The Upregulation of PLXDC2 Correlates with Immune Microenvironment Characteristics and Predicts Prognosis in Gastric Cancer

Abstract

Tumor microenvironment (TME) has been demonstrated to exhibit a regulatory effect on the progressions of gastric cancer (GC). However, the related functions of stromal and immune components (TME-associated genes) in TME remain largely unclear. From the TCGA dataset, we downloaded the clinical data of 375 GC cases and then estimated the percentage of tumor-infiltrating immunocytes (TICs) and the levels of immune and stromal constituents by the use of CIBERSORT and ESTIMATE tolls. Univariate assays were applied to study the differentially expressed genes. The associations between the clinical information of GC patients and the expressions of the specific genes were analyzed based on the TCGA datasets. The effect of Plexin domain containing 2 (PLXDC2) expression on TICs was conducted. We observed that PLXDC2 expression was distinctly upregulated in GC specimens compared with nontumor gastric specimens. Its upregulation was associated with advanced clinical stages and predicted a shorter overall survival of GC patients. The genes in the group of higher expressing PLXDC2 were primarily enriched in immunity-associated events. By the use of CIBERSORT, we observed that PLXDC2 expressions were related to the proportion of dendritic cells resting, T cell CD4 memory resting, eosinophils, mastocyte resting, mononuclear cells, plasma cells, T cell follicle helper, macrophage M2, and dendritic cells activated. Overall, our discoveries revealed that the expression of PLXDC2 was remarkable in GC, might be a possible biomarker for GC, and provided novel contents regarding immune infiltrates, offering novel insight for treatments of GC.

Figure 1

The association of scores with the survivals of GC cases. (a) Kaplan-Meier assays for GC cases based on low or high scores in ImmuneScore. (b) Survival analysis for StromalScore. (c) Survival analysis for GC cases grouped by ESTIMATEScore.

Figure 2

Association of StromalScore and ImmuneScore with clinical characteristics. Distribution of (a) ImmuneScore, (b) StromalScore, and (c) ESTIMATEScore in stage, T classification, M classification, and N classification.

Figure 3

The expression pattern of DEGs and their enrichment analysis of GO and KEGG. (a) Heatmap for dysregulated genes in ImmuneScore. (b) Heatmap for dysregulated genes in StromalScore. (c, d) Venn plots of common dysregulated genes shared by ImmuneScore and StromalScore. (e, f) GO and KEGG enrichment analyses for 640 DEGs.

Figure 4

Univariate assays with 640 DEGs. The top distinct genes were listed.

Figure 5

The expression of PLXDC2 in GC and its clinical significance. (a) The upregulation of PLXDC2 in GC specimens using TCGA and GTEx datasets. (b) No significance was observed just using TCGA datasets. (c) The levels of PLXDC2 in a paired differentiation analysis. (d) Survival assays of 371 GC patients based on the mean expression of PLXDC2. (e–h) The expression of PLXDC2 in stage (e), T classification (f), M classification (g), and N classification (h), ^∗p < 0.05.

Figure 6

GSEA for cases with high PLXDC2 expressions and low expressions.

Figure 7

TIC profiles in cancer specimens and correlation assays. (a) Bar plot showing the proportion of 21 kinds of TICs in GC cases. (b) Heatmap of the correlations between 21 kinds of TICs and numeric.

Figure 8

Associations of TICs proportion with PLXDC2 expressions. (a) Violin plot showed the ratio differentiation of 21 kinds of immune cells between GC samples with high PLXDC2 expressions and low PLXDC2 expressions. (b) Scatter plot showed the association of 8 kinds of TICs proportion with the PLXDC2 expressions. (c) Venn plot exhibited eight kinds of TICs related to PLXDC2 expressions.

Figure 9

The increased expression of PLXDC2 and its oncogenic roles. (a) RT-PCR for the expression of PLXDC2 in 9 pairs of GC specimens and matched nontumor specimens. (b) The levels of PLXDC2 in five GC cells were determined by RT-PCR. (c) RT-PCR confirmed the transfection efficiency of si-PLXDC2-1 and si-PLXDC2-2 in BGC823 and MKN45 cells. (d) Cell proliferation ability was compared between the PLXDC2 siRNA stable transfection and negative control in BGC823 and MKN45 cells, ^∗∗p < 0.01.