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Zinc Finger E-box binding Homeobox 1 as Prognostic Biomarker and its Correlation with Infiltrating Immune Cells and Telomerase in Lung Cancer
Biomed Sci Letters 2022;28:9-24
Published online March 31, 2022;  https://doi.org/10.15616/BSL.2022.28.1.9
© 2022 The Korean Society For Biomedical Laboratory Sciences.

Hye-Ran Kim*, Choong-Won Seo* and Jongwan Kim†,*

Department of Biomedical Laboratory Science, Dong-Eui Institute of Technology, Busan 47230, Korea
Correspondence to: Jongwan Kim. Department of Biomedical Laboratory Science, Dong-Eui Institute of Technology, 54 Yangji-ro, Busanjin-gu, Busan 47230, Korea.
Tel: +82-51-860-3525, Fax: +82-51-860-3150, e-mail: dahyun@dit.ac.kr
*Professor.
Received March 2, 2022; Revised March 22, 2022; Accepted March 24, 2022.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
 Abstract
The aim of this study was to identify the expression of zinc finger E-box binding homeobox 1 (ZEB1), its prognostic significance, and correlation between ZEB1 and infiltrating immune cells in lung cancer. Correlation between ZEB1 and telomerase was also analyzed in different types of cancers. RNA sequencing analysis and survival rates of patients were confirmed by Gene Expression Profiling Interactive Analysis (GEPIA). The Kaplan-Meier plotter and PrognoScan databases were used to analyze the prognostic value of ZEB1 in various cancers. The Tumor IMmune Estimation Resource (TIMER) was used to determine the correlation between ZEB1 and infiltrating immune cells. Lower ZEB1 expression was lower in lung cancer and was related to poor prognosis in lung adenocarcinoma (LUAD). ZEB1 expression exhibited a significantly positive correlation with infiltration levels of immune cells in LUAD and lung squamous cell carcinoma. Furthermore, we found that the ZEB1 expression correlated with subunits of telomerase. Our findings suggest ZEB1 as a potential biomarker to be used for prognostic significance and tumor immunology in lung cancer. The correlation between the expression of ZEB1 and telomere-related gene will help in understand the cancer-promoting mechanisms.
Keywords : Lung cancer, ZEB1, Prognosis, Immune cells, TERT, TERC
INTRODUCTION

Lung cancer is one of the common causes of death worldwide (Siegel et al., 2012). This process is developed into multiple stages that includes several genetic and epigenetic changes. The majority of primary lung cancers and premalignant lesions has mesenchymal phenotype, characterized by downregulation of E-cadherin and upregulation of vimentin (Sekido et al., 2003; Sato et al., 2007). Despite advances in treatment and early detection of lung cancer, many patients are diagnosed at an advanced stage, and the overall 5-year survival rates are 10~15% with a poor prognosis (Cagle et al., 2013). Lung cancer consists of several subtypes that have pathological and clinical relevance (Fujimoto and Wistuba, 2014). Recognition of histologic subtypes of non-small cell lung carcinomas (NSCLCs) such as adenocarcinoma and squamous cell carcinomas, as the most frequent subtype have become significant as a determinant of treatment in this disease (Kerr et al., 2014).

Zinc finger E-box binding homeobox 1 (ZEB1) plays a significant role in tumorigenesis and is remarkably associated with malignant progression of cancers. It is highly expressed in various mesenchymal cancers, such as breast, glioma, lung and pancreatic cancers, and its expression is positively correlated with tumor invasion and metastasis (Aghdassi et al., 2012; Sahay et al., 2015; Li et al., 2018; Suzuki et al., 2018). ZEB1 has been investigated for its role in a variety of cancers in humans, including gastric cancer, osteosarcoma and hepatocellular carcinoma, suggesting its important role in tumorigenesis. As a results of accumulating evidence, ZEB1 was abnormally expressed in different types of cancers and promoted aggressiveness during carcinogenesis (Chen et al., 2019). The many studies have shown that overexpression of ZEB1 was associated with shorter survival in patients suffering from various types of cancer such as colorectal cancer, esophageal squamous cell carcinoma, gastric cancer, hepatocellular carcinoma, intrahepatic cholangiocarcinoma, oral cavity carcinoma and pancreatic cancer (Singh et al., 2011; Kurahara et al., 2012; Okugawa et al., 2012; Zhou et al., 2012; Hashiguchi et al., 2013; Zhang et al., 2013; Bronsert et al., 2014; Murai et al., 2014; Yang et al., 2014; Goscinski et al., 2015; Wu et al., 2016; Terashita et al., 2016; Yao et al., 2017). Nevertheless, the correlation between ZEB1 and prognostic significance in lung cancer remains inconclusive. Thus, we carry out a meta-analysis to evaluate the prognostic value of ZEB1 in different types of cancer include lung cancer.

ZEB1 exhibits a unique reverse association with immune cell activity and abundance in various cancers (Block et al., 2019). Its transcriptional activities in tumor cells can regulate the anti-tumor immune response, and it is associated with epithelial to mesenchymal transition (EMT) in immune cell development. Chae et al. demonstrated that EMT was associated with decreased T-cell infiltration and increased cytokine expression associated with immunosuppressive in lung squamous cell cancer and adenocarcinoma (Chae et al., 2018). EMT-related genes have correlated with intratumoral stromal cells; a specific relationship between ZEB1 expression and decreased immune activity in multiple cancer types has been identified (Block et al., 2019). However, although ZEB1 is associated with immune cell development of several cancers, the underlying infiltrating immune cells in lung cancer are poorly understood. Therefore, we evaluated the correlation between ZEB1 and infiltrating immune cells in lung cancer.

Telomerase, which contains subunits such as telomerase reverse transcriptase (TERT) and telomerase RNA component (TERC), serves to protect telomeres. Telomerase was activated in adult germ-line tissues and immortal cells (Shen et al., 2002), and most malignant tumors (Hiyama and Hiyama, 2002). A previous study demonstrated that ZEB1 was positively correlated with TERT in breast-invasive ductal carcinoma, and telomerase activity and telomere length were altered (Yu et al., 2018). ZEB1 was overexpressed in various cells to induce EMT by suppressing E-cadherins (Mooney et al., 2015). Therefore, we examined the correlation between ZEB1 and telomeres in different types of cancer, including lung cancer.

In this study, we identified ZEB1 expression in normal and different types of tumor tissues based on TCGA data obtained from public databases. We also analyzed the correlation between ZEB1 and prognosis in different cancer types, including lung cancer, using public databases. Moreover, we demonstrated the correlation of ZEB1 with infiltrating immune cells in lung cancer using the Tumor IMmune Estimation Resource (TIMER) database. Our findings highlight the significant role of ZEB1 in lung cancer as well as provide a potential relationship and mechanism of between ZEB1 and tumor-immune interactions and between ZEB1 and telomerase.

MATERIALS AND METHODS

Oncomine database analysis

The expression level of ZEB1 in lung cancer was assessed using the Oncomine database (Rhodes et al., 2007). Oncomine is a public online database consisting of publicly available microarray data. Fold change of mRNA expression was analyzed by selecting data related to lung cancer samples vs. normal samples. Standardized normalization and parameters are provided on the Oncomine platform as follows: P-value < 0.001, fold change > 1.5, and gene ranking in the top 5%.

Gene Expression Profiling Interactive Analysis (GEPIA)

The GEPIA database, which is a web server tool from the TCGA and GTEx projects (Tang et al., 2017; Chen et al., 2019; Gu et al., 2020), was used to examine differences in ZEB1 expression between normal and tumor tissues based on RNA sequencing.

Kaplan-Meier plotter database analysis

The Kaplan-Meier plotter is based on database (Gyorffy et al., 2010) and is capable of identifying the association of genes with survival in various types of cancer, including lung cancer. Clinical data including those related to gender, age, stage, grade, and chemotherapy were applied to all patients. Correlation between individual ZEB1 expression and survival in lung cancer was analyzed online and presented as the hazard ratio, 95% confidence intervals, and computed log rank P-value.

PrognoScan database analysis

The PrognoScan database is used to evaluate biological relationships between gene expression and patient prognosis, such as first progression survival (FPS), overall survival (OS), post progression survival (PPS) (Mizuno et al., 2009). We used database to identify the correlation between ZEB1 mRNA expression and survival in lung cancer with a Cox P-value < 0.05.

TIMER analysis

TIMER consists of 10,897 samples across 32 cancer types. Spearman's correlation analysis of these samples was performed to determine the correlation between ZEB1 expression and telomerase subunits (TERT and TERC) in the TCGA database (Li et al., 2017). TIMER has also been used to analyze tumor-infiltrating immune cells (TIICs) in lung cancer; it determines their abundance based on statistical analysis of gene expression profiles (Li et al., 2016). We analyzed the association between the level of ZEB1 expression and infiltrating immune cells (CD4+ T cells, CD8+ T cells, B cells, neutrophils, dendritic cells, and macrophages) in different cancer types, including lung cancer.

Statistical analysis

Gene expression data acquired from the Oncomine database were analyzed using online tools. Survival curves were generated using Kaplan-Meier plots and PrognoScan online tools. The correlation of gene expression was evaluated by means of the TIMER database using Spearman's correlation analysis. All the results are presented as P values employing the log-rank test.

RESULTS

Expression levels of mRNA of ZEB1 in different types of cancer

Applying meta-analysis to data on lung cancer in the Oncomine database, we measured the expression levels of ZEB1 mRNA between normal and lung cancer tissues in five distinct lung cancer datasets (Hou et al., 2010; Mabey et al., 2012; Navarro et al., 2019). The analysis revealed that mRNA expression levels of ZEB1 were significantly lower in lung cancer among the five analyzed lung cancer datasets with different histological findings (P = 1.58E-17, Fig. 1). To determine differences in the mRNA expression levels of ZEB1 between tumor tissues and normal tissues, its expression in normal and various cancers type, including lung cancer, was analyzed using the GEPIA. The results revealed that ZEB1 mRNA expression was lower in lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), bladder urothelial carcinoma (BLCA), breast invasive car-cinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), colon adenocarcinoma (COAD), kidney chromophobe (KICH), ovarian serous cystadenocarcinoma (OV), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), testicular germ cell tumors (TGCT), uterine corpus endometrial carcinoma (UCEC), and uterine carcinosarcoma (UCS) than in normal tissues (Fig. 1A, Supplementary Fig. 1A and B). However, ZEB1 expression was higher in glioblastoma multiforme (GBM), acute myeloid leukemia (LAML), brain lower grade glioma (LGG), pancreatic adenocarcinoma (PAAD), pheochromocytoma, paraganglioma (PCPG), and thymoma (THYM) than in normal tissues (Supplementary Fig. 1C). These results suggest that expression of ZEB1 mRNA was either high or low depending on the type of cancer.

Fig. 1. mRNA expression levels of ZEB1 in different types of cancer. The expression levels of ZEB1 were analyzed by using the Oncomine and GEPIA databases. (A) Low expression of ZEB1 in various cancer tissues than in normal tissues. (B) Low expression of ZEB1 in samples of five distinct lung cancer datasets exhibiting different histological findings. (C) Low expression of ZEB1 in lung cancer. *P < 0.05. LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma.

Prognostic significance of ZEB1 expression in different types of cancer

We identified whether expression of ZEB1 correlated with prognosis in lung cancer. Towards this objective, the effect of ZEB1 expression on survival rates was investigated using the Kaplan-Meier plotter and PrognoScan databases. The survival rates such as first progression survival (FPS), overall survival (OS), and post-progression survival (PPS) corresponding to ZEB1 expression in lung cancer were analyzed. The results revealed that patients with lower ZEB1 levels had a significantly shorter survival time than those with higher ZEB1 levels (Fig. 2). Lower expression of ZEB1 was associated with poorer prognosis in LUAD (FPS: HR = 1.61, P = 0.004; OS: HR = 1.89, P = 5.1e-07; Fig. 2A and B). However, expression of ZEB1 was not associated with PPS in LUAD (Fig. 2C) and FPS, OS, and PPS in LUSC (Fig. 2D-F). These results reveal the prognostic significance of ZEB1 expression in LUAD. Next, we indicated the relationship between ZEB1 expression and clinicopathological characteristics of lung cancer using the Kaplan-Meier Plotter database; the results are shown in Table 1. Low ZEB1 expression correlated with poorer OS in men (HR = 1.61, P = 7.2e-0.6) and women (HR = 1.61, P = 3.7e-05). It correlated with worse OS (HR = 3.32, P = 5.8e-12) and PPS (HR = 2.44, P = 0.0033) in stage 1, and PPS (HR = 2.04, P = 0.043) in stage M (distant metastases). The results of this study showed that the prognostic significance of ZEB1 expression based on clinicopathological characteristics, especially in the early stage and distant metastases of LUAD. To further examine the prognostic potential of ZEB1 in different cancer types, we used the PrognoScan database. The analysis indicated worse prognosis in blood, brain, breast, colorectal, eye, lung, and ovarian cancers (Supplementary Table 1). Taken together, expression of ZEB1 was associated with poorer prognosis in LUAD and other cancers.

Association between ZEB1 and clinicopathological characteristics in lung cancer

Clinicopathological characteristics First progression survival Overall survival Post progression survival
N Hazard ratio P-value N Hazard ratio P-value N Hazard ratio P-value
SEX
Male 243 1.19 (0.85~1.7) 0.31 659 1.61 (1.3~2.0) 7.2e-0.6 82 1.49 (0.88~2.6) 0.14
Female 353 1.33 (0.85~2.1) 0.22 374 2.08 (1.5~2.9) 3.7e-0.5 56 1.45 (0.69~3.0) 0.32
STAGE
1 316 1.43 (0.91~2.2) 0.12 449 3.23 (2.3~4.5) 5.8e-12 76 2.44 (1.3~4.5) 0.0033
2 125 1.23 (0.72~2.1) 0.45 161 1.14 (0.72~1.8) 0.57 54 1.1 (0.55~2.2) 0.78
STAGE T
1 54 1.02 (0.27~3.8) 0.98 224 1.15 (0.78~1.7) 0.49 9 2.78 (0.44~1.8) 0.26
2 121 1.02 (0.55~1.9) 0.94 190 1.24 (0.85~1.82) 0.26 39 1.82 (0.85~3.8) 0.12
STAGE N
0 126 1.3 (0.65~2.6) 0.45 324 1.03 (0.75~1.4) 0.84 31 1.89 (0.81~4.4) 0.13
1 51 1.49 (0.6~3.72) 0.39 102 1.02 (0.62~1.68) 0.93 18 2.08 (0.61~7.1) 0.23
STAGE M
0 177 1.11 (0.64~1.9) 0.7 462 1.04 (0.82~1.3) 0.73 49 2.04 (1.0~4.1) 0.043

The clinicopathological characteristics of ZEB1 were analyzed using the Kaplan-Meier plotter. *P < 0.05. T, tumor; N, lymph node; M, distant metastases. Bold values indicate P < 0.05



Fig. 2. Prognostic significance of high expression of ZEB1 in cancers. The prognostic value of ZEB1 was analyzed using the Kaplan-Meier plotter. Survival curves of FPS (A), OS (B) and PPS (C) of ZEB1 in LUAD. Survival curves of FPS (A), OS (B) and PPS (C) of ZEB1 in LUSC. FPS, first progression survival; OS, overall survival; PPS, post-progression survival.

Correlation between ZEB1 expression and infiltrating immune cells in different types of cancer

The survival time of cancer patients is decided by the quantity and activity status of tumor-infiltrating lymphocytes (Ohtani, 2007; Japanese Gastric Cancer Association, 2017). We explored the correlation between ZEB1 expression and immune cell infiltration in lung cancer using the TIMER database in 32 cancer types, including lung cancer. The results revealed that expression of ZEB1 exhibited a significantly positive correlation with the infiltration levels of CD4+T cells (R = 0.191, P < 2.02e-05), CD8+T cells (R = 0.319, P < 4.22e-13), neutrophils (R = 0.359, P < 1.95e-16), macrophages (R = 0.427, P < 3.08e-23), and dendritic cells (R = 0.211, P < 2.27e-06) in LUAD. Furthermore, ZEB1 expression showed a significantly positive correlation with the infiltration levels of CD4+T cells (R = 0.164, P < 3.25e-04), CD8+T cells (R = 0.273, P < 1.26e-09), neutrophils (R = 0.193, P < 2.22e-05), macrophages (R = 0.26, P < 8.46e-09), and dendritic cells (R = 0.319, P < 9.83e-13) in LUSC (Fig. 3). However, expression of ZEB1 was not significantly correlated with B cells in lung cancer. Moreover, ZEB1 expression correlated with the infiltration levels of CD4+T cells in 19 species cancers, CD8+T cells in 24 species cancers, B cells in 10 cancer types, neutrophils in 24 cancer types, macrophages in 24 cancer types, and dendritic cells in 21 cancer types (Supplementary Table 2). These findings presented that ZEB1 expression correlate with the infiltration of immune cells in different cancer types, including lung cancer.

Fig. 3. Correlation between ZEB1 expression and infiltrating immune cells in lung cancer. The correlation between ZEB1 and infiltrating immune cells was analyzed using the TIMER database. (A, B) infiltrating immune cells (CD4+T cells, CD8+T cells, neutrophils, macrophages, dendritic cells) in LUAD and LUSC.

Correlation between ZEB1 expression and telomerase in different cancer types

To identify the correlation of ZEB1 with TERT and TERC, we examined the data obtained from the TIMER database in 32 cancer types of TERT and TERC (Table 2, 3). These results revealed that ZEB1 expression was negatively correlated with TERT expression in BRCA (R = -0.25, P < 0.000), COAD (R = -0.12, P < 0.013), LUAD (R = -0.18, P < 0.000), PAAD (R = -0.20, P < 0.008), PRAD (R = -0.22, P < 0.000), READ (R = -0.18, P < 0.024), sarcoma (R = -0.18, P < 0.004), stomach adenocarcinoma (STAD, R = -0.22, P < 0.000), and TGCT (R = -0.57, P < 0.000). More-over, expression of ZEB1 was negatively correlated with TERC in BRCA (R = -0.17, P < 0.000), COAD (R = -0.16, P < 0.007), kidney renal clear cell carcinoma (R = -0.09, P < 0.048), kidney renal papillary cell carcinoma (R = -0.13, P < 0.033), LGG (R = -0.14, P < 0.001), LUAD (R = -0.12, P < 0.008), OV (R = -0.13, P < 0.019), PAAD (R = -0.13, P < 0.004), READ (R = -0.42, P < 0.000), STAD (R = -0.20, P < 0.000), and TGCT (R = -0.34, P < 0.000) (Table 2). In contrast, ZEB1 expression was positively correlated with TERT in GBM (R = 0.38, P < 0.000), skin cutaneous melanoma (R = 0.11, P < 0.013), THYM (R = 0.38, P < 0.000), and uveal melanoma (R = 0.36, P < 0.001). In addition, it was positively correlated with TERC in cholangiocarcinoma (R = 0.44, P < 0.007). These results suggest that expression of ZEB1 was correlated with TERT and TERC in different cancers type.

Correlation between ZEB1 and TERT expression. The correlation between ZEB1 and TERT expression was analyzed using the TIMER database

Cancer type R P
Adrenocortical carcinoma -0.03 0.773
Bladder urothelial carcinoma -0.07 0.154
Breast invasive carcinoma -0.25 0.000
Cervical squamous cell carcinoma and endocervical adenocarcinoma -0.02 0.700
Cholangiocarcinoma -0.12 0.503
Colon adenocarcinoma -0.12 0.013
Lymphoid neoplasm diffuse large B-cell Lymphoma 0.21 0.152
Esophageal carcinoma 0.02 0.747
Glioblastoma multiforme 0.38 0.000
Head and neck squamous cell carcinoma 0.01 0.898
Kidney Chromophobe 0.10 0.411
Kidney renal clear cell carcinoma -0.06 0.154
Kidney renal papillary cell carcinoma 0.08 0.173
Brain lower grade glioma -0.05 0.290
Liver hepatocellular carcinoma -0.09 0.084
Lung adenocarcinoma -0.18 0.000
Lung squamous cell carcinoma -0.05 0.305
Mesothelioma -0.10 0.353
Ovarian serous cystadenocarcinoma -0.06 0.319
Pancreatic adenocarcinoma -0.20 0.008
Pheochromocytoma and Paraganglioma 0.02 0.764
Prostate adenocarcinoma -0.22 0.000
Rectum adenocarcinoma -0.18 0.024
Sarcoma -0.18 0.004
Skin cutaneous melanoma 0.11 0.013
Stomach adenocarcinoma -0.22 0.000
Testicular germ cell tumors -0.57 0.000
Thyroid carcinoma 0.01 0.900
Thymoma 0.38 0.000
Uterine corpus endometrial carcinoma -0.06 0.157
Uterine carcinosarcoma -0.23 0.082
Uveal melanoma 0.36 0.001

Bold values indicate P < 0.05



Correlation between ZEB1 and TERC expression. The correlation between ZEB1 and TERC expression was analyzed using the TIMER database

Cancer type R P
Adrenocortical carcinoma -0.10 0.389
Bladder urothelial carcinoma -0.05 0.301
Breast invasive carcinoma -0.17 0.000
Cervical squamous cell carcinoma and endocervical adenocarcinoma -0.09 0.121
Cholangiocarcinoma 0.44 0.007
Colon adenocarcinoma -0.16 0.001
Lymphoid neoplasm diffuse large B-cell Lymphoma -0.24 0.107
Esophageal carcinoma 0.03 0.727
Glioblastoma multiforme -0.05 0.575
Head and neck squamous cell carcinoma 0.01 0.822
Kidney Chromophobe 0.08 0.511
Kidney renal clear cell carcinoma -0.09 0.048
Kidney renal papillary cell carcinoma -0.13 0.033
Brain lower grade glioma -0.14 0.001
Liver hepatocellular carcinoma 0.01 0.805
Lung adenocarcinoma -0.12 0.008
Lung squamous cell carcinoma -0.07 0.097
Mesothelioma -0.13 0.225
Ovarian serous cystadenocarcinoma -0.13 0.019
Pancreatic adenocarcinoma -0.13 0.084
Pheochromocytoma and Paraganglioma -0.08 0.257
Prostate adenocarcinoma -0.13 0.004
Rectum adenocarcinoma -0.42 0.000
Sarcoma 0.01 0.817
Skin cutaneous melanoma 0.04 0.364
Stomach adenocarcinoma -0.20 0.000
Testicular germ cell tumors -0.34 0.000
Thyroid carcinoma -0.03 0.502
Thymoma 0.12 0.200
Uterine corpus endometrial carcinoma -0.04 0.336
Uterine carcinosarcoma 0.17 0.198
Uveal melanoma -0.11 0.316

Bold values indicate P < 0.05


DISCUSSION

Zinc finger E-box binding homeobox 1 (ZEB1) is a transcription factor belonging to the human ZEB family. ZEB1 is involved in several processes during the advance of lymphopoiesis, neural crest cells and neurogenesis (Vandewalle et al., 2009). ZEB1 regulates gene expression by interacting with specific activators (Sanchez-Tillo et al., 2015) or repressors (Siles et al., 2013) in various cancers. ZEB1 was highly expressed in mesenchymal tumors such as glioma, lung cancer, breast cancer, and pancreatic cancer, and its levels were positively correlated with invasiveness (Aghdassi et al., 2012; Sahay et al., 2015; Li et al., 2018; Suzuki et al., 2018). ZEB1 plays important role in epithelial to mesenchymal transition (EMT) in various cancers of humans (Zhang et al., 2015). EMT was a process characterized by the transformation from an epithelial cell phenotype to a mesenchymal phenotype, which was associated with enhanced cellular invasion and motility (Zeisberg and Neilson, 2009). ZEB1 facilitates EMT by suppressing the E-cadherin that maintains the epithelial phenotype (Aigner et al., 2007). An increasing number of study has shown that overexpression of ZEB1 was associated with shorter survival in various types of cancer, including colorectal cancer (Singh et al., 2011; Zhang et al., 2013; Wu et al., 2016), gastric cancer (Okugawa et al., 2012; Murai et al., 2014), hepatocellular carcinoma (Zhou et al., 2012; Hashiguchi et al., 2013), pancreatic cancer (Kurahara et al., 2012; Bronsert et al., 2014), esophageal squamous cell carcinoma (Yang et al., 2014; Goscinski et al., 2015), oral cavity carcinoma (Yao et al., 2017), and intrahepatic cholangiocarcinoma (Terashita et al., 2016). Nevertheless, the prognostic significance of ZEB1 in lung cancer remains unclear. Thus, we performed a comprehensive meta-analysis to identify the prognostic values of ZEB1 in different types of cancer, including lung cancer. Our results showed that lower expression of ZEB1 had a prognostic value in various cancers, including LUAD. However, it was not associated with PPS in LUAD, FPS, OS, and PPS in LUSC. Furthermore, lower expression of ZEB1 correlated with poorer OS in both men and women. It also correlated with a worse outcome of OS and PPS in stage 1 and PPS in stage M. Our findings suggest that ZEB1 could be considered as a potential prognostic marker for LUAD and other cancers.

Cancer cells produce many cytokines and chemokines that grow various immune cells in the human body into a tumor, creating tumor-related inflammation (MacMahon, 1991; Kitamura et al., 2015). The tumor-infiltrating immune cells can control tumor progression through the production of inflammatory mediators. Cancer cells, by engaging in a complex crosstalk with immune cells, reveal EMT plasticity to adapt to the changing microenvironment they encounter in a primary cancer, during metastasis. ZEB1 is a driver of EMT and plays several roles in immune cell development. Recent studies have shown that EMT-related genes were highly correlated with intratumoral stromal cells and have ascertained a specific relationship between stroma-corrected expression of ZEB1 and decreased immune activity in various cancers types (Block et al., 2019). Recently, several studies have revealed the role of ZEB1 in multiple immune cell lineages. ZEB1 influences the immune response to cancer in multiple ways, either directly or indirectly. It is primarily expressed by dendritic cells (DCs) and neutrophils (Scott and Omilusik, 2019). The expression of ZEB1 in cancer cells has been shown to be associated with the molecular features of stem cells. Miranda et al. have shown a strong negative association between cancer stemness and anti-cancer immunity (Miranda et al., 2019). This negative association was particularly observed for CD8+ lymphocytes, and then for NK and B cells, whereas it was more variable for CD4+ cells, regulatory T cells (Tregs), and neutrophils, thus indicating that the influence of cancer stemness on tumor infiltration by immune cells might be cell-specific (Miranda et al., 2019). They also demonstrated a strong negative association between tumor cell expression of the stemness marker ZEB1 and the number of CD8+ tumor-infiltrating lymphocytes (TILs). ZEB1 was highlighted both as a marker of tumor cell EMT and tumor stroma in mesenchymal cells (Miranda et al., 2019). Our study is the first to explore the correlation between ZEB1 and immune cell infiltration in lung cancer. Our findings revealed that ZEB1 expression displayed a significantly positive correlation with the infiltration levels of CD4+T cells, CD8+T cells, neutrophils, macrophages, and dendritic cells in LUAD and LUSC. These findings suggest that ZEB1 may be a potential diagnostic and therapeutic target in lung cancer patients. Nonetheless, the correlation between ZEB1 and infiltrating immune cells requires further study.

ZEB1 is a significant inducer of epithelial to mesenchymal transition (EMT) and is identified as a repressor of cell adhesion molecule as well as genes related to cell polarity (Miyazono, 2009). ZEB1 is a key EMT nuclear transcription factor that play significant roles in regulating E-cadherin expression. E-cadherin is involved in starting EMT and epithelial marker (Wellner et al., 2009; Sanchez-Tillo et al., 2011). EMT, an absolute requirement for tumor metastasis and invasion, plays a key role in progression of cancer (Kalluri and Weinberg, 2009; Tsuji et al., 2009). Many studies have shown that TERT promotes tumor metastasis and invasion in various cancers such as gastric, liver, and esophageal cancers (Cayuela et al., 2005; Cristofari and Lingner, 2006; Moroishi et al., 2015), and that TERT promotes EMT via the Wnt signaling pathway in gastric cancer and osteosarcoma (Sanchez-Tillo et al., 2010; Liu et al., 2013). ZEB1 is related in regulating the expression of E-cadherin in tumor metastasis and invasion, resulting in cancer prognosis (Schmalhofer et al., 2009; Sanchez-Tillo et al., 2011). ZEB1 promotes EMT by directly binding to E-cadherin promoter E-box region. ZEB1 recruits TERT and binds to the E-cadherin promoter to repress its expression (Qin et al., 2016). A previous study demonstrated that TERT promotes cancer metastasis by stimulating EMT through the ZEB1 pathway (Mooney et al., 2015). Upregulation of TETC is an early event in tumorigenesis, and TETC could be correlated with tumor grade rather than with telomerase activity or TERT expression (Yashima et al., 1997; Maitra et al., 1999; Dome et al., 2005). Hence, we evaluated the correlation between ZEB1 and telomerase subunits (TERT and TERC) in different types of cancer, including lung cancer. Our findings suggested that ZEB1 correlates with TERT and TERC in various cancers, including LUAD. Although the correlation of ZEB1 is revealed in various cancer types, detailed mechanisms underlying ZEB1 regulation should be confirmed in future studies.

In conclusion, our results indicate that the expression of ZEB1 correlates well with infiltrating immune cells and shows poor prognostic significance in lung cancer. We suggest that ZEB1 could be a potential prognostic biomarker and provide novel insights into tumor immunology. Understanding the correlation between ZEB1 expression and telomerase may provide insights into telomere-related diseases, including different types of cancer. Therefore, it will be interesting to conduct future oncology-based studies to understand the biological functions of ZEB1 as well as the correlation between ZEB1 and telomere-associated gene expression. Taken together, these findings suggest that ZEB1 could be a potential diagnostic target for the treatment of lung cancer patients.

SUPPLEMENTARY MATERIALS
bsl-28-1-9-supple.pdf
ACKNOWLEDGEMENT

None.

CONFLICT OF INTEREST

The author declares no conflict of interest.

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