Highlights
- •
Longitudinal glioma evolution follows an IDH mutation-dependent trajectory
- •
Hypermutation and CDKN2A deletions underlie increased proliferation at recurrence
- •
Recurrent IDH-wild-type neoplastic cells up-regulate neuronal signaling programs
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Mesenchymal transitions associate with distinct myeloid cell interactions
Summary
Graphical abstract
Keywords
Introduction
- Wen P.Y.
- Weller M.
- Lee E.Q.
- Alexander B.M.
- Barnholtz-Sloan J.S.
- Barthel F.P.
- Batchelor T.T.
- Bindra R.S.
- Chang S.M.
- Chiocca E.A.
- et al.
Results
GLASS cohort
Longitudinal cellular heterogeneity in glioma
- Richards L.M.
- Whitley O.K.N.
- MacLeod G.
- Cavalli F.M.G.
- Coutinho F.J.
- Jaramillo J.E.
- Svergun N.
- Riverin M.
- Croucher D.C.
- Kushida M.
- et al.
Histological features underlie subtype switching and cell-state changes at recurrence
Acquired somatic alterations at recurrence associate with changes in cellular composition
Neuronal signaling activity is increased in recurrent IDHwt tumors
Mesenchymal tumors exhibit a distinct myeloid cell phenotype
- Muller S.
- Kohanbash G.
- Liu S.J.
- Alvarado B.
- Carrera D.
- Bhaduri A.
- Watchmaker P.B.
- Yagnik G.
- Di Lullo E.
- Malatesta M.
- et al.
Antigen presentation is disrupted at recurrence in IDHmut-noncodel glioma
- Cloughesy T.F.
- Mochizuki A.Y.
- Orpilla J.R.
- Hugo W.
- Lee A.H.
- Davidson T.B.
- Wang A.C.
- Ellingson B.M.
- Rytlewski J.A.
- Sanders C.M.
- et al.
Discussion
- Pombo Antunes A.R.
- Scheyltjens I.
- Lodi F.
- Messiaen J.
- Antoranz A.
- Duerinck J.
- Kancheva D.
- Martens L.
- De Vlaminck K.
- Van Hove H.
- et al.
Limitations of the study
STAR★Methods
Key resources table
REAGENT or RESOURCE | SOURCE | IDENTIFIER |
---|---|---|
Antibodies | ||
BV421 anti KI67 | BD Biosciences | RRID:AB_2686897 |
AF488 anti SOX2 | Thermo Fisher Scientific | RRID:AB_2574479 |
AF555 anti EGFR | Cell Signaling Technology | Cat#5108S |
Rabbit anti CD14 | Abcam | RRID:AB_2889158 |
AF647 anti Olig2 | Abcam | Cat#ab225100 |
AF700 anti CD44 | Novus Biologicals | Cat#NBP1-41266AF700 |
AF568 Goat anti Rabbit Highly cross absorbed secondary antibody | Thermo Fisher Scientific | RRID:AB_10563566 |
AF594 anti SNAP25 | Novus Biologicals | Cat#NBP2-74245AF594 |
AF700 anti NeuN | Novus Biologicals | Cat#NBP1-92693AF700 |
AF647 anti alpha SMA | Novus Biologicals | Cat#NBP2-34522AF647 |
JF549 anti Oncostatin M | Novus Biologicals | Cat#NB120-10842JF549 |
Biological samples | ||
Glioma tissue and matched normal blood | Henry Ford Health System | N/A |
Glioma tissue and matched normal blood | Seoul National University | N/A |
Chemicals | ||
Histo-Clear | National Diagnostics | Cat#HS-202 |
Antigen Retrieval Buffer (Citrate, pH6) | Abcam | Cat#ab93678 |
Fc Receptor Blocker | Innovex | Cat#NB309 |
Background Buster | Innovex | Cat#NB306 |
Fluoromount G | SouthernBiotech | Cat#0100-01 |
Cover Glass | Thermo Scientific | Cat#152450 |
Slides | Denville Scientific | Cat#M1021 |
Saponin | Sigma | Cat#S7900-100G |
Triton X-100 | Sigma | Cat#T8787 |
Bovin serum albumin IgG free | Jackson Immuno Research | RRID:AB_2336946 |
Normal rabbit serum | Jackson Immuno Research | RRID:AB_2337123 |
Sytox blue | Thermo Fisher | Cat#S11348 |
DAPI | Thermo Fisher | Cat#D1306 |
Critical commercial assays | ||
AllPrep DNA/RNA Mini Kit | Qiagen | Cat#80204 |
SureSelectXT Low-Input Reagent Kit | Agilent | Cat#5191-4080 |
SureSelectXT Human All Exon V6 +COSMIC | Agilent | Cat#5190-9307 |
QIAamp DNA Mini Kit | Qiagen | Cat#51104 |
KAPA Hyper Prep Kit (Illumina) | Roche | Cat#7962363001 |
KAPA mRNA Hyperprep Kit | Roche | Cat#8098123702 |
Tempus xO Assay | Tempus | N/A |
KAPA stranded mRNAseq Kit | Roche | Cat#7962207001 |
NuGEN Ovation RNAseq System | Tecan | Cat#7102-A01 |
Deposited data | ||
Processed DNA somatic alteration data | This paper | https://www.synapse.org/glass |
RNAseq pseudocount and TPM data | This paper | https://www.synapse.org/glass |
Digitized H&E images | This paper | https://styx.neurology.emory.edu/girder/#collection/625dda70622f966e826a0446 |
Custom pipeline and analysis code | This paper | https://github.com/fsvarn/GLASSx/ |
Longitudinal glioma RNAseq fastq files | European Genome Phenome Archive | EGAS00001001041 |
Longitudinal glioma RNAseq fastq files | European Genome Phenome Archive | EGAS00001001880 |
Longitudinal glioma RNAseq bam files | European Genome Phenome Archive | EGAS00001001033 |
Longitudinal glioma RNAseq bam files | European Genome Phenome Archive | EGAS00001001255 |
Longitudinal glioma RNAseq fastq files | European Genome Phenome Archive | EGAS00001003790 |
Longitudinal glioma RNAseq fastq files | Sequencing Read Archive | BioProject#PRJNA320312 |
Longitudinal glioma whole exome and RNAseq fastq files | Sequencing Read Archive | BioProject# PRJNA482620 |
Longitudinal TCGA GBM LGG RNAseq fastq files | Genomic Data Commons | https://portal.gdc.cancer.gov/ |
TOIL TCGA TARGET GTEx RNAseq TPM data | University of California Santa Cruz Xenabrowser | https://xenabrowser.net/datapages/ |
Ivy Glioblastoma Atlas Project RNAseq FPKM data | Ivy GAP | https://glioblastoma.alleninstitute.org/static/download.html |
Processed glioblastoma single-cell data | Broad Single Cell Portal | Study: Single cell RNA-seq of adult and pediatric glioblastoma |
Multi-sector single-cell glioma RNAseq count data | Gene Expression Omnibus | GSE117891 |
RNAseq count data from FACS-sorted glioma cell populations | BrainTIME Portal | https://joycelab.shinyapps.io/braintime/ |
b37 reference genome (human_g1k_v37_decoy) | GATK Resource Bundle | https://gatk.broadinstitute.org/hc/en-us/articles/360035890811-Resource-bundle |
Pan-glioma single-cell RNAseq data | Synapse | https://www.synapse.org/#!Synapse:syn26375549 |
Software and algorithms | ||
bedtools |
Quinlan, and Hall, 2010
|
https://bedtools.readthedocs.io/en/latest/ |
Seuratv3.2.3 |
Stuart et al., 2019
|
https://satijalab.org/seurat/ |
BWA MEM 0.7.17 |
Li, and Durbin, 2009
|
http://bio-bwa.sourceforge.net/ |
GATK 4.0.10.1 |
McKenna et al., 2010
|
https://gatk.broadinstitute.org/hc/en-us |
TITAN |
Ha et al., 2014
|
https://github.com/gavinha/TitanCNA |
OptiType v1.3.2 |
Szolek et al., 2014
|
https://github.com/FRED-2/OptiType |
pVACseq v4.0.10 |
Hundal et al., 2016
|
https://pvac-seq.readthedocs.io/en/latest/ |
LOHHLA |
McGranahan et al., 2017
|
https://bitbucket.org/mcgranahanlab/lohhla/ |
STARv2.7.5 |
Dobin et al., 2013
|
https://github.com/alexdobin/STAR |
fastp v0.20.0 |
Chen et al., 2018
|
https://github.com/OpenGene/fastp |
kallisto v0.46.0 |
Bray et al., 2016
|
https://pachterlab.github.io/kallisto/ |
ssgsea.GBM.classification |
Wang et al., 2017
|
N/A |
CIBERSORTx webserver |
Newman et al., 2019
|
https://cibersortx.stanford.edu/ |
CIBERSORTx docker |
Newman et al., 2019
|
https://hub.docker.com/r/cibersortx/hires |
Imaris 9.0.2 and 9.4 | Bitplane | http://www.bitplane.com/imaris/imaris |
Flowjo v10 | Flowjo LLC | https://www.flowjo.com/solutions/flowjo |
R v3.6.1 | The R Project for Statistical Computing | https://www.r-project.org/ |
topGO v2.38.1 | Bioconductor | https://bioconductor.org/packages/release/bioc/html/topGO.html |
Resource availability
Lead contact
Materials availability
Experimental model and subject details
Human subjects
Method details
GLASS datasets
Public datasets
Whole-exome and whole-genome analysis
RNA preprocessing
Quality control
Bulk transcriptional subtype classification
Joint single-cell and bulk RNAseq dataset
Deconvolution analyses
Immunofluorescence staining and image acquisition
Histo-cytometry
Validation of cell-state proportions
Annotation and validation of histological features
Histological feature adjustment
Validation of cell state gene expression profiles
Cell-state gene expression profile analysis
Quantification and statistical analysis
Data and code availability
- •
Estimated count and transcript per million gene expression matrices as well as mutation calls, copy number calls, and all downstream tables generated for this study can be downloaded on Synapse (https://www.synapse.org/glass). Digitized H&E images are available on the Digital Slide Archive (https://styx.neurology.emory.edu/girder/#collection/625dda70622f966e826a0446).
- •
All custom scripts, pipelines, and code used in data processing and figure creation is available on the project’s Github repository (https://github.com/fsvarn/GLASSx).
- •
Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.
Acknowledgments
Author contributions
Declaration of interests
Supplemental information
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Table S1. Sequencing centers and hospitals with corresponding GLASS barcode designations for newly added GLASS data, related to Figure 1
-
Table S2. Clinical characteristics of GLASS RNAseq cohort arranged by glioma molecular subtype and time point, related to Figure 1
-
Table S3. CIBERSORTx single-cell signature matrix, related to Figure 1
-
Table S4. Histological feature pathology definitions and pathologist annotations, related to Figure 2
-
Table S5. Cell-state-specific post-treatment gene signatures, related to Figure 4
-
Table S6. Transcriptional subtype-specific myeloid gene signatures, related to Figure 5
-
Table S7. Mesenchymal myeloid gene signature, related to Figure 5
-
Table S8. Candidate ligand-receptor interactions associated with mesenchymal transition, related to Figure 5
-
Document S1. List of consortium members and affiliations
References
-
iGLASS: imaging integration into the Glioma Longitudinal Analysis Consortium.Neuro. Oncol. 2020; 22: 1545-1546
-
Longitudinal molecular trajectories of diffuse glioma in adults.Nature. 2019; 576: 112-120
-
Outer radial glia-like cancer stem cells contribute to heterogeneity of glioblastoma.Cell Stem Cell. 2020; 26: 48-63.e6
-
Mesenchymal differentiation mediated by NF-kappaB promotes radiation resistance in glioblastoma.Cancer Cell. 2013; 24: 331-346
-
Near-optimal probabilistic RNA-seq quantification.Nat. Biotechnol. 2016; 34: 525-527
-
The somatic genomic landscape of glioblastoma.Cell. 2013; 155: 462-477
-
Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas.N. Engl. J. Med. 2015; 372: 2481-2498
-
Single-cell analyses reveal YAP/TAZ as regulators of stemness and cell plasticity in Glioblastoma.Nat. Cancer. 2021; 2: 174-188
-
Molecular profiling reveals biologically discrete subsets and pathways of progression in diffuse glioma.Cell. 2016; 164: 550-563
-
Single-cell characterization of macrophages in glioblastoma reveals MARCO as a mesenchymal pro-tumor marker.Genome Med. 2021; 13: 88
-
fastp: an ultra-fast all-in-one FASTQ preprocessor.Bioinformatics. 2018; 34: i884-i890
-
Neoadjuvant anti-PD-1 immunotherapy promotes a survival benefit with intratumoral and systemic immune responses in recurrent glioblastoma.Nat. Med. 2019; 25: 477-486
-
The tumor microenvironment strongly impacts master transcriptional regulators and gene expression class of glioblastoma.Am. J. Pathol. 2012; 180: 2108-2119
-
Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy.Nat. Commun. 2020; 11: 3406
-
STAR: ultrafast universal RNA-seq aligner.Bioinformatics. 2013; 29: 15-21
-
How to analyse the spatiotemporal tumour samples needed to investigate cancer evolution: a case study using paired primary and recurrent glioblastoma.Int. J. Cancer. 2018; 142: 1620-1626
-
Glioblastomas acquire myeloid-affiliated transcriptional programs via epigenetic immunoediting to elicit immune evasion.Cell. 2021; 184: 2454-2470.e26
-
Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities.Nat. Cancer. 2021; 2: 141-156
-
Histo-cytometry: a method for highly multiplex quantitative tissue imaging analysis applied to dendritic cell subset microanatomy in lymph nodes.Immunity. 2012; 37: 364-376
-
MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma.Proc. Natl. Acad. Sci. USA. 2014; 111: 12550-12555
-
Glioma through the looking glass: molecular evolution of diffuse gliomas and the Glioma Longitudinal Analysis Consortium.Neuro. Oncol. 2018; 20: 873-884
-
Visualizing and interpreting cancer genomics data via the Xena platform.Nat. Biotechnol. 2020; 38: 675-678
-
Genetic mechanisms of immune evasion in colorectal cancer.Cancer Discov. 2018; 8: 730-749
-
TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data.Genome Res. 2014; 24: 1881-1893
-
Interactions between cancer cells and immune cells drive transitions to mesenchymal-like states in glioblastoma.Cancer Cell. 2021; 39: 779-792.e11
-
pVAC-Seq: a genome-guided in silico approach to identifying tumor neoantigens.Genome Med. 2016; 8: 11
-
Single-cell multimodal glioma analyses identify epigenetic regulators of cellular plasticity and environmental stress response.Nat. Genet. 2021; 53: 1456-1468
-
Oncostatin M promotes cancer cell plasticity through cooperative STAT3-SMAD3 signaling.Oncogene. 2017; 36: 4001-4013
-
CD8+ T-cell-mediated immunoediting influences genomic evolution and immune evasion in murine gliomas.Clin. Cancer Res. 2020; 26: 4390-4401
-
Whole-genome and multisector exome sequencing of primary and post-treatment glioblastoma reveals patterns of tumor evolution.Genome Res. 2015; 25: 316-327
-
Spatiotemporal evolution of the primary glioblastoma genome.Cancer Cell. 2015; 28: 318-328
-
Perspective of mesenchymal transformation in glioblastoma.Acta Neuropathol. Commun. 2021; 9: 50
-
Interrogation of the microenvironmental landscape in brain tumors reveals disease-specific alterations of immune cells.Cell. 2020; 181: 1643-1660.e17
-
Radiotherapy is associated with a deletion signature that contributes to poor outcomes in patients with cancer.Nat. Genet. 2021; 53: 1088-1096
-
Evolutionary trajectories of IDH(WT) glioblastomas reveal a common path of early tumorigenesis instigated years ahead of initial diagnosis.Cancer Cell. 2019; 35: 692-704.e12
-
Molecular pathology of tumors of the central nervous system.Ann. Oncol. 2019; 30: 1265-1278
-
Fast and accurate short read alignment with Burrows-Wheeler transform.Bioinformatics. 2009; 25: 1754-1760
-
The 2016 World Health Organization Classification of tumors of the central nervous system: a summary.Acta Neuropathol. 2016; 131: 803-820
-
DNA methylation and somatic mutations converge on the cell cycle and define similar evolutionary histories in brain tumors.Cancer Cell. 2015; 28: 307-317
-
Allele-specific HLA loss and immune escape in lung cancer evolution.Cell. 2017; 171: 1259-1271.e11
-
The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.Genome Res. 2010; 20: 1297-1303
-
Single-cell profiling of human gliomas reveals macrophage ontogeny as a basis for regional differences in macrophage activation in the tumor microenvironment.Genome Biol. 2017; 18: 234
-
An integrative model of cellular states, plasticity, and genetics for glioblastoma.Cell. 2019; 178: 835-849.e21
-
Determining cell type abundance and expression from bulk tissues with digital cytometry.Nat. Biotechnol. 2019; 37: 773-782
-
Single-cell RNA sequencing reveals functional heterogeneity of glioma-associated brain macrophages.Nat. Commun. 2021; 12: 1151
-
BBKNN: fast batch alignment of single cell transcriptomes.Bioinformatics. 2020; 36: 964-965
-
Single-cell profiling of myeloid cells in glioblastoma across species and disease stage reveals macrophage competition and specialization.Nat. Neurosci. 2021; 24: 595-610
-
An anatomic transcriptional atlas of human glioblastoma.Science. 2018; 360: 660-663
-
BEDTools: a flexible suite of utilities for comparing genomic features.Bioinformatics. 2010; 26: 841-842
-
A draft network of ligand-receptor-mediated multicellular signalling in human.Nat. Commun. 2015; 6: 7866
-
Gradient of developmental and injury response transcriptional states defines functional vulnerabilities underpinning glioblastoma heterogeneity.Nat. Cancer. 2021; 2: 157-173
-
Molecular and genetic properties of tumors associated with local immune cytolytic activity.Cell. 2015; 160: 48-61
-
Neoantigen-directed immune escape in lung cancer evolution.Nature. 2019; 567: 479-485
-
Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma.Genome Biol. 2020; 21: 216
-
Profiling cell type abundance and expression in bulk tissues with CIBERSORTx.in: Kidder B.L. Stem Cell Transcriptional Networks: Methods and Protocols. Springer, 2020: 135-157
-
Comprehensive integration of single-cell data.Cell. 2019; 177: 1888-1902.e21
-
OptiType: precision HLA typing from next-generation sequencing data.Bioinformatics. 2014; 30: 3310-3316
-
Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma.Nature. 2016; 539: 309-313
-
Glutamatergic synaptic input to glioma cells drives brain tumour progression.Nature. 2019; 573: 532-538
-
Neuronal activity promotes glioma growth through Neuroligin-3 secretion.Cell. 2015; 161: 803-816
-
Electrical and synaptic integration of glioma into neural circuits.Nature. 2019; 573: 539-545
-
Targeting neuronal activity-regulated neuroligin-3 dependency in high-grade glioma.Nature. 2017; 549: 533-537
-
Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq.Science. 2017; 355: eaai8478
-
Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1.Cancer Cell. 2010; 17: 98-110
-
Clonal evolution of glioblastoma under therapy.Nat. Genet. 2016; 48: 768-776
-
The phenotypes of proliferating glioblastoma cells reside on a single axis of variation.Cancer Discov. 2019; 9: 1708-1719
-
Humanized mice in studying efficacy and mechanisms of PD-1-targeted cancer immunotherapy.FASEB J. 2018; 32: 1537-1549
-
Tumor evolution of Glioma-Intrinsic Gene Expression Subtypes Associates with immunological changes in the microenvironment.Cancer Cell. 2017; 32: 42-56e.6
-
Cancer-cell-intrinsic mechanisms shaping the tumor immune landscape.Immunity. 2018; 48: 399-416
-
Glioblastoma in adults: a Society for Neuro-Oncology (SNO) and European Society of Neuro-Oncology (EANO) consensus review on current management and future directions.Neuro. Oncol. 2020; 22: 1073-1113
-
SCANPY: large-scale single-cell gene expression data analysis.Genome Biol. 2018; 19: 15
-
IL1 receptor antagonist controls transcriptional signature of inflammation in patients with metastatic breast cancer.Cancer Res. 2018; 78: 5243-5258
-
Transcriptome-based network analysis reveals a spectrum model of human macrophage activation.Immunity. 2014; 40: 274-288
-
Surveying brain tumor heterogeneity by single-cell RNA-sequencing of multi-sector biopsies.Natl. Sci. Rev. 2020; 7: 1306-1318
-
Single-cell transcriptome analysis of lineage diversity in high-grade glioma.Genome Med. 2018; 10: 57
-
Interfaces of malignant and immunologic clonal dynamics in ovarian cancer.Cell. 2018; 173: 1755-1769.e22
-
Immune and genomic correlates of response to anti-PD-1 immunotherapy in glioblastoma.Nat. Med. 2019; 25: 462-469
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