TIMP2 is associated with prognosis and immune infiltrates of gastric and colon cancer

doi:10.21203/rs.3.rs-1593360/v1

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TIMP2 is associated with prognosis and immune infiltrates of gastric and colon cancer

https://doi.org/10.21203/rs.3.rs-1593360/v1

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Tissue inhibitor of metalloproteinase-2 (TIMP2) is an inhibitor among the tissue inhibitors of metalloproteinase (TIMP) family members, is associated with the progression of a variety of tumors. However, the association of TIMP2 with cancer prognosis and tumor-infiltrating lymphocytes remains unclear. TIMP2 expression was analyzed by Tumor Immune Estimation Resource (TIMER), TNMplot, Gene Expression Profiling Interactive Analysis (GEPIA) database and 50 paired gastric cancer tissues. We evaluated the influence of TIMP2 on clinical prognosis using Kaplan-Meier plotter, the PrognoScan database, GEPIA and TCGA data. The correlation of TIMP2 with tumor immune infiltrates and with the set of gene markers of immune infiltrates was investigated by TIMER and GEPIA. TIMP2 is highly expressed in gastric cancer and low expressed in colon cancer. High TIMP2 expression was significantly correlated with poor overall survival (OS, hazard ratio [HR] = 1.38, 95% confidence interval [CI]: [1.16–1.63]; P = 0.0002) and progression-free survival (PFS, HR = 1.39, 95% CI: [1.14–1.7]; P = 0.0012) in gastric cancers. Specifically, high TIMP2 expression was associated with poorer OS and PFS, but not with OS and PFS in stage 1 (OS HR = 1.96, P = 0.29; PFS HR = 0.43, P = 0.19) and stage 2 (OS HR = 1.59, P = 0.12; PFS HR = 1.47, P = 0.2) and stage N0 patients (OS HR = 1.6, P = 0.35; PFS HR = 1.56, P = 0.38) of gastric cancer patients. There was a significant positive correlation between TIMP2 expression and different type of immune cells, including CD4 + T cells, CD8 + T cells, macrophages, Neutrophils, and dendritic cells in stomach adenocarcinoma (STAD) and colon adenocarcinoma (COAD). Moreover, TIMP2 expression was strongly correlated with different sets of immune markers. These results suggest that TIMP2 is associated with prognosis and level of immune infiltrating in a variety of cancers, especially colon and gastric cancer patients. Moreover, expression of TIMP2 potentially contributes to regulation of tumor-associated macrophages (TAMs), dendritic cells, T cell exhaustion and Tregs in colon and gastric cancer. These findings suggest that TIMP2 may serve as a prognostic biomarker for predicting prognosis and immune infiltration in gastric and colon cancer.

TIMP2

immune infiltration

prognosis

gastric and colon cancer

With the development of medical technology, cancer has become one of the main factors threatening human health. In 2020, an estimated 19.3 million new cancer cases and almost 10.0 million cancer deaths. The incidence of colorectal cancer and gastric cancer was 10% and 5.6%, the third and fifth highest in the total, respectively(1). Immunology-related mechanisms play a significant role in the progression of gastrointestinal tumors, and immunotherapy strategy is a promising approach for the treatment of gastrointestinal tumors(2). Using cytotoxic T lymphocyte associated antigen 4 (CTLA4), representational immunotherapies such as programmed death-1 (PD-1) and programmed death ligand-1 (PD-L1) inhibitors have shown good efficacy in a variety of tumors, such as non-small cell lung cancer and melanoma(3, 4). However, at present, the efficacy of anti-CTLA4 in the clinical treatment of gastric cancer and colorectal cancer is not very significant, and anti-PD-1 and anti-PD-L1 are only partially effective(5–7). In recent years, more and more studies have found that tumor-infiltrating lymphocytes, such as tumor-associated macrophages (TAMs) and tumor-infiltrating neutrophils (TINS), are one of the factors that influence the prognosis and efficacy of chemotherapy and immunotherapy for gastric cancer and colorectal cancer(8, 9). Therefore, to elucidate the immunophenotype of tumor-immune interaction and to find new immune-related therapeutic targets in colorectal cancer and gastric cancer are the problems that need to be solved.

Tissue inhibitor of metalloproteinase-2 (TIMP2) is a unique inhibitor among the tissue inhibitors of metalloproteinase (TIMP) family members. It inhibits the proteolytic activity of matrix metalloproteinase 2 (MMP2), a member of the protease family, which is mainly involved in the degradation of extracellular matrix (ECM)(10). TIMP2 has been reported to interact with multiple membrane receptors, such as integrin α3β15, insulin-like growth factor 1 receptor (IGFR1) and membrane-bound MMP1, 4, 6(10–12), which play a role in homeostasis regulation at the interface with ECM. Imbalanced TIMP2 expression has been found to be associated with different types of cancer and metastasis, and in several cases it has been shown to be associated with poor patient outcomes(13), such as breast cancer(14), ovarian cancer(15) and gastric cancer(16).

Infiltrating immune cells account for a large proportion of the cells contained in the tumor microenvironment (TME)(17). In addition to macrophages, TME contains almost all types of immune cells, such as B cells, CD8 + T cells, CD4 + T cells, neutrophils, natural killer cells (NK) and dendritic cells (DC), some of these immune cells are closely involved in tumor progression(17). In recent years, immunotherapies have been developed to reactivate the adaptive and innate immune system and create a powerful anti-tumor immune response. For example, CTLA4, PD-1, and PD-L1 inhibitors mentioned above have been found to have significant antitumor effects against malignant melanoma and non-small cell lung cancer(18, 19). However, only a small number of patients with certain cancer types respond well to current immunotherapies. Therefore, there is a need to explore more potential targets for immunotherapy.

In this study, public databases such as PrognoScan and Kaplan-Meier Plotter were used to comprehensively analyzed TIMP2 expression and its correlation with prognosis of cancer patients. Subsequently, we analyzed the potential relationship between TIMP2 expression and the level of immune invasion using the TIMER and GEPIA databases. The results of this study suggest that TIMP2 may affect the prognosis of gastric cancer and colon cancer patients through its interaction with infiltrating immune cells.

Patients and tissue samples

Fifty paired gastric cancer tissues and adjacent normal tissues for immunohistochemistry and 5 paired fresh gastric cancer tissues for western blot were collected from Xu Zhou central hospital, Jiangsu, China, between January 2012 and December 2020. All patients had been diagnosed and confirmed with gastric cancer by histology and had not been received chemotherapy or radiation therapy prior to surgery. All experiments were performed according to the principles of the Declaration of Helsinki, and all patients received written informed consent, and this study was approved by the Institutional Ethics Committee of Xu Zhou central hospital.

Immunohistochemistry

The detailed procedures for the immunohistochemical experiments are described above(20), the tissue section was treated with primary antibodies against TIMP2 (sc-21735, working dilution 1: 50, Santa Cruz Biotechnology, Inc., USA).

Western blotting

Total proteins from all tissues were separated on a 10% SDS-PAGE gel and transferred to a polyvinylidene fluoride membrane (Millipore). Then, TBST containing 5% non–fat milk was used to block the cell membrane for 1 h, and it was incubated with anti-TIMP2 (sc-21735, working dilution 1:1000; Santa Cruz Biotechnology, Inc., USA) and GAPDH (sc-365062, working dilution 1:1000; Santa Cruz Biotechnology, Inc. USA). Afterward, the blots were labeled for 1 h with HRP-conjugated secondary antibody, followed by an enhanced chemiluminescence (ECL) system (Image Quant LAS 4000 mini, Pittsburgh, USA) according to the instructions of the manufacturer. All experiments were repeated at least three times. The relative density of bands was quantified using ImageJ (http://rsb.info.nih.gov/ij/) software.

Data mining from public databases

Tumor Immune Estimation Resource (TIMER, https://cistrome.shinyapps.io/timer/) was used to evaluate the expression of TIMP2 in a variety of and to analyze the characteristics of tumor-infiltrating immune cells(21). TNMplot (https://www.tnmplot.com/) and The Gene Expression Profiling Interactive Analysis
(GEPIA) database (http://gepia.cancer-pku.cn/) was used to verify the expression of TIMP2, see the citation for the specific use method and parameter setting of the database(22, 23).

Survival Analysis

We first used the PrognoScan database (http://www.abren.net/PrognoScan/) to analyze the correlation between TIMP2 expression and survival of different tumors(24). The threshold was adjusted to a Cox P-value< 0.05. We then used Kaplan-Meier plotter (http://kmplot. com/analysis/) database to analyze the relationship between TIMP2 expression and survival in gastric, liver, breast, lung, and ovarian cancers. The hazard ratio (HR) with 95% confidence intervals and log-rank P-value were also computed(25).

Immune Infiltration Analysis

We analyzed the expression of TIMP2 in different types of cancer by gene module and its correlation with the abundance of immune infiltration, including B cells, CD4+ T cells and other immune cells, as well as the tumor purity. At last, we assessed the association of TIMP2 with markers of immune cell subsets, including CD8+ T cells, total T cells, B cells, NK cells, DCs, monocytes, tumor-associated macrophages (TAMs), M1 and M2 macrophages, Th2, Tfh cells, Th17, Tregs, and dendritic cells. The significance of the correlation was then reanalyzed using the GEPIA database.

Statistical Analysis

In the TCGA database, patients were divided into two groups according to the mean of TIMP2 mRNA expression: high expression group and low expression group. The correlation between TIMP2 expression and clinicopathological factors was estimated using Fisher’s exact test. All survival curves were generated from the PrognoScan and Kaplan-Meier plotter databases and the results were displayed as HR and P values or COX P values. Spearman correlation and statistical significance were used to evaluate the correlation between TIMP2 expression and tumor immune cells. The strength of the correlation is shown as an R value: 0–0.19, “very weak”; 0.20–0.39, “weak”; 0.40–0.59, “moderate”; 0.60–0.79, “strong”; 0.80–1.00, “very strong.” P<0.05 were considered statistically significant.

The mRNA Expression Levels of TIMP2 in Human Tumors

We first compared mRNA expression level of TIMP2 in different cancers and normal tissues in the TCGA dataset using TIMER database. The result revealed that it expressed at relatively higher levels in Cholangio carcinoma, Head and Neck squamous cell carcinoma, Esophageal carcinoma, Kidney renal papillary cell carcinoma, and low expression in Bladder Urothelial Carcinoma, Breast invasive carcinoma, Colon adenocarcinoma, Kidney Chromophobe, Lung cancer, Prostate adenocarcinoma and Rectum adenocarcinoma (Figure 1A). Similar results were found in the TNMPlot and GEPIA database (Figure 1B and C).

The Correlation Between TIMP2 Expression and Cancer Patient’s Prognosis

We used the PrognoScan database to analyze whether TIMP2 expression was associated with prognosis in cancer patients. TIMP2 expression significantly affects prognosis in 5 cancer types, including colorectal, breast, head and neck, bladder, and ovarian cancers (Figure 2A-J). Two cohorts (GSE17536 and GSE17537) (26) including 177 and 55 colorectal cancer samples with different stages were analyzed, and the results showed that TIMP2 expression was correlated with prognosis (Figure 2E-H). To further investigate the prognostic potential of TIMP2 in different cancers, we evaluated the prognostic value of TIMP2 using the Kaplan-Meier plotter database (Figure 2K-T). The results indicated that high expression of TIMP2 is associated with poor prognosis in gastric cancer (overall survival [OS] hazard ratio [HR] = 1.38, 95% confidence interval [CI]: [1.16–1.63]; P=0.0002) and ovarian cancers (OS HR=1.23, 95% CI [1.08-1.4]; P=0.0013) (Figure 2M and S), and low expression of TIMP2 is association with poor prognosis in lung cancer (OS HR=0.83, 95% CI [0.73-0.94]; P=0.0034) (Figure 2Q). However, TIMP2 expression has less influence on breast cancer and liver cancer (Figures 2K and O). These results suggest the TIMP2 expression has an impact on the prognosis of ovarian, lung and gastric cancer.

The Expression of TIMP2 in Gastric and Colon Cancer Patients

To determine TIMP2 expression in gastric and colon cancer, we analyzed its mRNA expression using the TNMplot database. The results indicated that TIMP2 expression was decreased in colon cancer (Figures 3 A-C) and increased in gastric cancer (Figures 3 D-F). In order to verify the protein level of TIMP2, western blotting was used to detect the protein level in gastric cancer tissues and adjacent tissues of 5 patients with gastric cancer, and the results showed that the expression of TIMP2 in cancer tissues was significantly higher than that in adjacent tissues (Figures 4 A). The expression of TIMP2 protein was next analyzed by immunohistochemical staining in 50 paired gastric cancer tissues and corresponding normal tissues. Similar results were obtained from the assessment of TIMP2 protein expression (Figures 4 B). These results indicate that TIMP2 expression is decreased in colon cancer tissues and its mRNA and protein levels are increased in gastric cancer tissues.

TIMP2 Expression Correlated with Clinicopathological Parameters for Colon and Gastric Cancer Patients

In order to explore the relationship between TIMP2 expression and the clinicopathology of colon and gastric cancer, we first analyzed the correlation between TIMP2 expression and clinicopathological features of colon cancer in the TCGA database. As shown in Table 1, the low expression of TIMP2 is associated with the depth of tumor invasion, lymphatic metastasis, and tumor stage (P=0.037, P=0.001 and P=0.049, respectively). Furthermore, we investigated the correlation between TIMP2 expression and clinicopathological factors of the 50 paired gastric cancer and adjacent normal samples.

The results showed that TIMP2 expression was significantly correlated with Histologic grade in gastric cancer patients (P=0.007, Supplementary Table 1). In order to better understand the correlation of TIMP2 expression in cancer and the potential mechanism, we used Kaplan-Meier plotter database to investigated the relationship between TIMP2 expression and clinical characteristics in patients with gastric cancer. In stage 3 and 4 gastric cancer patients, high TIMP2 expression was associated with poorer OS and PFS, but not with OS and PFS in stage 1 (OS HR=1.96, P= 0.29; PFS HR=0.43, P= 0.19) and stage 2 (OS HR=1.59, P= 0.12; PFS HR=1.47, P= 0.2) and stage N0 patients (OS HR = 1.6, P= 0.35; PFS HR= 1.56, P= 0.38) of gastric cancer patients (Table 2). These results suggest that the expression level of TIMP2 may affect the prognosis of gastric cancer patients with lymph node metastasis.

The Expression of TIMP2 is Associated with Immune Infiltration in Gastric and Colon Cancer

Tumor infiltrate lymphocytes as an independent predictor of sentinel lymph node status and survival for cancer(27-29). Furthermore, we analyzed the relationship between TIMP2 expression and tumor-infiltrating immune cells in gastric cancer and colon cancer in the TIMER database. There was a significant positive correlation between TIMP2 expression and different type of immune cells, including CD4+ T cells (P = 3.62e-30, cor = 0.527), CD8+ T cells (P = 1.00e-09, cor = 0.297), B cells (P = 7.75e-03, cor =0.132), macrophages (P = 1.09e-52, cor = 0.664), Neutrophils (P = 1.18e-36, cor = 0.575), and dendritic cells (P = 1.83e-44, cor = 0.622) in COAD (Figure 5 A). Similarly, there were positive correlations with infiltrating levels of CD4+ T cells (P = 7.50e-13, cor = 0.363), CD8+ T cells (P = 5.45e-04, cor = 0.179), macrophages (P = 6.62e-53, cor = 0.687), Neutrophils (P = 1.99e-05, cor = 0.288), and dendritic cells (P = 1.67e-18, cor = 0.434) in STAD (Figure 5 A). In addition, TIMP2 expression has negative correlations with tumor purity in COAD (P = 4.60e-20, cor = -0.433) and STAD (P = 2.85e-03, cor = -0.153). Next, we analyzed the effect of TIMP2 expression and tumor-infiltrating immune cells on patient survival in COAD and STAD. As shown in Figure 5 B, the immune infiltration of tumor cells had no significant effect on the survival rate of COAD patients. However, high expression of TIMP2 in CD4+ T cells, macrophages and Neutrophils lead to a poor prognosis in STAD patients (P=0.035, P=0.002 and P=0.046, respectively). In addition, we found that several immune cell infiltration levels appeared to be associated with TIMP2 copy numbers changes, including B cells, CD8+T cells, neutrophils, and dendritic cells, especially in STAD (Figure 5 C). These results indicate that TIMP2 expression plays an important role in tumor immune cell infiltration.

Correlation Between TIMP2 Expression and Immune Markers

To further investigate the potential relationship between TIMP2 expression and immune infiltrating cells in STAD and COAD, we analyzed the correlations between TIMP2 and immune markers of various immune cells in the TIMER and GEPIA databases. These immune cell markers mainly include CD8+ T cells, T cells (general), B cells, monocytes, TAMs, M1 and M2 macrophages, neutrophils, NK cells and Dendritic cell. In addition, we also analyzed T cells with different functions, such as Th1 cells, Th2 cells, Tfh cells, Th17 cells, Treg cells and exhausted T cells. After adjusting for correlation by purity, the results showed that the expression level of TIMP2 was significantly correlated with the majority of immune marker sets in various immune cells and different T cells in STAD and COAD (Table 3).

According to the results in Table 3, the expression levels of most monocyte markers, TAMs and M2 macrophages and Dendritic cell are strongly correlated with the expression of TIMP2 in STAD and COAD. Specifically, we showed CD86, CSF1R of Monocyte, CCL2, CD68, IL10 of TAMs, CD163, VSIG4 and MS4A4A of M2 phenotype, HLA-DPB1, HLA-DQB1, HLA-DRA, HLA-DPA1, CD1C, NRP1 and ITGAX of Dendritic cell are significantly correlate with TIMP2 expression in STAD and COAD (P <0.001, Figure 6 A and B). Then, we further analyzed the correlation between TIMP2 expression and the above mononuclear markers and TAMs in STAD and COAD by GEPIA database. In COAD, the correlation between TIMP2 and mononuclear markers and TAM is similar to that of TIMER. In STAD, the correlation between TIMP2 and Dendritic cell are slightly different from those of TIMER (Supplementary Table 2). These results suggest that TIMP2 may regulate macrophage polarization, but there is no close relationship between TIMP2 and Dendritic cell infiltration in STAD and COAD.

TIMP2 is a representative of the tissue inhibitor family of metalloproteinases. TIMP2 was initially found to inhibit cell proliferation and migration in vitro by inhibiting the function of MMPs. Abnormal expression of TIMP2 can affect many cancers, including gastric and colon cancer. Wang et al determined the expression of TIMP2 in a colorectal cancer tissue microarray by immunohistochemistry and found that lower TIMP2 expression in cancer tissues was correlated with poorer overall survival, and TIMP2 expression was independent prognostic factors for colorectal cancer patients(30). The results of Wang et al. identified TIMP2 as a new candidate biomarker for poor prognosis in gastric cancer patients and revealed the potential function of TIMP2 and the potential mechanism of gastric cancer progression (31). These results suggest that abnormally expressed TIMP2 plays a potential role in the biological behavior of gastric and colon cancer.

At present study, we assessed the expression of TIMP2 in different types of cancer using TIMER, TNMplot and GEPIA database. In many types of cancers, TIMP2 is differentially expressed in tumors and corresponding paracancerous tissues. Based on TIMER database, we found that compared with the normal tissue, TIMP2 in CHOL, HNSC and KIRP high expression, and some data sets show that in BLCA BRCA, COAD, KICH, LUAD, LUSC, PRAD, READ and UCEC in low levels (Fig. 1A). And, analysis of the TNMplot data showed that TIMP2expression was higher in Kidney renal papillary cell carcinoma, Pancreatic adenocarcinoma, skin cancer and gastric cancer, but lower expression in Adrenocortical carcinoma, Bladder Urothelial Carcinoma, breast cancer, colon cancer, Lung adenocarcinoma, Lung squamous cell carcinoma, Ovarian serous cystadenocarcinoma, Prostate adenocarcinoma, Rectum adenocarcinoma, Kidney Chromophobe, Testicular Germ Cell Tumors, Thyroid carcinoma, Uterine Corpus Endometrial Carcinoma and Uterine Carcinosarcoma, compared with normal adjacent tissues (Fig. 1B). Similar results were found in the GEPIA database (Fig. 1C). Furthermore, analyses from Prognoscan and Kaplan-Meier Plotter showed that differential expression of TIMP2 was associated with poor prognosis in colorectal, gastric, head and neck, lung and ovarian cancers (Fig. 2). In addition, low TIMP2 expression is associated with the depth of tumor invasion, lymphatic metastasis, and tumor stage of colon cancer patients in TCGA database (Table 1). And, high TIMP2 expression was significantly correlated with Histologic grade in gastric cancer patients (Supplementary Table 1). Furthermore, high TIMP2 expression was associated with poor prognosis of gastric cancer in stages 3–4, T2-T3, and N1-N3 (Table 2). These findings strongly suggest that TIMP2 can be used as a prognostic biomarker for a variety of tumors, especially colon and gastric cancer.

Another important finding of this study is that TIMP2 expression is associated with different levels of immune infiltration in colon and gastric cancer. The results showed that the expression level of TIMP2 was positively correlated with the infiltration levels of CD8 + T, CD4 + T cells, neutrophils, macrophages and dendritic cells in COAD and STAD (Fig. 4A). In addition, high TIMP2 expression in CD4 + T cells, macrophages and Neutrophils lead to a poor prognosis in STAD patients (Fig. 4B). Moreover, we analyzed the correlation between TIMP2 and immune markers in immune cells, and the correlation between TIMP2 expression and immune cell marker genes suggests the role of TIMP2 in tumor immune regulation in COAD and STAD (Table 3 and Supplementary Table 2). These results further demonstrate that TIMP2 plays an important role in the recruitment and regulation of immune infiltrating cells in COAD and STAD.

Recent studies have explained the possible mechanisms of TIMP2 expression and immune infiltration and prognosis. TIMP2 plays a regulatory role in inhibiting tumor growth and metastasis by regulating mesenchymal transformation of epithelial cells and signaling pathways related to metastatic growth, including classical Wnt signaling and PI3K signaling involved in EMT (32). Monocytes are the major components of the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME). The expression level of TIMP2 in TME may have prognostic value for PDAC patients. In addition, activation of TIMP2 expressed monocytes in PDAC may provide a potential therapeutic opportunity to inhibit tumor cell invasion (33). Guedez et al. reported that TIMP2 deficiency in non-small cell lung cancer (NSCLC) up-regulated the expression of immunosuppressive genes IL-10, IL-13, IL-11 and chemokine ligands that control the growth of myeloid-derived suppressor cell (MDSC) and decreased interferon -γ. Tumor immunosuppression and angiogenesis are associated with the increase of MDSCs, and TIMP2 is a negative regulator of MDSCs. Therefore, TIMP2 is of great significance for immunotherapy or anti-angiogenic therapy of NSCLC(34). Therefore, TIMP2 expression may be a potential mechanism related to tumor immune invasion and prognosis.

In summary, abnormal expression of TIMP2 is associated with poor prognosis in multiple tumors, and increased expression of TIMP2 is associated with increased immune infiltration levels of CD8 + T cells, CD4 + T cells, macrophages, neutrophils, and DCS in colon and gastric cancer. Therefore, TIMP2 may play an important role in immune cell infiltration in patients with gastric and colon cancer and serve as a biomarker for prognosis.

Acknowledgement

We acknowledge the TIMER, TNMplot，Kaplan-Meier plotter, the PrognoScan, GEPIA and TCGA public database for providing their platforms and contributors for uploading their meaningful datasets.

Author contributions

FJ, JYH and WLM analyzed the experimental data and draw up the manuscript. NGP and LH contributed to statistical analysis. TYQ provided technical assistance in the acquisition of data. PZJ and FJ designed and supervised the study, and was a major contributor in modifying the manuscript. All authors read and approved the final version.

Funding

This study was supported by the First Affiliated Hospital of Anhui Medical University National Natural Science Foundation Cultivation fund (grant number 2018kj24).

Data availability

All datasets generated for this study are included in the article. The datasets presented in this study can be found in online repositories.

Compliance with ethical standards

Conflict of interests

The authors report no conflicts of interest in this work.

Ethical approval

The studies involving human participants were reviewed and approved by Xu Zhou central hospital (no. XZXY-LJ-20210526-096). The patients provided their written informed consent to participate in this study.

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Peeney D, Jensen SM, Castro NP et al. (2020) TIMP-2 suppresses tumor growth and metastasis in murine model of triple-negative breast cancer. Carcinogenesis. 41: 313-25. doi: 10.1093/carcin/bgz172
Benzing C, Lam H, Tsang CM, Rimmer A, Arroyo-Berdugo Y, Calle Y, Wells CM (2019) TIMP-2 secreted by monocyte-like cells is a potent suppressor of invadopodia formation in pancreatic cancer cells. BMC Cancer. 19: 1214. doi: 10.1186/s12885-019-6429-z
Guedez L, Jensen-Taubman S, Bourboulia D, Kwityn CJ, Wei B, Caterina J, Stetler-Stevenson WG (2012) TIMP-2 targets tumor-associated myeloid suppressor cells with effects in cancer immune dysfunction and angiogenesis. J Immunother. 35: 502-12. doi: 10.1097/CJI.0b013e3182619c8e

Table 1

The correlation between TIMP2 expression and clinicopathological features of colon cancer in the TCGA database.

Characteristics		No. of patients	TIMP2 expression		c²	P
Characteristics		No. of patients	High (n=173)	Low (n=281)	c²	P
Gender					1.115	0.291
	Male	240	86 (49.71%)	154 (54.8%)
	Female	214	87 (50.29%)	127 (45.2%)
Age					2.54	0.111
	＜60 years	125	55 (31.79%)	70 (24.91%)
	≥60 years	329	118 (68.21%)	211 (75.09%)
T stage					4.352	0.037
	T1+T2		25 (14.45%)	63 (22.42%)
	T3+T4		148 (85.55%)	218 (77.58%)
N stage					12.599	0.001
	N0	267	85 (49.13%)	182 (64.77%)
	N1	188	88 (50.87%)	99 (35.23%)
M stage					1.524	0.467
	M0	333	123 (72.35%)	210 (75.81%)
	M1	64	24 (14.12%)	40 (14.44%)
	Mx	50	23 (13.53%)	27 (9.75%)
AJCCstage					7.86	0.049
	I	75	22 (12.94%)	53 (19.34%)
	II	177	63 (37.06%)	114 (41.61%)
	III	128	61 (35.88%)	67 (24.45%)
	IV	64	24 (14.12%)	40 (14.6%)

Table 2

Correlation of TIMP2 mRNA expression and clinical prognosis in gastric cancer with different clinicopathological factors by Kaplan-Meier plotter.

Clinicopathological characteristics		Overall surviva (n = 881)			Progress-free surviva (n = 645)
Clinicopathological characteristics	N	Hazard ratio	P-value	N	Hazard ratio	P-value
Gender
Female	236	1.54(1.05-2.28)	0.028	201	1.53(1.02-2.29)	0.039
Male	544	1.52(1.22-1.89)	1.50E-04	437	1.55(1.21-1.98)	5.00E-04
Stage
1	67	1.96(0.55-6.97)	0.29	60	0.43(0.12-1.58)	0.19
2	140	1.59(0.88-2.88)	0.12	131	1.47(0.81-2.67)	0.2
3	305	1.56(1.17-2.08)	0.0024	186	1.8(1.24-2.61)	0.0016
4	148	2.07(1.39-3.07)	0.00024	141	1.62(1.1-2.4)	0.014
Stage T
2	241	1.9(1.24-2.93)	0.0029	239	1.8(1.19-2.74)	0.0052
3	204	1.9(1.3-2.76)	0.00067	204	1.52(1.05-2.2)	0.025
4	38	1.74(0.73-4.12)	0.21	39	2.18(1-4.74)	0.044
Stage N
0	74	1.6(0.59-4.37)	0.35	72	1.56(0.57-4.23)	0.38
1	225	2.2(1.44-3.37)	0.00021	222	2.14(1.43-3.21)	0.00016
2	121	2.13(1.35-3.35)	0.00084	125	2.59(1.51-4.43)	0.00033
3	76	1.96(1.14-3.38)	0.014	76	1.87(1.09-3.2)	0.022
1+2+3	422	1.87(1.44-2.44)	2.10E-06	423	1.79(1.39-2.31)	6.20E-06
Stage M
0	444	1.73(1.31-2.29)	1.00E-04	443	1.67(1.28-2.18)	0.00014
1	56	2.13(1.15-3.96)	0.014	56	1.62(0.86-3.03)	0.13
Lauren Classfication
Intestinal	320	2.17(1.58-2.98)	8.10E-07	263	2.08(1.45-2.97)	4.20E-05
Diffuse	241	1.58(1.12-2.23)	0.0085	231	1.56(1.1-2.21)	0.011
Differentiation
Poor	165	1.21(0.81-1.8)	0.35	121	1.77(1.1-2.85)	0.017
Moderate	67	1.97(1.02-3.83)	0.041	67	1.88(1-3.54)	0.045

Table 3

Correlation analysis between TIMP2 and relate genes and markers of immune cells in TIMER.

Description	Gene markes	COAD				STAD
Description	Gene markes	None		Purity		None		Purity
		Cor	P	Cor	P	Cor	P	Cor	P
CD8+ T cell	CD8A	0.396	***	0.286	***	0.215	***	0.198	***
	CD8B	0.259	***	0.183	**	0.108	*	0.103	*
T cell (general)	CD3D	0.358	***	0.209	***	0.14	*	0.109	*
	CD3E	0.464	***	0.345	***	0.187	***	0.159	**
	CD2	0.443	***	0.336	***	0.218	***	0.197	***
B cell	CD19	0.303	***	0.182	**	0.206	***	0.195	***
	CD79A	0.43	***	0.304	***	0.231	***	0.197	***
Monocyte	CD86	0.69	***	0.628	***	0.435	***	0.418	***
	CD115 (CSF1R)	0.704	***	0.637	***	0.572	***	0.556	***
TAM	CCL2	0.707	***	0.638	***	0.501	***	0.483	***
	CD68	0.578	***	0.518	***	0.345	***	0.325	***
	IL10	0.528	***	0.48	***	0.455	***	0.45	***
M1 Macrophage	INOS (NOS2)	-0.135	*	-0.197	***	-0.036	0.461	-0.04	0.434
	IRF5	0.388	***	0.406	***	0.342	***	0.348	***
	COX2(PTGS2)	0.302	***	0.232	***	0.319	***	0.313	***
M2 Macrophage	CD163	0.713	***	0.653	***	0.538	***	0.52	***
	VSIG4	0.661	***	0.591	***	0.564	***	0.562	***
	MS4A4A	0.658	***	0.592	***	0.542	***	0.582	***
Neutrophils	CD66b (CEACAM8)	-0.178	***	-0.158	***	0.02	0.691	0.047	0.364
	CD11b (ITGAM)	0.698	***	0.658	***	0.522	***	0.514	***
	CCR7	0.474	***	0.361	***	0.318	***	0.301	***
Natural killer cell	KIR2DL1	0.156	**	0.095	0.056	0.094	0.057	0.106	*
	KIR2DL3	0.157	**	0.108	*	0.041	0.409	0.034	0.514
	KIR2DL4	0.199	***	0.105	*	-0.068	0.167	-0.089	*
	KIR3DL1	0.225	***	0.158	**	0.055	0.264	0.045	0.387
	KIR3DL2	0.252	***	0.171	**	0.076	0.122	0.076	0.14
	KIR3DL3	0.01	0.836	-0.01	0.84	-0.102	0.037	-0.085	0.092
	KIR2DS4	0.165	**	0.124	*	0.017	0.735	0.005	0.929
Dendritic cell	HLA-DPB1	0.569	***	0.476	***	0.276	***	0.253	***
	HLA-DQB1	0.36	***	0.254	***	0.164	**	0.141	**
	HLA-DRA	0.52	***	0.417	***	0.206	**	0.184	***
	HLA-DPA1	0.573	***	0.481	***	0.248	***	0.227	***
	BDCA-1(CD1C)	0.505	***	0.418	***	0.384	***	0.379	***
	BDCA-4(NRP1)	0.802	***	0.766	***	0.715	***	0.703	***
	CD11c (ITGAX)	0.71	***	0.651	***	0.477	***	0.459	***
Th1	T-bet (TBX21)	0.43	***	0.344	***	0.178	**	0.167	**
	STAT4	0.435	***	0.334	***	0.293	***	0.282	***
	STAT1	0.474	***	0.429	***	0.086	0.081	0.08	0.12
	IFN-γ (IFNG)	0.229	***	0.161	**	-0.041	0.41	-0.053	0.302
	TNF-α (TNF)	0.356	***	0.297	***	0.163	**	0.136	*
Th2	GATA3	0.517	***	0.459	***	0.323	***	0.32	***
	STAT6	0.152	**	0.156	**	0.233	***	0.24	***
	STAT5A	0.355	***	0.337	***	0.436	***	0.44	***
	IL13	0.32	***	0.259	***	0.104	*	0.131	*
Tfh	BCL6	0.604	***	0.548	***	0.565	***	0.544	***
	IL21	0.23	***	0.181	***	0.06	0.225	0.051	0.318
Th17	STAT3	0.433	***	0.392	***	0.493	***	0.482	***
	IL17A	-0.181	***	-0.212	***	-0.196	***	-0.22	***
Treg	FOXP3	0.609	***	0.54	***	0.25	***	0.236	***
	CCR8	0.632	***	0.577	***	0.376	***	0.377	***
	STAT5B	0.409	***	0.44	***	0.556	***	0.551	***
	TGFβ (TGFB1)	0.737	***	0.674	***	0.626	***	0.615	***
T cell exhaustion	PD-1 (PDCD1)	0.414	***	0.313	***	0.155	**	0.148	*
	CTLA4	0.469	***	0.382	***	0.126	*	0.113	*
	LAG3	0.397	***	0.298	***	0.106	*	0.086	0.096
	TIM-3 (HAVCR2)	0.695	***	0.641	***	0.433	***	0.424	***
	GZMB	0.07	0.128	0.032	0.518	0.029	0.559	-0.009	0.869

*P < 0.01; **P < 0.001; ***P < 0.0001.

No competing interests reported.

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TIMP2 is associated with prognosis and immune infiltrates of gastric and colon cancer

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