GBMdeconvoluteR

GBMdeconvoluteR quantifies neoplastic and immune cell population proportions in IDH wild-type (IDHwt) glioblastoma from bulk RNA sequencing to characterize tumor cellular composition.

Key Features:

• Specificity for IDHwt GBM: Tailored for IDH wild-type glioblastoma and uses a single immune cell reference including B cells, T-cells, NK-cells, microglia, tumor-associated macrophages, monocytes, mast cells, and dendritic cells (DCs).
• Comprehensive neoplastic references: Includes GBM cancer cell references for astrocyte-like, oligodendrocyte- and neuronal progenitor-like, and mesenchymal cell states.
• Marker-based deconvolution: Employs a marker-based deconvolution strategy using GBM tissue-specific markers to quantify cell-type proportions from bulk RNA sequencing.
• Validation by imaging mass cytometry: Validated with single-cell resolution imaging mass cytometry (IMC) on ten IDHwt GBM samples, including five paired primary and recurrent tumors.
• Recapitulation of single-cell multi-omics findings: Recapitulates associations observed in multi-omics single-cell studies, notably between mesenchymal GBM cancer cells and lymphoid and myeloid immune cells.
• Clinical correlation: Demonstrates that associations between mesenchymal cancer cells and immune cells are more pronounced in patients with poorer prognoses.
• Bulk RNA sequencing input: Operates on bulk RNA sequencing data to derive quantitative estimates of immune and neoplastic cell proportions.

Scientific Applications:

• Cellular composition analysis: Quantify proportions of immune and neoplastic cell populations within IDHwt glioblastoma samples.
• Immune infiltration studies: Analyze lymphoid and myeloid infiltration patterns and their association with GBM cancer cell states.
• Cancer cell heterogeneity: Investigate prevalence and interactions of astrocyte-like, oligodendrocyte- and neuronal progenitor-like, and mesenchymal GBM cells.
• Clinical correlation and prognosis: Correlate tumor microenvironment composition with patient prognosis and potential implications for therapy response.

Methodology:

Marker-based deconvolution techniques integrate GBM-specific single-cell references to analyze bulk RNA sequencing data, with tissue-specific markers validated by single-cell resolution imaging mass cytometry (IMC).