Comprehensive analysis of peroxisome proliferator-activated receptors to predict the drug resistance, immune microenvironment, and prognosis in stomach adenocarcinomas.

BACKGROUND

Peroxisome proliferator-activated receptors (PPARs) exert multiple functions in the initiation and progression of stomach adenocarcinomas (STAD). This study analyzed the relationship between PPARs and the immune status, molecular mutations, and drug therapy in STAD.

METHODS

The expression profiles of three PPAR genes (PPARA, PPARD and PPARG) were downloaded from The Cancer Genome Atlas (TCGA) dataset to analyze their expression patterns across pan-cancer. The associations between PPARs and clinicopathologic features, prognosis, tumor microenvironment, genome mutation and drug sensitivity were also explored. Co-expression between two PPAR genes was calculated using Pearson analysis. Regulatory pathways of PPARs were scored using gene set variation analysis (GSVA) package. Quantitative real-time polymerase chain reaction (qRT-PCR), Western blot, Cell Counting Kit-8 (CCK-8) assay and transwell assay were conducted to analyze the expression and function of the PPAR genes in STAD cell lines (AGS and SGC7901 cells).

RESULTS

PPARA, PPARD and PPARG were more abnormally expressed in STAD samples and cell lines when compared to most of 32 type cancers in TCGA. In STAD, the expression of PPARD was higher in Grade 3+4 and male patients, while that of PPARG was higher in patient with Grade 3+4 and age > 60. Patients in high-PPARA expression group tended to have longer survival time. Co-expression analysis revealed 6 genes significantly correlated with the three PPAR genes in STAD. Single-sample GSEA (ssGSEA) showed that the three PPAR genes were enriched in 23 pathways, including MITOTIC_SPINDLE, MYC_TARGETS_V1, E2F_TARGETS and were closely correlated with immune cells, including NK_cells_resting, T_cells_CD4_memory_resting, and macrophages_M0. Immune checkpoint genes (CD274, SIGLEC15) were abnormally expressed between high-PPAR expression and low-PPAR expression groups. TTN, MUC16, FAT2 and ANK3 genes had a high mutation frequency in both high-PPARA/PPARG and low-PPARA/PPARG expression group. Fourteen and two PPARA/PPARD drugs were identified to be able to effectively treat patients in high-PPARA/PPARG and low-PPARA/PPARG expression groups, respectively. We also found that the chemotherapy drug Vinorelbine was positively correlated with the three PPAR genes, showing the potential of Vinorelbine to serve as a treatment drug for STAD. Furthermore, cell experiments demonstrated that PPARG had higher expression in AGS and SGC7901 cells, and that inhibiting PPARG suppressed the viability, migration and invasion of AGS and SGC7901 cells.

CONCLUSIONS

The current results confirmed that the three PPAR genes (PPARA, PPARD and PPARG) affected STAD development through mediating immune microenvironment and genome mutation.