Extended Data Fig. 1: Single-cell RNA-Seq analysis and ex vivo drug profiling of standard-of-care treatment for glioblastoma. | Nature Medicine

Extended Data Fig. 1: Single-cell RNA-Seq analysis and ex vivo drug profiling of standard-of-care treatment for glioblastoma.

From: High-throughput identification of repurposable neuroactive drugs with potent anti-glioblastoma activity

Extended Data Fig. 1

a, Example FACS gates of patient sample P011 to enrich for glioblastoma cells prior to scRNA-Seq (n = 50,000 cells shown). b, c, UMAP projection of 7684 single-cell transcriptomes colored by b, patient (P007: 3,475 cells; P011: 1,490 cells; P012: 330 cells; P013: 2,389 cells, this study), and c, cluster-id. TME, tumor microenvironment; OPC, oligodendrocyte precursor cells; EC, endothelial cell; TAM, tumor-associated macrophage; NK, natural killer cell. d, % cells expressing genes (y-axis) per patient (data points) and subpopulation (x-axis) across 22 glioblastoma patient samples (dots) and 3 scRNA-Seq datasets (shape). e, Example IF images of patient samples (P047, P049) labeled with different glioblastoma markers (Nestin, EGFR, and CX43). f, Quantification of IF images in e across n = 4 glioblastoma patient samples (dots) for EGFR and CX43 expression in either Nestin+ or Nestin- cells. Two-tailed t-test. g, Genes (columns) enriched in (NES-, S100B-, and CD45-) triple-negative cells (‘Other’) compared to ([NES+ or S100B + ] and CD45-) cells across 22 patients (rows) from three scRNA-seq cohorts. Heatmap depicts log2(fold change) of genes enriched in ‘Other’ cells. Expression of top-10 genes (columns) per patient (rows) clustered into 3 gene modules. h, Cell-type specific enrichment analysis (Web-CSEA69) of the ‘Other’ enriched gene modules as in g. Dots represent individual Web-CSEA datasets, example member genes of their respective gene modules annotated above. i, Example single-cell crops of cleaved CASP3 + /- negative cells by IF in the image dataset used to train a convolutional neural network (CNN) based on nuclear (DAPI) and cell morphology (Brightfield) to detect apoptotic cells. j, Apoptotic classifier CNN performance in classifying the test image dataset (n = 1,214 single-cell crops). k, % cells classified as apoptotic by the CNN across the prospective cohort (n = 27 patients) and marker defined populations. l, Temozolomide PCY score (TMZ; rows; n = 4 concentrations) across patient samples (columns; prospective cohort, n = 27; retrospective cohort, n = 18). Color indicates the PCY score for glioblastoma cells. Values beyond color scale limits set to minimum and maximum values. m, Clinical predictability of ex vivo TMZ response (averaged across n = 4 concentrations) in stratifying progression free survival (PFS) of the prospective cohort (n = 16 patients). P-values from survival curve comparison by the log-rank (Mantel-Cox) test. d,f,k, Boxplots as in Fig. 1b.

Source data

Back to article page