fpr1 or random sequence gRNA (n = 20 mice per group, statistics were log rank; represents 3 pooled experiments). (j) Survival of mice bearing control GL261 or GL261 with Fpr2 gRNA (n = 20 mice for sgRandom; n = 10 mice for sgFpr2; statistical test by log rank; repeated twice with identical results). (k) Survival of Rag2–/– mice bearing GL261 harboring Fpr1 or random control gRNA (n = 8 mice sgRandom and n = 7 sgFpr1 group; statistics by log rank; repeated twice with identical results). (l) Box and whisker plot of FPR1 expression vs. spatially defined layers programs16. (m) Box and whisker plot of FPR1 correlation to malignant metaprograms16. Boxplots display median, interquartile range (IQR) ± 1.5IQR and outlier values (n) Correlation of FPR1 and ANXA1 expression from the Ivy Glioblastoma Atlas27. (o) Transwell migration assay of GL261 sgRandom vs GL261 sgFpr1; p value from unpaired two-tailed t-test. *** p < 0.001, **p < 0.005. Data are mean and error bars show ± SEM (e-h, o). Illustrations in a created in BioRender (Lee, J. https://BioRender.com/0bkvepw; 2025).

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Extended Data Fig. 6 Immune response from necroptotic GL261.

(a-b) Immunofluorescence of pMLKL in two human GBM isolates following necroptosis induction in the presence of rhANXA1 and/or an FPR1 neutralizing antibody (each dot represents a separate well, with n = 3 wells per condition; p values were calculated by two-sided unpaired t-test and replicated twice). (c-d) In vitro demonstration of GL261-RIPK3act (c) or GL261-OVA-RIPK3act (d) cell death as measured 48 h after the addition of 50 μM B/B homodimerizer (n = 3 wells per condition; two-sided unpaired t-test; experiment was replicated 3 times). (e-k) Flow cytometry analysis of vehicle (n = 3) vs RIPK3-activated (n = 5 mice) GL261-infiltrating cDC1 (e), cDC2 (f;) subsets, and CD8+ T cells (n = 4 and n = 5 mice) for IFN-γ (g), IL-10 (h), PD1 and TIM3 expression (I); and FOXP3 expression (j) and IL10 expression (k) in the CD4+ population. Unpaired two-tailed t-test (e-k). (l) Schematic for antigen presentation assay in which lysate from RIPK3 activated or control GL261-OVA cells was pulsed onto splenic DCs, and co-cultured with transgenic SIINFEKL-specific OT1 CD8 T cells. (m-o) Mean fluorescence intensities of CD11c+ MHCII+ dendritic cells, I-a/I-e (m), CD80 (n), and CD86 (o). (p) Percent proliferating CD3+ CD8+ T cells from OT1 mice, as measured by Cell Trace dilution, after 72 h of co-culture with lysate-pulsed DCs. (q) Thymidine incorporation assay of co-cultures taken in the final 12 h. (r-w) Flow cytometry of OT1 CD8 T cells from co-culture, displaying upregulation of IL-2 (r), CD25 (s), CD44 (t), IFNγ (u), CD107a (v), and PD1 (w). n = 3 replicates per group, p values from unpaired two tailed t-test for m-w. Data are mean and error bars show ± SEM (a-k; m-w.

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Extended Data Fig. 7 Investigation of astrocyte ANXA1 signaling.

(a) ELISA quantification in supernatants of primary human astrocytes (n = 3 wells per group; unpaired two-tailed t-test; graph represents one replicate experiment which was performed 3 times with similar results). (b) Representative images from staining of human astrocytes for cleaved IL-1β. (c) Representative images corresponding to Fig. 4j, detecting nuclear NF-κB in human astrocyte-GBM co-cultures. (d-e) Validation of astrocyte-specific Anxa1 knockdown with AAV-PHP.eB and sgRNA. Representative image (d) and automated quantification (e) of ANXA1+ cells of GFAP+ astrocytes (n = 5 sgRosa-transduced and n = 5 sgAnxa1 transduced mice; p values from unpaired two-tailed t-test). (f) Schematic of lentivirus-mediated Anxa1 perturbation study. (g) Kaplan-Meier survival plot of GL261 bearing mice following astrocyte-specific Anxa1 inactivation with lentivirus. Transduction with a random gRNA was used as a control. (n = 9 mice for sgRandom and n = 10 mice for sgAnxa1 group; p values from log rank; experiment was repeated twice with similar results). (h-i) Volcano plot (h) and ingenuity pathway analysis (IPA; i) of astrocytes from sgAnxa1 vs. sgRosa transduced mice (n = 4 sgAnxa1 and n = 3 sgRosa mice per group). (j) Gene set enrichment pathway analysis (GSEA) of astrocyte specific knockdown of Anxa1 showing decreased G protein-coupled receptor signaling in GL261 cells (n = 3 sgRosa and n = 4 sgAnxa1 transduced mice). (k) Representative images of immunofluorescence staining of ASC, GFAP, and DAPI in peritumoral regions from GL261-bearing mice from day 24, corresponding to Fig. 4n. (l) Kaplan-Meier survival plot of GL261 bearing Rag2–/– mice that were pre-treated with AAV-PHP.eB transducing sgAnxa1 or Rosa26 control under the GFAP promoter, as in Fig. 4l,m. (n = 8 mice per group, and p value from log rank; experiment replicated twice). Data are mean and error bars show ± SEM (a, e).

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Extended Data Fig. 8 Flow gating, TAM RNA-seq in GL261sgFpr1 and AAV PHP-eB-GFAP-sgAnxa1.

(a) Flow cytometry gating scheme. (b,c) Ingenuity pathway analysis on microglia (b) and monocyte-derived macrophages (c), based on differential gene expression between sgFpr1 vs. sg Random GL261 bearing mice (n = 4 mice for sgRandom and n = 5 mice for sgFpr1 group).

Extended Data Fig. 9 Effect on T cells and DCs of Fpr1 perturbation and overexpression in GL261 cells.

(a-d) Analysis of CD4 T-cells in the presence or absence of GL261 cell inactivation of Fpr1. (a) FOXP3+ CD4+ T cells (n = 4 sgRandom and n = 5 sgFpr1 mice), (b) IL-10+ CD4+ T cells (n = 4 sgRandom and n = 5 sgFpr1 mice), (c) FOXP3-IL-10+ CD4+ T cells (n = 4 sgRandom and n = 5 sgFpr1 mice), and (d) IL-2+ CD4+ T cells were quantified (n = 4 sgRandom and n = 5 sgFpr1 mice). (e-h) CD8 T cell suppression upon over-expression of FPR1 in GL261, including tetramer staining for GARC-1 (e; n = 6 control and n = 7 Fpr1 OE mice) and CD107a (f; n = 6 control and n = 7 Fpr1 OE mice), IFN-γ (g; n = 6 control and n = 7 Fpr1 OE mice) and TNF (h; n = 6 control and n = 7 Fpr1 OE mice). (i-n) Conventional (cDC) and monocyte-derived dendritic cell (moDC) quantification and gene expression analysis following GL261 cell inactivation of Fpr1, including cDC1 abundance (i; n = 4 mice per group), pathway analysis (j; n = 3 sgRandom and n = 3 sgFpr1 mice), cDC2 abundance (k; n = 4 sg Random and n = 5 sgFpr1 mice per group) and pathway analysis (l; n = 3 sgRandom and n = 3 sgFpr1 mice), and monocyte-derived DC (moDC) abundance (m; n = 4 sgRandom and n = 6 sgFpr1 mice) and pathway analysis (n; n = 3 sgRandom and n = 3 sgFpr1 mice). (o, p) Exhaustion markers of CD8 T cells from animals receiving sgAnxa1 or sgRosa are shown (n = 10 for sgRosa and n = 7 for sgAnxa1; left, PD-1, and right, TIM-3). (p) contour plot of exhaustion stages of CD8+ T cells. (q-r). Pathway analysis on microglia (q) and monocyte-derived macrophages (r) based on RNA-seq between mice transduced with AAV-PHP.eB sgAnxa1 vs. sgRosa followed by GL261-Luc2 implantation (n = 3 mice per group). All p values were from two-sided unpaired t-test. Data are mean and error bars show ± SEM (a-i; k, m, o).

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Supplementary information

Supplementary Tables

Table 1: GBM patient characteristics for patient tissue RABID-seq. Table 2: GBM isolates for in vitro mechanistic studies.

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Supplementary Data

Supplementary Data 1–22.

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Andersen, B.M., Faust Akl, C., Wheeler, M.A. et al. Barcoded viral tracing identifies immunosuppressive astrocyte–glioma interactions. Nature 644, 1097–1106 (2025). https://doi.org/10.1038/s41586-025-09191-9

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