TMEM200A is a potential prognostic biomarker and correlated with immune infiltrates in gastric cancer

Introduction

Gastric cancer (GC) is a deadly disease with low overall survival statistics worldwide. It ranks as the fifth most common human malignancy and the third leading cause of cancer-related deaths (Seidlitz, Koo & Stange, 2021). GC development is attributed to a variety of causes. Helicobacter pylori (H. pylori) infection is considered the major risk factor for non-cardiac GC (Smyth et al., 2020). Despite many strategies have been pursued to prevent GC, GC still remains a significant global health problem (Ferro et al., 2014; Rahman, Asombang & Ibdah, 2014). In light of cancer places a heavy burden on individuals, families, communities and health systems. New strategies are urgently needed to reveal the mechanism of the development and progression of GC. It is particularly important to identify new potential targets for GC therapy, as well as the identification of predictive biomarkers for clinical benefit.

Transmembrane (TMEM) proteins are a type of protein that span the lipid bilayer and mediate a large amount of biological functions (Jiang et al., 2021). Based on their transmembrane properties, TMEM proteins play an important role in signal transduction, ion transport and cell adhesion (Zhao et al., 2022). Some of them have been identified to be associated with diseases, including cancer (Ehrlich, Lacey & Ehrlich, 2020; Li et al., 2021a). In several cancer types, differential harmonization of gene expression of TMEMs have been found, such as breast cancer (TMEM17) (Zhao et al., 2018), lung cancer (TMEM116) (Zhang et al., 2021a), cervical cancer (TMEM48) (Jiang et al., 2021), gastric cancer (TMEM45B) (Shen et al., 2018), colorectal cancer (TMEM180) (Shiraishi et al., 2021), glioblastoma multiforme (TMEM39A) (Tran et al., 2017), hepatocellular carcinoma (TMEM106C) (Duan et al., 2021), osteosarcoma (TMEM45B) (Li et al., 2017).

The TMEM200s contain three TMEM200 family members in mammals, from TMEM200A to TMEM200C. Transmembrane protein 200A (TMEM200A), also known as KIAA1913, TTMA, and TTMC, is similar to other members of the gene family. In previous studies, researchers have demonstrated that TMEM200A is involved in the progression of pancreatic cancer (Tan, Schaffalitzky de Muckadell & Joergensen, 2020) and acute myeloid leukemia (AML) (Nie et al., 2022). In addition, evidence showed TMEM200A was important for adipose tissue morphology by regulation the proliferation of precursor cells. Both the accumulation of lipids and glycerol levels were reduced after knockdown of TMEM200A, while the cell number was increased (Lundback et al., 2020). However, TMEM200B has not been reported in cancer studies. Meanwhile, TMEM200C has been identified as a potential oncogene in uveal melanoma and is therefore a biomarker of early tumor metastasis and poor prognosis (Ness et al., 2021). In a previous, TMEM200A has demonstrated its oncogenic features in stomach adenocarcinoma (Zhang et al., 2020). However, the role of TMEM200A in GC is still unclear.

In this study, we compared the differential expression of TMEM200A expression in GC using publicly available data and experimental validation. Subsequently, we analyzed the influences of TMEM200A expression and patient characteristics on overall survival in GC patients. Additionally, we tried to unveil the underlying signaling pathway of TMEM200A expression level in GC progression. Moreover, we evaluated the association of TMEM200A with tumor-infiltrating immune cells. These, in turn will allow us to contribute towards the current literature on potential positive effects of TMEM200A in GC.

Materials and Methods

Results

The differential expression of TMEM200A in GC

The GC mRNA dataset were downloaded from TCGA database. Our study represented a total of 407 samples with 375 samples of GC tissues and 32 samples of adjacent non-tumor tissues. We discovered that the expression of TMEM200A in GC tissues was significantly higher than that in adjacent non-tumor tissues (P = 1.382e−05) (Fig. 1A).

To validate the difference in TMEM200A expression in TCGA database, we performed a comprehensive meta-analysis of TMEM200A expression using GEO database. As a result, the I² was 78% (P = 0.01), the combined SMD of TMEM200A was 0.31 according to the random effects model (95% CI [0.07–0.55], Fig. 2), suggesting that TMEM200A was up-regulated in GC.

Finally, we experimentally verified the expression level of TMEM200A. As a result, the expression level of TMEM200A mRNA in GC cells (HGC-27, MKN-28, AGS and MGC-803) were significantly higher than that in GES-1 (P = 0.0006 for HGC-27 vs. GES-1; P = 0.0022 for MKN-28 vs. GES-1; P = 0.0019 for AGS vs. GES-1; P = 0.0006 for MGC-803 vs. GES-1) (Fig. 3A). In clinical samples, the expression level of TMEM200A was higher in tumor tissues compared with in adjacent non-tumor tissues (P = 0.018) (Fig. 3B).

Prognostic significance of TMEM200A expression in GC patients

Previous analysis suggested that the overall survival was significantly correlated with TMEM200A expression in GC patients. Here, univariate and multivariate analysis were conducted to assess the effect of TMEM200A expression and patient characteristics on overall survival. Univariate analysis revealed that TMEM200A (HR = 1.064; 95% CI [1.018–1.113]; P = 0.006), age (HR = 1.027; 95% CI [1.008–1.047]; P = 0.006), pathological stage (HR = 1.535; 95% CI [1.221–1.931]; P = 0.000), T stage (HR = 1.298; 95% CI [1.023–1.645]; P = 0.032), M stage (HR = 2.048; 95% CI [1.096–3.827]; P = 0.025) and N stage (HR = 1.267; 95% CI [1.069–1.502]; P = 0.006), which were significant predictors of poor prognosis (Table 3). Multivariate analysis showed that TMEM200A (HR = 1.064; 95% CI [1.013–1.117]; P = 0.013), age (HR = 1.037; 95% CI [1.016–1.058]; P = 0.000) and gender (HR = 1.599; 95% CI [1.041–2.457]; P = 0.032) were independently associated with overall survival in GC (Table 3) (Fig. 4). These results suggested TMEM200A is a potential freestanding predictor of poor overall survival in GC patients.

Table 3:

Univariate and multivariate analysis of the relationship between TMEM200A expression and GC patients.

Clinicopathological features	Univariate analysis			Multivariate analysis
	HR	95% CI	P-value	HR	95% CI	P-value
Age	1.027	[1.008–1.047]	0.006	1.037	[1.016–1.058]	0.000
Gender	1.484	[0.980–2.247]	0.062	1.599	[1.041–2.457]	0.032
Grade	1.368	[0.947–1.977]	0.095	1.439	[0.980–2.113]	0.063
Pathological stage	1.535	[1.221–1.931]	0.000	1.308	[0.850–2.012]	0.222
T	1.298	[1.023–1.645]	0.032	1.090	[0.793–1.500]	0.595
M	2.048	[1.096–3.827]	0.025	2.122	[0.951–4.736]	0.066
N	1.267	[1.069–1.502]	0.006	1.071	[0.835–1.375]	0.589
TMEM200A	1.064	[1.018–1.113]	0.006	1.064	[1.013–1.117]	0.013

DOI: 10.7717/peerj.15613/table-3

Note:

HR, hazard ratio; CI, confidence interval.

Gene sets enriched in TMEM200A expression phenotype

High expression TMEM200A related signaling pathways based on GSEA was used to identify signaling pathways involved in GC. Based on normalized enrichment score (NES), false discovery rate (FDR) q-value, and nominal P-value, significantly enriched signaling pathways were obtained. 10 KEGG items including cytokine-cytokine receptor interaction, chemokine signaling pathway, T cell receptor signaling pathway, leukocyte transendothelial migration, toll-like receptor signaling pathway, TGF-β signaling pathway, JAK-STAT signaling pathway, mTOR signaling pathway, MAPK signaling pathway, pathway in cancer were significantly enriched in the increased expression phenotypes of TMEM200A (Table 4) (Figs. 5 and S1).

Table 4:

Gene sets enriched in the high-TMEM200A expression phenotype.

TMEM200A expression level	Gene set name	NES	NOM P-value	FDR q-value
High-TMEM200A expression	KEGG_CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION	1.99	0.004	0.018
	KEGG_CHEMOKINE_SIGNALING_PATHWAY	1.96	0.004	0.020
	KEGG_T_CELL_RECEPTOR_SIGNALING_PATHWAY	1.72	0.030	0.052
	KEGG_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION	1.95	0.004	0.020
	KEGG_TOLL_LIKE_RECEPTOR_SIGNALING_PATHWAY	1.80	0.016	0.042
	KEGG_TGF_BETA_SIGNALING_PATHWAY	2.09	0.000	0.010
	KEGG_JAK_STAT_SIGNALING_PATHWAY	1.91	0.004	0.023
	KEGG_MTOR_SIGNALING_PATHWAY	1.71	0.022	0.052
	KEGG_MAPK_SIGNALING_PATHWAY	1.96	0.000	0.018
	KEGG_PATHWAYS_IN_CANCER	1.90	0.000	0.022

DOI: 10.7717/peerj.15613/table-4

Note:

NES, normalized enrichment score; NOM, nominal; FDR, false discovery rate.

Relationship between TMEM200A expression and tumor-infiltrating immune cells

Gene set enrichment analysis suggest several immune-related signaling pathway as high expression TMEM200A associated signaling pathways in GC. Here, we next investigated whether TMEM200A expression was correlated to immune infiltration in GC. 375 tumor samples were divided into two parts according to TMEM200A expression, and thereby 187 samples of high expression group and 188 samples of low expression group met screening criterion. Finally, CIBERSORT was used to explore gene expression profiles of downloaded samples to infer the density of 22 types of immune cells, which helped assess their differing concentrations in the up-regulated and down-regulated TMEM200A expression groups. The proportion of 22 subpopulations of immune cells were showed in Fig. 6. CD8+ T cells and eosinophils are main immune cells effected by TMEM200A expression. Among them, CD8+ T cells are apparently (P = 0.017) decreased in high expression group compared with low expression group. In contrast, eosinophils (P = 0.002) are increased in high expression group compared with low expression group.

Discussion

TMEMs make up approximately 30% of the human proteome (Babcock & Li, 2014). Most of them play a fundamental role during tumor progression or cancer cell metastasis via signal transduction (Marx et al., 2020). In previous studies, multiple mechanisms indicated TMEMs are involved in tumor progression, as examples some TMEMs have been described as tumor suppressors. The overexpression of TMEM176A can inhibit cell migration, invasion and cell growth in colorectal (Gao et al., 2017). Furthermore, the expression levels of both TMEM97 protein and mRNA were lower in tumor tissues compared to adjacent normal tissues in pancreatic cancer and kidney cancer (Kayed et al., 2004; Schmit & Michiels, 2018). In the opposite site, many TMEMs are up-regulated in cancer, thereby TMEMs can act as oncogenes. In a previous study, it has been evidenced that TMEM158 can promote tumor growth, such as regulating cell proliferation and invasion in ovarian cancer (Cheng et al., 2015). In addition, inhibition of TMEM158 can impair the TGF-β signaling pathway (Cheng et al., 2015). Additionally, many TMEMs have been involved in drug resistance, such as TMEM45A (Flamant et al., 2012). Evidence showed that high levels of TMEM45A expression in breast and liver cancer cells may be indicative of potential resistance to cancer therapy, making TMEM45A a tumor-promoting factor (Flamant et al., 2012). Thus, TMEM can function either as an oncoprotein or tumor suppressor. Nevertheless, the reporting of TMEM200A was extremely inadequate, which hampers the assessment of its role in tumor progression. Here we have used publicly available data, RT-qPCR, survival curve and Cox proportional hazard regression models to gain new insights into the expression of TMEM200A on the overall survival in GC patients. In addition, the relationship between TMEM200A expression and tumor-infiltrating immune cells were also analyzed. These insights may have impact on GC patient care.

Here, we found that the differential expression of TMEM200A was significantly up-regulated in GC tissues than that in adjacent normal tissues in accordance to TCGA database. Consequentially, a meta-analysis was performed to verify the differential expression of TMEM200A in GC based on GEO datasets. Consistent with the previous observations, TMEM200A was increased in GC tissues. Furthermore, it was also confirmed in our experiments with GES-1 and GC cells in addition to human GC tissues and adjacent normal tissues, and the result was consistent with the results of the bioinformatics assay. Moreover, we analyzed the expression level of TMEM200A in GC patients with patient characteristics. As a result, the expression level of TMEM200A was significantly different in group classified according to tumor T stage. In addition, chi-square test and logistic regression analysis with TMEM200A expression also indicated that up-regulated TMEM200A was significantly related to T stage. Collectively, these results suggested that the high expression of TMEM200A may act as an oncogene, and thereby can be a prognostic biomarker in GC.

Our study uncovered the relationship between TMEM200A expression with the overall survival of GC patients using Kaplan-Meier method. We showed that GC patients with high TMEM200A expression had a poorer overall survival than that of patients with low expression. In addition, univariate analysis showed that TMEM200A and some other patient characteristics, as examples age, pathological stage, T stage, M stage and N stage were poor prognosis predictor. Moreover, multivariate analysis showed that TMEM200A was independently associated with overall survival in GC. These findings suggested TMEM200A is a freestanding predictor of poor overall survival in GC patients.

It has been demonstrated that TMEMs were involved in cancer progression via different signaling pathways. TMEM116, for example, is required for lung cancer cell motility and metastasis through PDK1 signaling pathway (Zhang et al., 2021a); TMEM229A suppresses non‑small cell lung cancer progression via inactivating the ERK pathway (Zhang et al., 2021b); inhibition of proliferation by knockdown of TMEM168 in glioblastoma cells via suppression of Wnt/β-Catenin pathway (Xu et al., 2019); TMEM17 promotes malignant progression of breast cancer via AKT/GSK3β signaling (Zhao et al., 2018). In this situation, 10 KEGG items including cytokine-cytokine receptor interaction, chemokine signaling pathway, T cell receptor signaling pathway, leukocyte transendothelial migration, Toll-like receptor signaling pathway, TGF-β signaling pathway, JAK-STAT signaling pathway, mTOR signaling pathway, MAPK signaling pathway, pathway in cancer were significantly enriched in the increased expression phenotypes of TMEM200A using GSEA. The cytokine-cytokine receptor interaction is an immune-related signaling pathway and thereby indicated that TMEM200A may regulate the inflammatory response and immune function in GC (Qian, Zhang & Wang, 2019; Song et al., 2020). The chemokine signaling pathway, which may contribute to chronic inflammation (Zhang et al., 2015), as several cancers were found to be associated with chronic inflammatory conditions (Malhab et al., 2021), including GC (Sammarco et al., 2019). T cell receptor signaling pathway has a central role in the control of T cell differentiation, homeostasis and function, such as T cell receptor signaling play an important role in the differentiation and function of Treg cell (Li & Rudensky, 2016), and thus suppress host immunity (Fang et al., 2022b). Leukocyte transendothelial migration is one of the most step in the initiation of inflammatory immune response and chronic inflammation can lead to destructive diseases. Leukocyte migration inhibitors are considered as promising and potentially effective therapeutic agents to treat inflammatory (Getter et al., 2019; Kong et al., 2018). Toll-like receptor signaling pathway has been established to play an essential role in the activation of innate immunity and is one potential common inflammatory pathway (Figueroa-Hall, Paulus & Savitz, 2020; Takeda & Akira, 2004). Dysregulation of this signaling pathway can result in development of cancer (Moradi-Marjaneh et al., 2018). JAK-STAT signaling pathway is involved in many crucial biological processes, including cell proliferation, differentiation, apoptosis, and immune regulation (Xin et al., 2020). MAPK signaling pathway plays an important role in various biological events, including in the differentiation, proliferation, apoptosis of cells and metabolic reprogramming (Asl et al., 2021). TGF-β signaling pathway (Colak & ten Dijke, 2017; Xiong et al., 2020), mTOR signaling pathway (Fattahi et al., 2020; Zhang et al., 2019) and pathway in cancer (Chen et al., 2020; Li et al., 2021b) are common tumor-associated signaling pathways, including in GC. Taken together, the above findings not only provide ideas to explore the carcinogenic and cancer-promoting molecular mechanisms of TMEM200A, but also indicate TMEM200A is correlated with immune infiltrates in GC, suggesting that TMEM200A is involved in GC progression via regulating various molecular signaling pathways.

As TMEM200A is involved in several immune-associated signaling pathways. Here, our studies revealed that in GC diverse immune infiltration levels are correlated with TMEM200A expression. A CIBERSORT analysis showed a negative connection of TMEM200A expression with infiltration level of CD8+ T cells. CD8+ T cells are considered the main effectors of anti-tumor immunity in tumor microenvironment (Hossain et al., 2021). Thereafter, decreased level of CD8+ T cells or CD8+ T cells exhaustion can lead to a bad prognosis (Dolina et al., 2021; Fang et al., 2022b; Kurachi, 2019). In contrast, TMEM200A had a positive connection with infiltration level of eosinophils, where, tumor-associated tissue eosinophils appear to be a good prognostic factor in gastrointestinal (Reichman, Karo-Atar & Munitz, 2016). Thus, the relationships between gene markers of immune cells and TMEM200A expression implicate the significant meaning of TMEM200A in regulating tumor immune microenvironment of GC.

Striking, there is a recent publication that has similar methodology and results to ours (Deng et al., 2023). In this study, the authors also found the expression of TMEM200 in GC tissues was significantly higher than that in normal tissues. Subsequently, survival curve and Cox proportional hazard regression models indicated that high expression of TMEM200A was associated with a poor prognosis in GC patients. In addition, the possible biological functions and signaling pathways involved in TMEM200A and the relationship between TMEM200A expression and tumor-infiltrating immune cells were also analyzed. Moreover, co-expression of genes with TMEM200A, the correlation between TMEM200A expression and immune checkpoint expression, the effect of TMEM200A on the sensitivity of common chemotherapeutic drugs and DNA methylation sites were also analyzed in this study. However, the limitation is that this research work is based entirely on public databases. In our study, in order to reduce bias, we used multiple GEO datasets to validate the differential expression of TMEM200A. Furthermore, chi-square test and logistic regression were used to analysis the expression level of TMEM200A in GC patients with patient characteristics. Additionally, we experimentally validated the differential expression of TMEM200A in cell lines and clinical tissues. To sum up, the two studies yielded similar results and shed light on the potential role of TMEM200A in GC.

Conclusions

In summary, our study points to TMEM200A as a potential prognostic biomarker and correlated with immune infiltrates in GC. However, the prognostic value of TMEM200A in GC still needs to be explored and validated. For better understand the fundamental role of TMEM200A in GC, large amount in-depth in vivo and in vitro research is urgently needed to reveal the mechanism of TMEM200A in the development and progression of GC. We look forward to providing more substantial benefits in addressing critical issues.

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