CXCL9 Transcriptional Levels in a Variety of Tumors
The Oncomine database analyzed the levels different of CXCL9 mRNA in various tumors and their normal tissues. It found out that CXCL9 expression was elevated in the following cancers: gastric, breast, bladder, cervical, head and neck, colorectal, kidney, leukemia, liver, lymphoma, and prostate (Figure 1A). using the TIMER database, we further assessed the CXCL9 expression difference in various cancer. Results show that CXCL9 expression was elevated in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), colon adenocarcinoma (COAD), cholangiocarcinoma (CHOL), head and neck cancer (HNSC), kidney renal clear cell carcinoma (KIRC), liver hepatocellular carcinoma (LIHC), esophageal carcinoma (ESCA), lung squamous (LUSC), lung adenocarcinoma (LUAD), rectum adenocarcinoma (READ), prostate adenocarcinoma (PRAD), uterine corpus endometrial carcinoma (UCEC), and stomach adenocarcinoma (STAD) than their normal tissues. instead, CXCL9 expression was low in thyroid carcinoma (THCA), kidney chromophobe (KICH), and kidney renal papillary (KIRP) than their normal tissues. (Figure 1B).
The Prognostic value of CXCL9 in human cancers
Next, Using KM plotter database to analyze whether the CXCL9 expression level impacts cancer patient's prognosis. The result shows that high CXCL9 level corresponded with better prognosis in OV (OS HR = 0.78, P = 0.0017; PFS HR = 0.85, P = 0.015), GC patients (OS HR = 0.55, P = 1.1e-08; PFS HR = 0.58, 95% CI = 0.46-0.72, P = 7.6e-07), Breast patients (OS HR = 0.88, P = 0.0011; RFS HR = 0.83, P = 0.0039; PPS HR = 0.74, P = 0.022, DMFS HR = 0.68, P = 0.0011), Lung patients (PFS HR = 0.84, P = 0.015) and Liver patient (OS HR = 0.66, P = 0.027; PFS HR = 0.65, P = 0.0083) (Figure 2(A-H, G-L)). Yet, the CXCL9 expression was no correlation with OS in Lung cancer (Figure 2I). These results indicated that the CXCL9 expression impacts breast, liver, ovarian, and gastric cancer prognosis.
CXCL9 expression impact the clinical characteristic of OV and GC patient
Next, we are again using the Kaplan-Meier Plotter database to investigate whether CXCL9 expression affects the clinical characteristics of OV and GC patients. (Table 1). In stage 3 ovarian cancer patients, low CXCL9 expression show to be associated with a worse OS and PFS (OS HR = 0.73, P = 0.0005, PFS HR = 0.71, P = 5.1E-05). Overexpression CXCL9 was relationship with better OS and RFS of patients treated with Taxol, platin, and platin + Taxol chemotherapy. In stage 1-3 gastric cancer patients, high CXCL9 expression show to be associated with a better correlation with a better OS and PFS (OS HR = 0.1, P = 0.0066, PFS HR = 0.14, P = 0.027; OS HR = 0.45, P = 0.011, PFS HR = 0.44, P = 0.01; OS HR = 0.52, P = 2e-04, PFS HR = 0.53, P = 0.002). Besides, the gastric patients at the N0-2 stage also showed an obvious correlation with CXCL9 expression. (OS HR = 0.19, P = 0.011, PFS HR = 0.2, P = 0.014; OS HR = 0.55, P = 0.0061, PFS HR = 0.53, P = 0.0028; OS HR = 0.36, P = 0.0011, PFS HR = 0.42, P = 0.0035) (Table 2). These findings show that CXCL9 expression has prognostic signification in OV and GC patients according to their clinical characteristics.
CXCL9 expression impacts the immune cell infiltration from ovarian and gastric cancer.
Cancer patients' survival times are affected by tumor-infiltrating lymphocytes. So we analyzed the correlation between the 39 cancer in TIMER and the CXCL9 expression level. The analyzed result indicated that CXCL9 expression associates with tumor purity in 27 types of cancer. besides, CXCL9 expression obviously association with the infiltration levels of immune cell. Such as CD4+ (26 types cancer), B cell (23 types cancer), CD8+T cells (32 types cancer), Macrophage cells (12 types cancer), Neutrophil cell (32 types cancer) and Dendritic cell (34 types cancer) (supplementary Figure 1). In OV and GC, high CXCL9 transcription was association to better prognosis and elevated immune cell infiltration levels. High CXCL9 expression was found to be obviously positive associated with the infiltration level of immune cell including CD4+ (r = 0.268, P = 2.37e-09), B cells (r = 0.199, P = 1.14e-05), macrophages (r = 0.025, p = 5.79e-01), CD8+ T cells (r = 0.401, P = 5.15e-20), neutrophils (r = 0.338, P = 2.72e-14), and DCs (r = 0.39, P = 7.42e-14), in OV tissues (Figure 3A). Similar, in Gastric cancer has been found to be obviously correlation with better prognosis and elevated immune cell infiltration levels. Immune cell including CD4+ T cells (r = 0.131, P = 1. 20E-02) CD8+ T cells (r = 0.595, P = 8.33e-37), neutrophils (r = 0.521, P = 3.60e-27), macrophages (r = 0.179, P = 5.34e-04), and DCs (r = 0.551, P = 8.53e-31). Interestingly, Only B cells in GC had a negative association (r = -0.209, P = 5.44e-05) (Figure 3B). The results clearly indicate that CXCL9 can recruit immune cells in the OV and GC microenvironment.
CXCL9 Expression and Immune Marker Association Analyze
The immune cell that infiltration level obviously correlation with the CXCL9 expression in OV and GC by KM plotter were further analyzed in TIMER and GEPIA database (Figure 4, Table3 and Table4). we found markers of immune cells in OV was to be strongly correlated with CXCL9 expression, including CD8+ T cell marker, CD8A (r = 0.739; P =2.78e-44), CD8B (r = 0.585; P = 2.77e-24), T cell marker, CD3D (R = 0.83; P = 1.56e-64), CD3E (R = 0.842; P = 4.47e-68), CD2 (r = 0.852; P = 1.73e-71), B cell marker, CD79A (r = 0.584; P = 3.49e-24), Monocyte marker, CD86 (r = 0.512, P = 4.56e-18), TAM marker, CD68 (r = 0.488; P = 2.73e-16), M2 macrophage marker, MS4A4A (r = 0.446, P = 1.37e-13) Neutrophils marker,CCR7 (r = 0.602, P = 6.66e-26), Nature killer cell marker, KIR2DL4 (r = 0.482; P = 7.41e-16), Dendritic cell marker, HLA-DPB1 (r = 0.507; P = 1.12e-17), HLA-DRA (r = 0.447; P = 1.49e-15), HLA-DPA1 (r = 0.512, P = 4.74e-18) and CD11C (r = 0.421; P = 4.09e-12). Besides, we also found markers of immune cells in GC was to be strongly correlated with CXCL9 expression, including CD8+ T cell marker, CD8A (r = 0.737; P = 4.56e-66), CD8B (r = 0.604; P = 5.27e-39), T cell marker, CD3D (r = 0.707; P = 9.99e-59), CD3E (r = 0.706; P = 1.82e-58), CD2 (r = 0.745; P = 2.97e-68), Monocyte marker, CD86 (r = 0.643, P = 1.27e-45), CD115 (r = 0.499; P = 2.83e-25), TAM marker, IL10 (r = 0.404; P = 2.57e-16), M2 macrophage marker, CD163 (r = 0.521; P = 1.02e-27),VSIG4 (r = 0.465; P = 1.10e-21), MS4A4A (r = 0.523; P = 6.11e-28), Neutrophils marker, CD11b (r = 0.411; P = 7.33e-17), CCR7 (r = 0.412, P = 5.96e-17), Nature killer cell marker, KIR2DL1 (r = 0.412; P = 5.96e-17), KIR2DL4 (r = 0.549; P = 3.34e-31), KIR3DL1 (r = 0.443; P = 1.08e-19), KIR3DL2 (r = 0.437; P = 4.10e-19),Dendritic cell marker, HLA-DPB1 (r = 0.644; P = 1.02e-45), HLA-DQB1 (0.508; P = 3.06e-26), HLA-DRA (r = 0.637; p = 1.90e-44), HLA-DPA1 (r = 0.623; P = 1.90e-44) and CD11C (r = 0.497; P = 5.24e-25) (Figure 4 and Table3). GEPIA analysis resulted have consistent with TIMER (Table 4). These results indicated that CXCL9 expression correlation with infiltration of immune cells in OV and GC.