Global hypo-methylation in a proportion of glioblastoma enriched for an astrocytic signature is associated with increased invasion and altered immune landscape
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Evaluation Summary:
Glioblastoma is a challenging disease with a high level of heterogeneity. Here the authors use global methylation profiling of tumor-initiating cells and matched iNSCs and identify a subgroup of hypomethylated tumors with an astrocytic phenotype. Understanding heterogeneity in glioblastoma is a major challenge, and the identification of alterations of functional and clinical impact is of importance to the field.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)
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Abstract
We describe a subset of glioblastoma, the most prevalent malignant adult brain tumour, harbouring a bias towards hypomethylation at defined differentially methylated regions. This epigenetic signature correlates with an enrichment for an astrocytic gene signature, which together with the identification of enriched predicted binding sites of transcription factors known to cause demethylation and to be involved in astrocytic/glial lineage specification, point to a shared ontogeny between these glioblastomas and astroglial progenitors. At functional level, increased invasiveness, at least in part mediated by SRPX2, and macrophage infiltration characterise this subset of glioblastoma.
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Evaluation Summary:
Glioblastoma is a challenging disease with a high level of heterogeneity. Here the authors use global methylation profiling of tumor-initiating cells and matched iNSCs and identify a subgroup of hypomethylated tumors with an astrocytic phenotype. Understanding heterogeneity in glioblastoma is a major challenge, and the identification of alterations of functional and clinical impact is of importance to the field.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)
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Reviewer #1 (Public Review):
Glioblastoma is a complex disease and understanding its molecular complexity would be of great potential utility. Here the authors identify a subgroup of glioblastoma with a distinct methylation profile. They then perform transcriptomic analysis to support an astrocytic phenotype. However, it is unclear how this fits into existing paradigms and how this signature relates to known mutational profiles in glioblastoma.
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Reviewer #2 (Public Review):
Boot et al. investigate epigenetic DNA methylation changes in matching glioma-initiating cells and neural progenitors from glioblastoma patients. The authors find that a subset of glioblastomas shows a bias towards hypomethylation. This hypomethylation-bias subset of tumours also shows enrichment in an astrocytic lineage gene expression signature. A deeper analysis of differentially methylated regions in this subset of tumours revealed enrichment of binding sites of astrocyte-specific transcription factors in the differentially methylated regions. Functionally, xenografts of hypomethylation-bias tumour lines are more invasive, and the authors identified SPRX2 as a new candidate regulator of invasion and sphere formation. The authors further identify RARRES2 as a candidate molecule correlated with immune …
Reviewer #2 (Public Review):
Boot et al. investigate epigenetic DNA methylation changes in matching glioma-initiating cells and neural progenitors from glioblastoma patients. The authors find that a subset of glioblastomas shows a bias towards hypomethylation. This hypomethylation-bias subset of tumours also shows enrichment in an astrocytic lineage gene expression signature. A deeper analysis of differentially methylated regions in this subset of tumours revealed enrichment of binding sites of astrocyte-specific transcription factors in the differentially methylated regions. Functionally, xenografts of hypomethylation-bias tumour lines are more invasive, and the authors identified SPRX2 as a new candidate regulator of invasion and sphere formation. The authors further identify RARRES2 as a candidate molecule correlated with immune infiltration.
The strengths of this manuscript are the in-depth comparison of methylation signatures between glioblastoma cells and induced progenitor cells that will provide a useful resource, as well as the demonstration that an astrocyte lineage-specific signature identifies a subset of glioblastomas and implies functional relevance of developmental pathways in these tumours.
Overall, this is a very interesting study, but some weaknesses remain. These weaknesses include a reliance on in vitro experiments and bioinformatical correlations for functional validation of candidates. Furthermore, it is not quite clear where the cutoff value lies to separate bias vs. non-bias tumours - presumably glioblastomas will lie on a spectrum ranging from hyper- to hypomethylation.
The presented data should be more comprehensive to fully justify the conclusions.
Some of the claims made in the manuscript should be tempered: for example, whether astrocyte signature-enriched glioblastoma points to a shared ontogeny with astroglial progenitors is speculative. Increased macrophage infiltration into bias/enriched glioblastoma is only supported by correlation evidence from RNA-sequencing data.
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Reviewer #3 (Public Review):
The authors have used 10/11 GICs along with matched fibroblasts from dura that were reprogrammed to EPSC and then differentiated to iNSC and subsequently into iAPC and iOPC. On (most) of these lines the authors have done methylation and gene expression analysis. They find some GIC samples with reduced methylation levels (3 or 4, depending on the cutoff), and the remainder of the manuscript is based on finding what makes these cells differ from the others. Methylation analysis is done by comparing GICs with syngeneic iNSCs and screening for enrichment of TF binding motifs in various comparisons. DEG analysis compares a variety of different conditions.
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