Figure 1 from Single-Cell Atlas of Lineage States, Tumor Microenvironment, and Subtype-Specific Expression Programs in Gastric Cancer

Abstract

<p>scRNA-seq of gastric tumor and normal samples defines 34 cell states including rare cell populations. <b>A,</b> Schematic representation of experimental design and techniques used in this study. Thirty-one unique patients with gastric cancer undergoing surgical resection or endoscopy had tumor samples (<i>n</i> = 31) and adjacent normal samples (<i>n</i> = 11) harvested for analysis. Tumors ranged from stage I to IV and included samples of both primary tumors, distant (peritoneal) metastases, and matched normal gastric tissues. Twenty-nine tumors had scRNA-seq performed using the 10× platform (along with 11 adjacent normal tissues). Four patients had PDOs generated from their tumors (4 tumors + 4 adjacent normal), which were also sequenced by 10× scRNA-seq. A subset of 13 samples also had DSP performed using the NanoString GeoMx platform (10 tumor + 3 normal). In total, more than 200,000 cells were sequenced in this study. <b>B,</b> Uniform Manifold Approximation and Projection (UMAP) of 152,423 cells representing 34 unique cell states color-coded by their corresponding cell lineage or subtype. Each dot in the UMAP represents a single cell. <b>C,</b> Cell-lineage compositions of gastric cancer and normal samples inferred by scRNA-seq data. Middle (bubble plot), cell subclusters (rows) by tumor versus normal, stage, and gastric cancer histologic subtype (diffuse vs. intestinal). The size of the circle represents the cell proportion of each specific cell lineage/type. The circles are color-coded by defined cell lineages/types as shown in <b>B</b>. The stacked bar graph on the top shows the number of cells in each meta-cluster for each category. The histogram on the right shows the absolute cell numbers in each subcluster. <b>D,</b> Cluster–cluster heat map of gene-expression data of all 34 cell states across all samples using Pearson correlation matrix. Darker colors correspond to higher correlation. <b>E,</b> Pseudotime analysis of plasma metacluster generated using Monocle. The trajectory was rooted against the plasmablasts. Pseudotime analysis demonstrates different stages of plasma cell differentiation and maturation including plasmablasts, short-lived plasma cells, and long-lived plasma cells. <b>F,</b> Expression of <i>PLVAP</i> and <i>RGS5</i> in endothelial (STE2) and fibroblast (STF2 and STF4) clusters. Doublets were identified and filtered out using DoubletFinder. <i>PLVAP</i><sup>+</sup><i>RGS5</i><sup>−</sup> cells are predominantly present in the endothelial cluster (STE2). <i>PLVAP</i><sup>−</sup><i>RGS5</i><sup>+</sup> cells are predominant in the fibroblast cluster (STF2). The STF4 cluster shows cells expressing <i>PLVAP</i><sup>+</sup><i>RGS5</i><sup>+</sup>, suggestive of a rare mixed-lineage population.</p>

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