Journal of Jilin University(Medicine Edition) ›› 2023, Vol. 49 ›› Issue (5): 1268-1279.doi: 10.13481/j.1671-587X.20230521

• Research in clinical medicine • Previous Articles    

Bioinformatics analysis on predition effect of subtypes of cell pyroptosis and APOD on prognosis of gastric cancer patients

Haikang CUI1,Xudong ZHANG1,Xiaoning LI1,Xi YANG1,Lan YANG1,2,Wenjie ZHANG1,2()   

  1. 1.Department of Pathology, School of Medicial Sciences, Shihezi University, Shihezi 832002, China
    2.Key Laboratory of Xinjiang Endemic and Ethnic Diseases, Ministry of Education, Shihezi 832002, China
  • Received:2022-11-07 Online:2023-09-28 Published:2023-10-26
  • Contact: Wenjie ZHANG E-mail:zhangwj82@qq.com

Abstract:

Objective To seek the prognostic markers for the gastric cancer (GC) patients, and to achieve the early diagnosis and treatment of GC, and to provide the evidence for improving the survival rate of the GC patients. Methods The clinical data and transcriptome data of 407 and 433 GC patients were downloaded from the The Cancer Genome Atlas(TCGA) Database and GSE84437 Dataset, and merged; the GC tissue samples were classified and typed based on the expression levels of cell death-related genes and the ConsensusClusterPlus Package,and were divided into type A(342 cases) and type B(465 cases);the GC patients were divided into low expression group and high expression group according to the expression level of apolipoprotein D(APOD);the survminer Data Package was used to compare the differences in prognosis of the patients with different subtypes;the ssGSEA Algorithm was used to compare the differences in immune cell infiltration of the patients with different subtypes; Lasso regression and Cox regression were used to construct the prognostic risk model for the GC patients; the clinical characteristics of model genes were filtered;the differential expression of APOD in adjacent normal tissue and GC tissue was analyzed by Public Databases;GSEA analysis was used to assess the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment of APOD; the CIBERSORT Algorithm was used to evaluate the correlation between the content of immune cells and expression of APOD;the online website was used to analyze the drug sensitivity of APOD. Results There was statistically significant difference in prognosis of the patients with two subtypes of cell pyroptosis(P=0.002); the levels of 22 kinds of immune cells of the patients with type A were higher than those with type B(P<0.01); there were statistically significant differences in the percentages of two subtypes of cell pyroptosis of the patients with different ages (P<0.01) and N stages (P=0.04). The Public Databases analysis results showed that the expression of APOD in tumor tissue of the GC patients was lower than that in adjacent normal tissue; the survival results showed that compared with low expression group,the patients in high expression group had poorer prognosis; the clinical correlation analysis results showed that there were significant differences in the APOD expression of the patients with different T stage (P<0.05); the GSEA analysis results showed that high expression group enriched in the cell adhesion pathways, leukocyte endothelial migration pathways, and gap junction pathways; the immune infiltration analysis results showed that the contents of follicular helper T lymphocytes, CD4+ memory activated T lymphocytes, resting NK cells, and neutrophils in high expression group were lower than those in low expression group; APOD had positive correlations with CXC chemokine ligand 12(CXCL12)(r=0.500,P<0.01),transforming growth factor beta 1(TGFB1) (r=0.313,P<0.01),chemokine CC chemokine ligand 19(CCL19)(r=0.518,P<0.01),and CX3C chemokine receptor 1(CX3CR1)(r=0.444,P<0.01);the drug sensitivity analysis results showed that there were positive correlations between APOD and AZD-7762, KW-2449, and TG-101348(0<r<0.3,P<0.05). Conclusion Cell pyroptosis subtypes can effectively evaluate the prognosis of the GC patients; APOD can be regarded as the novel prognostic marker and therapeutic target for GC.

Key words: Gastric neoplasm, Cell pyroptosis, Apolipoprotein D, Survival, Prognosis, Immune infiltration

CLC Number: 

  • R735.2