PREreview of Spatial multi-omics defines a shared glioblastoma infiltrative signature at the resection margin

Pre-review of “Spatial multi-omics defines a shared glioblastoma infiltrative signature at the resection margin”

 by Tony Avril, Marc Aubry of the Proteostasis and Cancer team INSERM U1242

Proteostasis and Cancer & @omics Teams

INSERM UMR1242 Oncogenesis Stress Signaling

Centre Eugène Marquis, Rennes (France)

Summary of the article

In this manuscript, Pai et al (doi: https://doi.org/10.1101/2024.11.05.621879) aim at understanding the biology of GB tumors at their margins, that remains after surgery. To do so, they use single-nucleus (sn)RNA-seq and snATAC-seq approaches. They explore the spatial distribution of the margin vs core gene profiles they have identified. They describe a margin signature associated with a new TEAD1/EGFR signaling axis.

General comments

The results obtained by the authors are of significant interest, and overall provide a useful resource for the community to investigate core vs margin GB cells. We think that the study could benefit from reanalysis of existing signatures and of a refinement of both text & figure (see suggestions in specific points below). In general, could the authors draw and name specific areas of interest in all the UMAP and as they did in Fig.2b and Suppl.Fig.2d. In addition, all spatial representations (especially in Fig. 3 and 4) would gain in visibility if specific areas established in Fig.1g. i.e. Core, IT, CT and Margin were drawn.

Specific comments

Figure 1 and related Supplemental Figures 2 and 5:

Fig.1d. Are all the GB samples (except #2) wild-type IDH1? Could the IDH1mut samples included in the study bias the analysis? The authors should check the specific input of case 2 in their findings.

Fig.1e. How the authors interpret the enrichment of annotation ‘Bile acid metabolism’ in the C3 cluster? Is this cluster associated with necrotic regions?

Fig.1f. The authors should comment/explain why the abnormal neurons were under-represented in the snATACseq compared to the snRNAseq approach (Fig.1e).

Suppl.Fig.2 The authors should provide UMAP representations of snATACseq color by cluster and split by sample for each GBM (C+M) analyzed as they did for snRNAseq data in Supp.Fig.1a.

Fig.1g. How do the authors deal with the data obtained from necrotic zones, where RNA is known to be unstable?

Suppl.Fig.5c. How do the authors explain the specific and exclusive regions of non-tumoral ex/ni neurons and oligodendrocytes?

Figures 2 and 3 and related Supplemental Figures 2 and 5:

Fig.2h., 2i. and Fig.3c. Could the authors indicate the number of genes used for each gene annotation (at least in the ‘Methods’ section)?

Figure 6:

Could the authors analyze the expressions of TEAD1 and its co-activators YAP/TAZ in spatial transcriptomic ST1 and ST2. Are they associate with margin zones?

Fig.6e. What is the rational to use LN as negative controls?

Competing interests

The authors declare that they have no competing interests.

Competing interests

The authors declare that they have no competing interests.