Cuproptosis-related gene DLAT is a biomarker of the prognosis and immune microenvironment of gastric cancer and affects the invasion and migration of cells

Abstract

Objective: Cuproptosis is a novel cell death dependent on mitochondrial respiration and regulated by copper. This study aimed to investigate the cuproptosis-related gene DLAT potential value in gastric cancer (GC).

Methods: Bioinformatics was used to analyze DLAT expression. DLAT expression in GC cell lines was detected using qRT-PCR. Cell proliferation ability was assessed using CCK8 and cell cycle assay. Cell migration and invasion were assessed using wound healing and transwell assay. A prognostic assessment was performed through survival and Cox regression analysis. DLAT protein expression was analyzed through HPA immunohistochemistry. Biological functions and processes were analyzed through GO and KEGG enrichment analysis and PPI. Correlation with immune cell infiltration and immune checkpoint genes was analyzed for DLAT.

Results: DLAT expression was upregulated in GC tissues and cells and correlated with shorter survival for patients. Age, gender, histological typing, lymph node metastasis, and distant metastasis were identified as independent prognostic factors affecting OS in GC. DLAT protein was upregulated in GC. The biological functions and pathways enriched in DLAT were mainly linked to mitochondrial respiration and the TCA cycle. The expression of DLAT was found to be positively correlated with the infiltration of Th and Th2 immune cells and only positively correlated with the expression of the BTN2A1 immune checkpoint gene.

Conclusion: DLAT has the potential to serve as a prognostic assessment factor in GC. The expression of DLAT was correlated with immune infiltration and tumor immune escape, providing a new target for immunotherapy of GC.

Keywords: DLAT; cuproptosis; gastric cancer; immune infiltration; prognosis.

FIGURE 1

DLAT expression in gastric cancer tissues and cells (A). DLAT expression in Pan‐cancer (B). DLAT expression was upregulated in the unpaired GC group in TCGA‐STAD compared to the normal group (C). DLAT expression was upregulated in the GC group in TCGA‐STAD in combination with GTEx normal samples compared to the normal group (D). DLAT expression was upregulated in the paired GC group in TCGA‐STAD (E). DLAT expression was upregulated in MGC‐803, SNU‐1, HGC‐27, and AGS compared to GES‐1. * p < 0.05, ** p < 0.01, *** p < 0.001.

FIGURE 2

Association of DLAT expression with clinicopathologic parameters (A). The expression of DLAT in the Normal group and tumor group was analyzed by TCGA (B) Individual cancer stages (C). Race (D), Age (E), Gender (F), N (G), Grade (H). Histological subtypes. *p < 0.05, **p < 0.01, ***p < 0.001.

FIGURE 3

Prognostic analysis and protein expression analysis of DLAT in gastric cancer (A). Kaplan–Meier prognosis analysis of OS and PFS of GC patients (B). Kaplan–Meier prognosis analysis of PFS of GC patients (C). ROC curve. Nomograms (D) and calibration (E) curves predicting 1‐and 3‐year OS of GC patients (F). DLAT protein expression analysis (G). The expression of DLAT protein in GC was analyzed by immunohistochemistry. *p < 0.05, **p < 0.01, ***p < 0.001.

FIGURE 4

DLAT affected the proliferation, invasion and migration of gastric cancer cells (A). The siRNA silencing efficiency was detected by qRT‐PCR (B). CCK8 assay was performed to assess the proliferative ability of AGS cells after silencing DLAT (C). Wound healing assay to assess the migration of AGS cells after silencing DLAT (D). Transwell migration assay also to assess the migration ability of AGS cells after silencing DLAT (E). Transwell invasion assay to assess the invasion of AGS cells after silencing DLAT (F). Flow cytometry to assess the cycle of AGS cells after silencing DLAT. *p < 0.05, **p < 0.01, ***p < 0.001.

FIGURE 5

Proteins interaction analysis and GO and KEGG analyses (A). Intersection of gene sets from interaction proteins and similar genes of DLAT. Correlations in DLAT compared with NDUFS1 (B) and CS (C). (D) Top 15 proteins interacting most in two gene sets (E). Correlations of interaction proteins. GO (F) and KEGG (G) analyses. *p < 0.05, **p < 0.01, ***p < 0.001.

FIGURE 6

Immune infiltration analysis (A). Correlations between DLAT and Infiltrations of multiple immune cells in GC (B). Correlations between DLAT and different immune checkpoint genes. *p < 0.05, **p < 0.01, ***p < 0.001.