mRNA level of SYT4 in cancers
Firstly, we used the Oncomine database to explore mRNA expression levels of SYT4 in different tumors (Fig. 1A). The result suggested that mRNA expression of SYT4 was higher in the lung tumor tissues than the normal lung tissues. In contrast, the mRNA expressions of SYT4 were lower in the brain and nervous system cancer, colorectal, esophageal, gastric, and prostate cancer, as well as in sarcoma. Supplemental Table 1 explicitly presented the mRNA expression levels of SYT4 in tumors according to different researches.
Further, we used the TIMER database to explore the expression levels of SYT4 in different cancers (Fig. 1B). We found that a significant difference of the expression levels of SYT4 between the cancer tissues and the normal tissues in the following cancers: bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), stomach adenocarcinoma (STAD), thyroid carcinoma (THCA), as well as uterine corpus endometrial carcinoma (UCEC).
Prognostic Significance Of SYT4 In Different Cancers
We used the gene chip data which were derived from the Kaplan-Meier plotter database to explore the association between SYT4 expressions and the survival of breast, lung, gastric and ovarian cancer patients. The results were shown in Fig. 2. For patients with gastric cancer, SYT4 was associated with an unfavorable prognosis [Overall survival (OS): HR = 1.39(1.12–1.73), log-rank P = 0.0025; Progression-free survival (PFS): HR = 1.31(1.03–1.67), log-rank P = 0.025]. For breast cancer patients, SYT4 was beneficial for patients’ recurrence free survival (RFS) [HR = 0.76(0.65–0.88), log-rank P = 0.00042] but had no significant impact on the OS [HR = 0.74(0.54–1.02), log-rank P = 0.065]. While SYT4 did not affect the OS and PFS of patients with lung cancer [OS: HR = 1.02(0.86–1.20), log-rank P = 0.84; PFS: HR = 1.12(0.86–1.47), log-rank P = 0.40] and ovarian cancer [OS: HR = 1.01(0.82–1.24), log-rank P = 0.93; PFS: HR = 1.07(0.89–1.29), log-rank P = 0.46].
After the exploration of SYT4 in the Kaplan-Meier plotter database, we analyzed the impact of SYT4 on the prognosis of different cancers by analyzing the RNA sequencing data which were from TCGA database through GEPIA2. (Supplemental Fig. 1). The results showed the impacts of SYT4 on the survival of LGG and STAD were consistency no matter the exploration of OS or disease-free survival (DFS). The expression levels of SYT4 were related to a poor prognosis in patients with STAD (OS: HR = 1.60, log-rank P = 0.006; DFS: HR = 1.80, log-rank P = 0.0041). In contrast, the expression levels of SYT4 were correlated with a good prognosis in LGG patients (OS: HR = 0.53, log-rank P = 0.00047; DFS: HR = 0.58, log-rank P = 6e-04).
To further explore the correlation between the expression levels of SYT4 and the survival of LGG patients, we verified it in the CGGA database (Supplemental Fig. 2). In the mRNAseq_325 dataset, the result suggested that a significant correlation between the expression level of SYT4 and all primary gliomas patients’ survival, as well as the patients with WHO grade II and III, but there was no correlation with the fourth-grade patients’ prognosis. Similarly, In the mRNAseq_693 dataset, the result indicated a correlation between the expression level of SYT4 and all primary gliomas patients’ survival, as well as the patients with WHO grade III, but there was no correlation with the grade II and IV patients. These results suggested the prognostic value of SYT4 in LGG and STAD. Among them, SYT4 was beneficial for the prognosis of LGG patients. In contrast, SYT4 was detrimental to the survival of STAD patients.
The expression of SYT4 has an impact on the survival of gastric patients with lymphatic metastasis
In order to explore the mechanism in which the expression level of SYT4 affected the survival of gastric cancer patients, we used the Kaplan-Meier plotter database to explore the association between the expression levels of SYT4 and clinical factors of gastric cancer patients (Table 1). We conducted a stratified analysis of clinical factors for OS and PFS, such as gender, AJCC stage, T stage, N stage, as well as M stage. In terms of gender, the expression level of SYT4 was related to an unfavorable prognosis of OS in both male [HR = 1.49(1.11–2.01), log-rank P = 0.0082] and female[HR = 1.89(1.22–2.93), log-rank P = 0.0039], and an unfavorable prognosis of PFS in female patients [HR = 1.56(1.02–2.38), log-rank P = 0.038]. Besides, a significant correlation was also shown between the expression level of SYT4 and the lymphatic metastasis of patients. We did not find a significant association between the expression level of SYT4 and the survival of gastric cancer patients without lymph node metastasis [OS: HR = 1.10(0.47–2.57), log-rank P = 0.83; PFS: HR = 1.16(0.50–2.70), log-rank P = 0.73]. However, there was a significantly correlation between the expression level of SYT4 and the survival of gastric cancer patients with N1 stage [OS: HR = 1.85(1.21–2.81), log-rank P = 0.0036; PFS: HR = 1.90(1.27–2.83), log-rank P = 0.0014]. Moreover, compared with patients without lymph node metastasis, as long as there was lymph node metastasis in gastric cancer patients, their OS [HR = 1.31(1.01–1.70), log-rank P = 0.045]and PFS [HR = 1.32(1.02–1.70), log-rank P = 0.031] were correlated with the expression level of SYT4. It was suggested that the expression level of SYT4 might further affect the prognosis of gastric cancer patients via affecting lymph node metastasis.
Table 1
Correlation of SYT4 mRNA expression and clinical factors in gastric cancer.
| Overall survival (n = 881) | Progression-free survival (n = 645) |
| N | HR | P-value | N | HR | P-value |
Sex | | | | | | |
Female | 187 | 1.89(1.22–2.93) | 0.0039 | 179 | 1.56(1.02–2.38) | 0.038 |
Male | 349 | 1.49(1.11–2.01) | 0.0082 | 341 | 1.30(0.97–1.74) | 0.073 |
Stage | | | | | | |
1 | 62 | 0.66(0.22–2.01) | 0.46 | 60 | 0.69(0.23–2.11) | 0.52 |
2 | 135 | 1.77(0.93–3.38) | 0.077 | 131 | 1.79(0.97–3.31) | 0.061 |
3 | 197 | 1.26(0.87–1.84) | 0.22 | 186 | 1.21(0.84–1.78) | 0.29 |
4 | 140 | 1.20(0.81–1.78) | 0.46 | 141 | 1.03(0.70–1.51) | 0.89 |
Stage T | | | | | | |
2 | 241 | 1.45(0.94–2.21) | 0.088 | 239 | 1.26(0.83–1.90) | 0.27 |
3 | 204 | 1.01(0.71–1.42) | 0.97 | 204 | 1.11(0.80–1.55) | 0.54 |
4 | 38 | 1.59(0.70–3.65) | 0.27 | 39 | 0.92(0.43–1.98) | 0.84 |
Stage N | | | | | | |
0 | 74 | 1.10(0.47–2.57) | 0.83 | 72 | 1.16(0.50–2.70) | 0.73 |
1 | 225 | 1.85(1.21–2.81) | 0.0036 | 222 | 1.90(1.27–2.83) | 0.0014 |
2 | 121 | 0.86(0.55–1.35) | 0.52 | 125 | 0.82(0.53–1.25) | 0.35 |
3 | 76 | 1.26(0.74–2.13) | 0.4 | 76 | 1.04(0.62–1.76) | 0.88 |
1 + 2 + 3 | 422 | 1.31(1.01–1.70) | 0.045 | 423 | 1.32(1.02–1.70) | 0.031 |
Stage M | | | | | | |
0 | 444 | 1.32(1.00-1.74) | 0.052 | 443 | 1.33(1.02–1.73) | 0.038 |
1 | 56 | 1.44(0.81–2.56) | 0.21 | 56 | 1.10(0.61–1.96) | 0.76 |
SYT4 expression is related to the level of immune infiltration in gastric cancer and low-grade brain glioma
Among various factors affecting survival and lymph node metastasis of cancer patients, lymphocyte infiltration is a significant independent predictor[24]. Therefore, we continued to analyze the asscociation between the expression levels of SYT4 and the levels of immune infiltration in 39 types of cancer in the TIMER database (Supplemental Fig. 3). According to the results, we found that tumor purity and the expression levels of SYT4 had significant correlations in 12 cancer types. Similarly, the levels infiltration of B lymphocytes, CD4 + T lymphocytes, CD8 + T lymphocytes, macrophages, neutrophils, and dendritic cells had significant correlations with the expression levels of SYT4 in 11, 14, 10, 19, 11 and 13 types of cancer, respectively.
Based on the findings in GEPIA2, Kaplan Meier plotter and CGGA, we focused on cancer types in which the expression level of SYT4 was negatively correlated with tumor purity in TIMER and had significant correlation with prognosis of patients in GEPIA2 and Kaplan Meier plotter, including STAD and LGG (Fig. 3). The BRAC was selected as a control. It was worth noting that the expression level of SYT4 was negatively related to the prognosis of STAD, but had a positive association with the infiltration of immune cells. We found that the expression level of SYT4 in STAD patients was negatively related to tumor purity (cor = − 0.172, P = 7.75e-04), but was positively associated with the following immune cell infiltration: B cells (cor = 0.192, P = 2.09e-04), CD4 + T cells (cor = 0.385, P = 2.38e-14), CD8 + T cells (cor = 0.122, P = 1.82e-02), macrophages (cor = 0.385, P = 1.72e-14), and dendritic cells (cor = 0.207, P = 6.01e-05). However, the expression level of SYT4 was positively related to the prognosis of LGG patients, but negatively associated with the following immune cell infiltration: B cells (cor = − 0.385, P = 6.54e-12), CD4 + T cells (cor = − 0.577, P = 1.34e-43), neutrophils (cor = − 0.375, P = 2.49e-17), macrophages (cor = − 0.505, P = 6.45e-32), and dendritic cells (cor = − 0.478, P = 1.37e-28). While we did not find similar correlations in BRCA. These above results suggested that the reasons why the expression level of SYT4 impacted the prognosis of STAD and LGG patients in the different way probably were that the different relationships between the expression level of SYT4 and the level of immune infiltration in STAD and LGG.
Correlations between the expression levels of SYT4 and markers of immune cells
We analyzed the correlations between the expression levels of SYT4 and immune markers of multiple immune cells in STAD and LGG based on the TIMER and GEPIA databases, whose aim was to further explore potential mechanisms of interaction between SYT4 and various immune infiltrating cells, such as CD8 + T cells, T cells (general), B cells, monocytes, TAMs, M1 / M2 macrophages, neutrophils, natural killer cells, and dendritic cells. Besides, we also performed correlation analysis on the immune marker of the following functional T cells: T helper cells, follicular helper T cell, regulatory T cells, and exhausted T cells. At the same time, its correlation coefficient was adjusted based on tumor purity[25] (Table 2). According to the correlation analysis between the expression levels of 56 immune cell markers and the expression levels of SYT4, we found that the purity-adjusted coefficients of 35 markers were statistically significant in STAD patients, and their purity-adjusted coefficients were all positive. While the purity-adjusted correlation analysis of 46 markers was statistically significant in LGG patients, and most of them were negatively correlated. And only ten markers had statistically significant purity-adjusted correlations with the expression levels of SYT4 in BRCA patients. Besides, we also found significant correlations between the expression levels of markers in monocytes, TAM and M2 macrophages and the expression levels of SYT4 in patients with STAD and LGG, but not in BRCA (Table 2, Fig. 4). In detail, these markers, such as CD115, CCL2, IL10, VSIG4, and MS4A4A, had significantly positive correlations with SYT4 expression levels in STAD (P < 0.0001, Fig. 4A-D). For LGG, the markers, such as CD163 of M2, NOS2, IRF5 and COX2 of M1, and CD86 of monocytes also showed a significant correlation with SYT4 expression levels except for these above markers (P < 0.0001, Fig. 4I-L). However, the expression of SYT4 in BRAC did not show significant correlations with the above markers (Fig. 4E-H). Then, to verify the results, we analyzed the correlation between monocytes, TAMs, M1, M2 macrophages immune markers and the expression levels of SYT4 in STAD, LGG, and BRAC based on the GEPIA2 database. And the results were similar to above those in TIMER (Table 3). What’s more, it is worth noting that the correlations between the expression level of SYT4 and the levels of immune markers were positive and negative in STAD and LGG, respectively. Hence, we probably concluded that the expression levels of SYT4 interacted with various immune cells in STAD and LGG in the opposite way, which affected the prognosis of patients and makes the difference about the survival of STAD and LGG.
Table 2
Correlation analysis between the expression level of SYT4 and markers of immune cells in TIMER.
Dscription | Gene markers | STAD | LGG | BC |
None | Purity | None | Purity | None | Purity |
Cor | p-Value | Cor | p-Value | Cor | p-Value | Cor | p-Value | Cor | p-Value | Cor | p-Value |
CD8 + T cell | CD8A | 0.24 | *** | 0.25 | *** | 0.23 | *** | 0.27 | *** | 0.03 | 3.58E-01 | 0.02 | 4.37E-01 |
| CD8B | 0.21 | *** | 0.23 | *** | 0.02 | 6.44E-01 | 0.03 | 4.57E-01 | 0.01 | 7.51E-01 | 0.01 | 7.50E-01 |
T cell (general) | CD3D | 0.19 | *** | 0.18 | ** | -0.22 | *** | -0.21 | *** | -0.01 | 7.72E-01 | -0.02 | 5.78E-01 |
| CD3E | 0.22 | *** | 0.21 | *** | -0.25 | *** | -0.25 | *** | 0.00 | 9.64E-01 | -0.01 | 8.00E-01 |
| CD2 | 0.21 | *** | 0.20 | *** | -0.25 | *** | -0.24 | *** | -0.01 | 8.24E-01 | -0.01 | 7.07E-01 |
B cell | CD19 | 0.28 | *** | 0.27 | *** | -0.33 | *** | -0.30 | *** | -0.02 | 4.88E-01 | -0.04 | 2.68E-01 |
| CD79A | 0.30 | *** | 0.28 | *** | -0.40 | *** | -0.40 | *** | -0.02 | 4.84E-01 | -0.04 | 1.87E-01 |
Monocyte | CD86 | 0.16 | ** | 0.14 | * | -0.51 | *** | -0.52 | *** | 0.01 | 6.83E-01 | -0.01 | 8.73E-01 |
| CD115(CSFIR) | 0.26 | *** | 0.24 | *** | -0.48 | *** | -0.50 | *** | 0.03 | 3.99E-01 | 0.01 | 7.55E-01 |
TAM | CCL2 | 0.27 | *** | 0.27 | *** | -0.34 | *** | -0.32 | *** | 0.07 | 2.27E-02 | 0.06 | 4.41E-02 |
| IL10 | 0.23 | *** | 0.23 | *** | -0.41 | *** | -0.38 | *** | 0.07 | 1.92E-02 | 0.06 | 5.34E-02 |
M1 Macrophage | INOS(NOS2) | -0.09 | 6.59E-02 | -0.10 | 6.29E-02 | 0.29 | *** | 0.29 | *** | 0.08 | * | 0.07 | 2.63E-02 |
| IRF5 | 0.12 | 1.24E-02 | 0.10 | 4.23E-02 | -0.50 | *** | -0.52 | *** | 0.08 | 1.26E-02 | 0.06 | 5.88E-02 |
| COX2(PTGS2) | 0.13 | * | 0.13 | * | 0.14 | * | 0.18 | *** | 0.13 | *** | 0.14 | *** |
M2 Macrophage | CD163 | 0.20 | *** | 0.18 | ** | -0.39 | *** | -0.36 | *** | 0.07 | 1.67E-02 | 0.06 | 6.48E-02 |
| VSIG4 | 0.20 | *** | 0.20 | *** | -0.54 | *** | -0.53 | *** | 0.04 | 1.63E-01 | 0.03 | 3.01E-01 |
| MS4A4A | 0.24 | *** | 0.24 | *** | -0.54 | *** | -0.53 | *** | 0.08 | * | 0.07 | 2.67E-02 |
Neutrophils | CD66b(CEACAM8) | 0.07 | 1.73E-01 | 0.07 | 1.91E-01 | -0.10 | 2.37E-02 | -0.09 | 6.09E-02 | 0.10 | ** | 0.10 | * |
| CD11b(ITGAM) | 0.18 | ** | 0.16 | * | -0.46 | *** | -0.47 | *** | -0.07 | 3.03E-02 | -0.08 | 1.27E-02 |
| CCR7 | 0.33 | *** | 0.33 | *** | -0.11 | 1.25E-02 | -0.10 | 2.65E-02 | 0.02 | 5.72E-01 | 0.01 | 7.41E-01 |
Natural killer cell | KIR2DL1 | 0.06 | 2.39E-01 | 0.06 | 2.33E-01 | -0.02 | 6.77E-01 | -0.04 | 4.35E-01 | 0.05 | 1.05E-01 | 0.04 | 1.88E-01 |
| KIR2DL3 | 0.07 | 1.40E-01 | 0.05 | 3.58E-01 | -0.12 | * | -0.13 | * | 0.03 | 3.56E-01 | 0.03 | 4.22E-01 |
| KIR2DL4 | -0.04 | 3.61E-01 | -0.05 | 2.95E-01 | -0.33 | *** | -0.33 | *** | 0.00 | 9.55E-01 | -0.02 | 5.96E-01 |
| KIR3DL1 | 0.13 | * | 0.10 | 6.29E-02 | 0.02 | 5.72E-01 | 0.03 | 5.12E-01 | 0.03 | 4.06E-01 | 0.00 | 9.65E-01 |
| KIR3DL2 | 0.10 | 3.82E-02 | 0.08 | 1.16E-01 | -0.14 | * | -0.15 | ** | 0.02 | 4.97E-01 | 0.02 | 4.99E-01 |
| KIR3DL3 | -0.03 | 5.53E-01 | -0.01 | 8.78E-01 | -0.03 | 4.44E-01 | -0.03 | 5.45E-01 | 0.02 | 5.72E-01 | 0.01 | 7.47E-01 |
| KIR2DS4 | -0.02 | 6.94E-01 | -0.04 | 4.12E-01 | -0.10 | 2.07E-02 | -0.10 | 2.75E-02 | 0.02 | 4.91E-01 | 0.01 | 6.99E-01 |
Dendritic cell | HLA-DPB1 | 0.06 | 2.09E-01 | 0.07 | 1.55E-01 | -0.34 | *** | -0.35 | *** | 0.12 | *** | 0.01 | 8.51E-01 |
| HLA-DQB1 | 0.00 | 9.76E-01 | 0.02 | 7.23E-01 | -0.26 | *** | -0.28 | *** | 0.11 | ** | 0.03 | 3.65E-01 |
| HLA-DRA | -0.01 | 8.03E-01 | 0.00 | 9.89E-01 | -0.32 | *** | -0.34 | *** | 0.10 | * | -0.01 | 6.59E-01 |
| HLA-DPA1 | 0.01 | 8.99E-01 | 0.01 | 7.75E-01 | -0.31 | *** | -0.32 | *** | 0.08 | 1.00E-02 | -0.04 | 2.66E-01 |
| BDCA-1(CD1C) | 0.20 | *** | 0.21 | *** | -0.19 | *** | -0.19 | *** | 0.13 | *** | 0.03 | 2.86E-01 |
| BDCA-4(NRP1) | 0.38 | *** | 0.40 | *** | -0.13 | * | -0.10 | 2.62E-02 | 0.19 | *** | 0.13 | *** |
| CD11c(ITGAX) | 0.17 | ** | 0.18 | ** | -0.23 | *** | -0.27 | *** | 0.08 | * | -0.02 | 6.12E-01 |
Th1 | T-bet(TBX21) | 0.09 | 7.70E-02 | 0.10 | 5.91E-02 | -0.22 | *** | -0.20 | *** | 0.11 | ** | 0.00 | 9.71E-01 |
| STAT4 | 0.17 | ** | 0.18 | ** | 0.47 | *** | 0.45 | *** | 0.17 | *** | 0.07 | 3.55E-02 |
| STAT1 | -0.04 | 3.74E-01 | -0.02 | 6.56E-01 | -0.08 | 7.37E-02 | -0.08 | 8.91E-02 | 0.03 | 3.50E-01 | -0.02 | 5.51E-01 |
| IFNG(INF-γ) | -0.14 | * | -0.12 | 2.02E-02 | -0.13 | * | -0.15 | * | 0.05 | 6.90E-02 | -0.03 | 3.79E-01 |
| TNF(TNF-α) | 0.08 | 1.20E-01 | 0.10 | 4.92E-02 | -0.10 | 2.19E-02 | -0.11 | 2.09E-02 | 0.02 | 4.81E-01 | -0.01 | 7.89E-01 |
Th2 | GATA3 | 0.19 | *** | 0.21 | *** | -0.21 | *** | -0.22 | *** | -0.17 | *** | -0.13 | *** |
| STAT6 | 0.09 | 6.78E-02 | 0.11 | 3.74E-02 | 0.15 | ** | 0.10 | 2.35E-02 | 0.07 | 2.97E-02 | 0.05 | 1.32E-01 |
| STAT5A | 0.16 | ** | 0.20 | ** | -0.28 | *** | -0.33 | *** | 0.07 | 1.30E-02 | 0.00 | 9.57E-01 |
| IL13 | 0.12 | 1.30E-02 | 0.13 | 1.11E-02 | 0.15 | ** | 0.14 | * | 0.08 | * | 0.04 | 2.03E-01 |
Tfh | BCL6 | 0.32 | *** | 0.34 | *** | -0.09 | 4.38E-02 | -0.04 | 3.53E-01 | 0.07 | 2.16E-02 | 0.05 | 1.54E-01 |
| IL21 | -0.03 | 5.42E-01 | -0.01 | 7.90E-01 | -0.13 | * | -0.15 | ** | 0.00 | 9.35E-01 | -0.05 | 9.30E-02 |
Th17 | STAT3 | 0.23 | *** | 0.25 | *** | -0.24 | *** | -0.22 | *** | 0.02 | 4.62E-01 | 0.00 | 9.84E-01 |
| IL17A | -0.05 | 3.23E-01 | -0.05 | 3.06E-01 | -0.05 | 2.38E-01 | -0.04 | 4.41E-01 | 0.01 | 6.91E-01 | -0.02 | 4.56E-01 |
Treg | FOXP3 | 0.10 | 4.81E-02 | 0.12 | 2.09E-02 | 0.15 | ** | 0.14 | * | 0.13 | *** | 0.04 | 1.66E-01 |
| CCR8 | 0.14 | * | 0.17 | * | -0.19 | *** | -0.20 | *** | 0.04 | 1.56E-01 | -0.02 | 4.40E-01 |
| STAT5B | 0.33 | *** | 0.34 | *** | 0.00 | 9.21E-01 | 0.07 | 1.06E-01 | 0.00 | 9.58E-01 | -0.03 | 3.03E-01 |
| TGFB1(TGFβ) | 0.38 | *** | 0.38 | *** | -0.22 | *** | -0.26 | *** | 0.19 | *** | 0.10 | * |
T cell exhaustion | PDCD1(PD-L1) | 0.06 | 2.34E-01 | 0.09 | 7.94E-02 | -0.27 | *** | -0.27 | *** | 0.12 | *** | 0.02 | 4.86E-01 |
| CTLA4 | 0.01 | 8.88E-01 | 0.04 | 4.23E-01 | -0.11 | * | -0.11 | 1.79E-02 | 0.07 | 1.71E-02 | -0.02 | 5.58E-01 |
| LAG3 | -0.01 | 9.13E-01 | 0.03 | 6.23E-01 | -0.14 | * | -0.13 | * | 0.04 | 1.66E-01 | -0.01 | 8.03E-01 |
| TIM-3(HAVCR2) | 0.13 | 1.07E-02 | 0.14 | * | -0.29 | *** | -0.35 | *** | 0.06 | 4.89E-02 | -0.03 | 4.30E-01 |
| GZMB | -0.07 | 1.64E-01 | -0.05 | 3.09E-01 | -0.02 | 5.89E-01 | -0.03 | 4.85E-01 | 0.08 | * | -0.01 | 7.38E-01 |
STAD: Stomach adenocarcinoma; LGG: Brain lower grade glioma; BC: Breast cancer; TAM: tumour-associated macrophage; Th: T helper cell; Tfh: Follicular helper T cell; Treg: regulatory T cell; Cor: R value of Spearman’s correlation; None: correlation without adjustment; Purity: correlation adjusted by purity. *p < .01; **p < .001; ***p < .0001. |
Table 3
Correlation analysis between the expression level of SYT4 and markers of monocytes, TAM, M1 and M2 in GEPIA.
Dscription | Gene markers | STAD | BRCA | LGG |
Tumor | Tumor | Tumor |
Cor | p-Value | Cor | p-Value | Cor | p-Value |
Monocyte | CD86 | 0.16 | * | 0.01 | 0.74 | -0.48 | *** |
| CD115(CSFIR) | 0.25 | *** | 0.027 | 0.37 | -0.45 | *** |
TAM | CCL2 | 0.25 | *** | 0.055 | 0.07 | -0.32 | *** |
| IL10 | 0.20 | *** | 0.099 | * | -0.36 | *** |
M1 | NOS2 | -0.07 | 0.16 | 0.073 | 0.016 | 0.31 | *** |
| IRF5 | 0.11 | 0.027 | 0.10 | ** | -0.48 | *** |
| COX2(PTGS2) | 0.16 | * | 0.12 | *** | 0.14 | * |
M2 | CD163 | 0.15 | * | 0.056 | 0.064 | -0.39 | *** |
| VSIG4 | 0.18 | ** | 0.045 | 0.14 | -0.51 | *** |
| MS4A4A | 0.22 | *** | 0.09 | * | -0.52 | *** |
STAD: Stomach adenocarcinoma; BRCA: Breast invasive carcinoma; LGG: Brain lower grade glioma; TAM: tumour-associated macrophage; Cor: R value of Spearman’s correlation; *p < 0.01; **p < 0.001; ***p < 0.0001. |