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GBMdeconvoluteR accurately infers proportions of neoplastic and immune cell populations from bulk glioblastoma transcriptomics data

Lookup NU author(s): Dr Martina Finetti, Bethany Hunter, Professor Andrew FilbyORCiD, Dr David McDonald


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© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. BACKGROUND: Characterizing and quantifying cell types within glioblastoma (GBM) tumors at scale will facilitate a better understanding of the association between the cellular landscape and tumor phenotypes or clinical correlates. We aimed to develop a tool that deconvolutes immune and neoplastic cells within the GBM tumor microenvironment from bulk RNA sequencing data. METHODS: We developed an IDH wild-type (IDHwt) GBM-specific single immune cell reference consisting of B cells, T-cells, NK-cells, microglia, tumor associated macrophages, monocytes, mast and DC cells. We used this alongside an existing neoplastic single cell-type reference for astrocyte-like, oligodendrocyte- and neuronal progenitor-like and mesenchymal GBM cancer cells to create both marker and gene signature matrix-based deconvolution tools. We applied single-cell resolution imaging mass cytometry (IMC) to ten IDHwt GBM samples, five paired primary and recurrent tumors, to determine which deconvolution approach performed best. RESULTS: Marker-based deconvolution using GBM-tissue specific markers was most accurate for both immune cells and cancer cells, so we packaged this approach as GBMdeconvoluteR. We applied GBMdeconvoluteR to bulk GBM RNAseq data from The Cancer Genome Atlas and recapitulated recent findings from multi-omics single cell studies with regards associations between mesenchymal GBM cancer cells and both lymphoid and myeloid cells. Furthermore, we expanded upon this to show that these associations are stronger in patients with worse prognosis. CONCLUSIONS: GBMdeconvoluteR accurately quantifies immune and neoplastic cell proportions in IDHwt GBM bulk RNA sequencing data and is accessible here:

Publication metadata

Author(s): Ajaib S, Lodha D, Pollock S, Hemmings G, Finetti MA, Gusnanto A, Chakrabarty A, Ismail A, Wilson E, Varn FS, Hunter B, Filby A, Brockman AA, McDonald D, Verhaak RGW, Ihrie RA, Stead LF

Publication type: Article

Publication status: Published

Journal: Neuro-Oncology

Year: 2023

Volume: 25

Issue: 7

Pages: 1236-1248

Print publication date: 01/07/2023

Online publication date: 23/01/2023

Acceptance date: 02/04/2018

ISSN (print): 1522-8517

ISSN (electronic): 1523-5866

Publisher: Oxford University Press


DOI: 10.1093/neuonc/noad021

PubMed id: 36689332


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