Single-cell analysis uncovers ductal cell subpopulations in human PDAC

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Single-cell analysis uncovers ductal cell subpopulations in human PDAC Single-cell analysis uncovers ductal cell subpopulations in human PDAC. A, Graphical scheme describing the workflow. Single-cell analysis uncovers ductal cell subpopulations in human PDAC. A, Graphical scheme describing the workflow. Human and murine pancreatic tumors were dissociated into single cells. Two fractions of cells were collected by FACS from each sample: (1) all viable cell fraction (DAPI−); (2) fibroblast-enriched fraction (DAPI−, CD45−, CD31−, and EPCAM−). The sorted cells from each fraction were subjected to single-cell capture, barcoding, and reverse transcription using the 10X Genomics platform. B, Unsupervised clustering of viable cells from six human PDAC resections and two adjacent-normal pancreata, represented as a t-SNE plot. Different cell type clusters are color coded. C, Bubble plot showing selected cell type–specific markers across all clusters. Size of dots represents the fraction of cells expressing a particular marker, and intensity of color indicates the level of mean expression. Legends are shown below. D, Reclustering of the ductal cell types in the data set (clusters 2, 8, and 15 from B), represented as a t-SNE plot. E, Proportion of cells from adjacent-normal pancreata and tumor resections present in each ductal cell subcluster. The horizontal black line represents the input contribution of adjacent-normal or tumor tissues into the data set. F, Violin plot showing normalized expression of marker genes for the different ductal cell subclusters. UMI, unique molecular identifier. G, Hallmark pathways enriched in the three tumor-derived ductal cell subclusters (subclusters 1, 3, and 4) relative to the adjacent-normal–derived ductal cell subcluster (subcluster 2). Size of dots represents the intersection of upregulated genes (>2 logFC) with hallmark pathway gene sets, and intensity of color indicates log10(q-value). Legends are shown below. Ela Elyada et al. Cancer Discov 2019;9:1102-1123 ©2019 by American Association for Cancer Research