Transcriptional and methylation levels of IGFBP7 in patients with GC
To determine the expression levels of IGFBP7 in different cancers, we analyzed IGFBP7 expression among various cancers using the TIMER database. The results revealed that the expression levels of IGFBP7 were divergent in different cancers. In stomach adenocarcinoma (STAD), the expression of IGFBP7 was significantly increased compared to that in normal tissues (Fig. 1A). Oncomine database further revealed that IGFBP7 mRNA expression was upregulated in GC among seven datasets (Fig. 1B). Moreover, increased IGFBP7 expression in GC was confirmed using TCGA (Fig. 1C) and three GEO datasets (Fig. 1D-F). In addition, the mRNA expression of IGFBP7 was significantly upregulated in gastric diffuse adenocarcinoma, intestinal type adenocarcinoma, and mixed adenocarcinoma compared to normal gastric tissues (Table 1). Taken together, the results of multiple datasets suggested that the mRNA expression of IGFBP7 was significantly upregulated in GC tissues compared to normal gastric tissues.
Table 1
The mRNA expression of IGFBP7 was upregulated in different types of gastric cancer compared with normal gastric tissues.
Different types of GC vs. Normal | Fold Change | t-test | P-value | reference |
Diffuse Gastric Adenocarcinoma | 4.217 | 14.986 | 6.31E-13 | Chen Gastric |
Gastric Instinal type Adenocarcinoma | 2.333 | 11.245 | 6.19E-19 | Chen Gastric |
Gastric Mixed Adenocarcinoma | 4.414 | 8.377 | 1.24E-05 | Chen Gastric |
Gastric Instinal type Adenocarcinoma | 2.721 | 7.102 | 3.26E-09 | DErrico Gastric |
Gastric Mixed Adenocarcinoma | 4.669 | 7.154 | 1.54E-06 | DErrico Gastric |
Diffuse Gastric Adenocarcinoma | 2.238 | 4.998 | 4.16E-06 | Cho Gastric |
Gastric Adenocarcinoma | 2.139 | 2.529 | 3.50E-02 | Cho Gastric |
Gastric Instinal type Adenocarcinoma | 1.987 | 3.061 | 3.00E-03 | Cho Gastric |
To examine whether the mRNA expression of IGFBP7 was regulated by DNA methylation, we used the MEXPRESS tool to visualize the gene expression and methylation levels of IGFBP7. The results revealed that all probes in the promoter region showed a significantly negative correlation with IGFBP7 mRNA levels (Figure S1A). In addition, the promoter methylation level of IGFBP7 was reduced in GC compared to that in normal gastric tissue (Figure S1B), and promoter hypomethylation was associated with a poor prognosis of GC (Figure S1C). Altogether, the results showed that the expression of IGFBP7 was negatively regulated by methylation and was associated with prognosis of GC.
Relationship between IGFBP7 and clinicopathological characteristics of GC patients
To explore the relationship between the mRNA expression of IGFBP7 and the clinicopathological characteristics of GC patients, we analyzed clinical information of GC samples from the TCGA-STAD project. The results revealed that the mRNA expression of IGFBP7 was significantly increased in the G3 phase (P < 0.001, Fig. 2C), advanced tumor status (T2/3/4) (P < 0.001. Figure 2D) and advanced stages (II/III/IV) (P < 0.05, Fig. 2G). The correlation between IGFBP7 expression and stage was also confirmed using the GSE15459 dataset (P < 0.01, Fig. 2H). The expression level of IGFBP7 was significantly higher in GC samples with H. pylori infection than that in GC samples without H. pylori infection (P = 0.001, Fig. 2I). However, the mRNA expression of IGFBP7 showed no significant correlation with age, gender, node status and metastasis status (P > 0.05, Fig. 2A, B, E,F).
High IGFBP7 expression predicted a poor prognosis in GC patients
To explore the prognostic value of IGFBP7 in GC patients, we used GC sample data based on microarray chip and transcriptome sequencing from two different databases. The microarray chip results revealed that high IGFBP7 expression was strongly associated with poor overall survival (OS, Fig. 3A), first progression survival (FP, Fig. 3B) and post progression survival (PPS, Fig. 3C) of GC. Furthermore, the analysis based on transcriptome sequencing data indicated that high IGFBP7 expression was significantly related to poor overall survival (Fig. 3D) and disease-free survival (Fig. 3E). In addition, univariate and multivariate Cox regression analyses revealed that high IGFBP7 expression was an independent risk factor for unfavorable survival of GC (Table 2).
Table 2
Univariate and multivariate analysis of IGFBP7 mRNA levels and clinical parameters in TCGA gastric cancer patients
Variables | Univariate analysis | | Multivariate analysis |
| HR | 95%CI | P value | | HR | 95%CI | P value |
Age(years) | 1.68 | 1.13–2.49 | 0.010** | | 1.75 | 1.18–2.59 | 0.006** |
> 60 | | | | | | | |
≤ 60 | | | | | | | |
Gender | 1.47 | 1-2.15 | 0.049* | | 1.44 | 0.98–2.11 | 0.06 |
Male | | | | | | | |
Female | | | | | | | |
Stage | 1.72 | 1.19–2.48 | 0.004** | | 1.48 | 0.90–2.43 | 0.12 |
III + IV | | | | | | | |
I + II | | | | | | | |
Grade | 1.28 | 0.089–1.85 | 0.186 | | NA | NA | NA |
G3 | | | | | | | |
G1 + G2 | | | | | | | |
T stage | 1.46 | 0.94–2.26 | 0.096 | | NA | NA | NA |
T3 + T4 | | | | | | | |
T1 + T2 | | | | | | | |
N stage | 1.70 | 1.11–2.61 | 0.014* | | 1.29 | 0.72–2.87 | 0.39 |
N1 ~ N3 | | | | | | | |
N0 | | | | | | | |
M stage | 1.63 | 0.85–3.11 | 0.141 | | NA | NA | NA |
M1 | | | | | | | |
M0 | | | | | | | |
IGFBP7 | 1.5 | 1-2.1 | 0.032* | | 1.51 | 1.06–2.15 | 0.022* |
High | | | | | | | |
Low | | | | | | | |
*, P < 0.05; **, P < 0.01 |
Analyses of genes coexpressed with IGFBP7 in GC
Coexpressed genes typically have similar functions. The top eight coexpressed genes of IGFBP7 arranged by adjusted P values were identified. The correlation analysis revealed that IGFBP7 was highly positively correlated with tetraspanin subfamily member 6(LHFPL6), matrix Gla protein (MGP), septin 4(SEPTIN4), heat shock protein family B (Small) member 2(HSPB2), actin alpha 2, smooth muscle (ACTA2), layilin (LAYN),necdin, MAGE family member (NDN) and gamma-glutamyltransferase 5 (GGT5) (Fig. 4A-H). The survival map indicated that all 8 genes were risk factors for unfavorable survival of GC, among which five genes showed statistically significant relationships with survival (Fig. 4I). Overall survival analysis further confirmed that high expression levels of LHFPL6, SEPTIN4, HSPB2, LAYN and GGT5 were associated with poor prognosis of GC (Fig. 4J-N).
To explore the potential biological function of genes coexpressed with IGFBP7, top 200 genes were selected to conduct the enrichment analysis. The GO biological process (BP) analysis showed that the terms extracellular structure organization, extracellular matrix organization, muscle system process, ameboidal-type cell migration and regulation of cellular response to growth factor stimulus were significantly enriched (Figure S2A). The GO term cellular component (CC) analysis showed that the terms collagen-containing extracellular matrix, contractile fiber and extracellular matrix component were significantly enriched (Figure S2B). The molecular function (MF) analysis showed that the terms extracellular matrix structural constituent, glycosaminoglycan binding and collagen binding were mainly enriched (Figure S2C). KEGG pathway analysis showed that vascular smooth muscle contraction was significantly enriched (Figure S2D). Overall, the enrichment analysis indicated that IGFBP7 and its coexpressed genes may be involved in extracellular matrix- related signaling processes.
GSEA identified IGFBP7-related pathways
To analyze the possible biological pathways regulated by IGFBP7 in GC, we conducted GSEA between high and low IGFBP7 expression groups based on the TCGA-STAD dataset. A total of 22 pathways were significantly enriched in the IGFBP7 high expression phenotype (listed in Table S2). The main results showed that the terms cytokine-cytokine receptor interaction (Fig. 5A); calcium signaling pathway (Fig. 5B); vascular smooth muscle contraction (Fig. 5C); cell adhesion related terms such as ECM receptor interaction(Fig. 5D), cell adhesion molecules cams (Fig. 5E) and focal adhesion (Fig. 5F); and immune cell-related terms such as hematopoietic cell lineage(Fig. 5G), complement coagulation cascades(Fig. 5H) and leukocyte transendothelial migration(Fig. 5I) were significantly enriched. Other enriched terms, such as Hedgehog signaling pathway, gap junction, regulation of actin cytoskeleton, MAPK signaling pathway, JAK-STAT signaling pathway are listed in Table S2.
IGFBP7 expression correlated with the infiltration levels of immune cells in GC
As the enrichment analysis above indicated that cytokine-cytokine receptor interactions and immune cell related pathways were noticeably enriched, we wondered that whether immune cell infiltration was involved in the pathogenic role of IGFBP7 in GC. Therefore, we explored the relationship between IGFBP7 expression and infiltrating immune cells in GC using the TIMER database. The results showed that high IGFBP7 expression had the most significant correlation with macrophages (Cor = 0.696, P = 6.97e-55), followed by dendritic cells (Cor = 0.494, P = 3.43e-24), CD4 + T cells (Cor = 0.433, P = 3.66e-18), CD8 + T cells (Cor = 0.312, P = 8.37e-10) and neutrophils (Cor = 0.301, P = 3.50e-09) (Fig. 6). In addition, we also analyzed the correlations between IGFBP7 expression and immune markers of tumor associated macrophages (TAMs), M1 macrophages, dendritic cells, T cells and neutrophils. The results revealed that IGFBP7 expression had a strong correlation with gene markers of TAMs, DCs, Tregs, Th1, Th2 cells and neutrophils (Table 3). However, the expression of NOS2, IRF5, PTGS2 and CD68 in M1 macrophages showed a relatively weak correlation with IGFBP7 expression (Table 3). Overall, the results demonstrated that IGFBP7 had a strong relationship with immune cell infiltration in GC.
Table 3
Correlation analysis between IGFBP7 mRNA expression and gene markers of immune cells in gastric cancer
Immune cells | Gene marker | Correlation coefficient | P value |
TAM(M2) | CCL2 | 0.597 | 0 |
| IL10 | 0.402 | 1.53E-17 |
| CD206 | 0.392 | 0 |
| CD163 | 0.41 | 4.52E-35 |
| VSIG4 | 0.488 | 5.44E-51 |
| CSF1R | 0.564 | 0 |
| FCGR2A | 0.453 | 0 |
M1 | NOS2 | -0.067 | 1.73E-01 |
| IRF5 | 0.255 | 1.54E-07 |
| PTGS2 | 0.191 | 8.93E-05 |
| CD68 | 0.238 | 1.06E-06 |
DCs | ITGAX | 0.4 | 0 |
| CD1C | 0.511 | 5.88E-29 |
| NRP1 | 0.661 | 0 |
| THBD | 0.587 | 9.92E-40 |
Treg | FOXP3 | 0.345 | 6.91E-13 |
| STAT5B | 0.455 | 0 |
| TGFB1 | 0.611 | 8.77E-44 |
Th1 | STAT4 | 0.358 | 6.97E-14 |
| TBX21 | 0.303 | 3.07E-10 |
| CD4 | 0.494 | 0 |
| TNF | 0.101 | 3.98E-02 |
Th2 | GATA3 | 0.427 | 0 |
| CXCR4 | 0.504 | 4.58E-28 |
| CCR8 | 0.39 | 1.45E-16 |
| STAT5A | 0.336 | 1.93E-12 |
Neutrophils | MPO | 0.355 | 8.92E-14 |
| ITGAM | 0.449 | 0 |
| CCR7 | 0.438 | 0 |
| CD16(FCGR3A) | 0.372 | 4.81E-15 |
| CD32(FCG2A) | 0.453 | 0 |