CLDN6 and CLDN10 are Associated with Immune Inltration of Ovarian Cancer: A Study of Claudin Family

Background: Claudin family is a group of membrane proteins related to tight junction. There are many studies about them in cancer, but few studies pay attention to the relationship between them and the tumor microenvironment. In our research, we mainly focused on the genes related to the prognosis of ovarian cancer, and explored the relationship between them and the tumor microenvironment of ovarian cancer. Methods: The cBioProtal provided the genetic variation pattern of claudin gene family in ovarian cancer. The ONCOMINE database and Gene Expression Proling Interactive Analysis (GEPIA) were used to exploring the mRNA expression of claudins in cancers. The prognostic potential of these genes was examined via Kaplan-Meier plotter. Immunologic signatures were enriched by gene set enrichment analysis (GSEA). The correlations between claudins and the tumor microenvironment of ovarian cancer were investigated via Tumor Immune Estimation Resource (TIMER). Results: In our research, claudin genes were altered in 363 (62%) of queried patients/samples. Abnormal expression levels of claudins were observed in various cancers. Among them, we found that CLDN3, CLDN4, CLDN6, CLDN10, CLDN15 and CLDN16 were signicantly correlated with overall survival of patients with ovarian cancer. GSEA revealed that CLDN6 and CLDN10 were signicantly enriched in immunologic signatures about B cell, CD4 T cell and CD8 T cell. What makes more sense is that CLDN6 and CLDN10 were found related to the tumor microenvironment. CLDN6 expression was negatively correlated with immune inltration level in ovarian cancer, and CLDN10 expression was positively correlated with immune inltration level in ovarian cancer. Further study revealed the CLDN6 expression level was negatively correlated with gene markers of various immune cells in ovarian cancer. And, the expression of CLDN10 was positive correlated with gene markers of immune cells in ovarian cancer. Conclusions: CLDN6 and prognostic biomarkers, and correlated with immune inltration in ovarian cancer. Our results revealed new roles for CLDN6 and CLDN10, and they were potential therapeutic targets in the treatment of ovarian cancer. These results suggest that CLDN6 and CLDN10 may participate in the immune cells inltration of ovarian cancer, and these mechanisms may be the reasons for poor prognosis of ovarian cancer. ovarian cancer [35] . Studies have revealed that CLDN10 is not only related to OS of ovarian cancer, but also to the chemoresistance of ovarian cancer [36] . Recent evidences suggested that claudin-10 in an immune-related key gene and play a key role in the progression of papillary thyroid cancer [17, 37] . Our research innovatively found that the prognostic potential of CLDN6 and CLDN10 were related to the tumor immune microenvironment in ovarian cancer.

expression was negatively correlated with immune in ltration level in ovarian cancer, and CLDN10 expression was positively correlated with immune in ltration level in ovarian cancer. Further study revealed the CLDN6 expression level was negatively correlated with gene markers of various immune cells in ovarian cancer. And, the expression of CLDN10 was positive correlated with gene markers of immune cells in ovarian cancer.
Conclusions: CLDN6 and CLDN10 were prognostic biomarkers, and correlated with immune in ltration in ovarian cancer. Our results revealed new roles for CLDN6 and CLDN10, and they were potential therapeutic targets in the treatment of ovarian cancer.

Background
Ovarian cancer is the most lethal gynecologic oncology of genital system [1] . Although the advancement of surgical techniques and the combined application of chemotherapy drugs since the 1970s, the ve-year survival rate of advanced ovarian cancer is just about 40%-45% [2] . Therefore, it is still urgent to improve treatment for ovarian cancer.
Immunotherapy is an emerging treatment method for several solid tumors, because it would improve outcomes of patients. With the application of numerous immune-based interventions in ovarian cancer, immunotherapy has been proven to be useful in advanced ovarian cancer [3] .
Claudins are major components of tight junction and consist of more than 20 claudin proteins. They serve as a physical barrier to prevent molecules from passing freely through the paracellular space between epithelial or endothelial cell sheets, and also play critical roles in maintaining cell polarity and signal transductions [4] . Previous research con rmed known claudins gene expression patterns and identi ed several genes dysregulated in cancers [5] .
They may play roles in the tumorigenesis of solid tumors [6,7] , and represent promising targets for cancer detection, prognosis and therapy [8] . However, the relationship between claudins and the tumor microenvironment has not been investigated. Here, we comprehensively analyzed claudins expression in ovarian cancer, and further explored the relationship between claudins and immune cell in ltration.

ONCOMINE Database Analysis
The expression of claudins in various cancers were analyzed via the ONCOMINE database (https://www.ONCOMINE.org/resource/login.html) [11] . The ONCOMINE database includes more than 35 types of cancer and normal samples.
Gene Expression Pro ling Interactive Analysis (GEPIA) GEPIA version2 (http://gepia2.cancer-pku.cn/) [12] is a web server for analyzing the RNA sequencing expression data of 9,736 tumors and 8,587 normal samples from The Cancer Genome Atlas (TCGA) and the GTEx projects, using a standard processing pipeline. The expression pro le of claudins in ovarian cancer were explored according to GEPIA2.
The p-value cutoff was 0.05, and |log 2 FC| cutoff was 1.
Prognostic signi cance of claudins in ovarian cancer were analyzed via the online datasets.
Tumor Immune Estimation Resource (TIMER) TIMER (https://cistrome.shinyapps.io/timer/) [14] is a web server for comprehensive analysis of tumor-in ltrating immune cells. The correlation between claudins expression and immune cell in ltration were analyzed from this database. TIMER2.0, an updated and enhanced version of TIMER, can be used to systematically analyze immune in ltration across diverse cancer types.

Statistical Analyses
The expression of claudins were presented as mean. Kaplan-Meier survival curves were based on the log-rank test.
The HR was performed using the Cox model. Spearman correlation test was used for correlation analysis. P-value < 0.05 was considered to be signi cant.

Gene variation of claudins in ovarian cancer
Twenty-four reviewed proteins of claudin family were obtained from the UniProt Knowledgebase (UniProtKB) (https://www.uniprot.org/) ( Table 1) (An additional le shows this in more detail [see Table 1]). Firstly, we investigated the genetic variation of claudin family in ovarian cancer through the cBioProtal for Cancer Genomics (https://www.cbioportal.org/). Twenty-four genes were queried in 585 samples of ovarian serous cystadenocarcinoma (TCGA, PanCancer Atlas). Figure 1A showed the alteration frequency of genetic variation in serous ovarian cancer. Figure 1B showed that queried genes were altered in 363 (62%) of queried patients/samples. Among them, the top three gene variation were CLDN11 (24%), CLDN16 (22%) and CLDN1 (16%). Then, overall survival differences between altered group and unaltered group were compared by Kruskal Wallis test. We found that overall survival is reduced in altered group compared to unaltered group (p = 7.981e-3) (Fig. 1C). Previous studies have shown that claudin gene family dysregulated in a variety of tumors and involved in diagnostic, tumorigenesis, and prognosis [15][16][17] . Thus, this gene family is worthy of further research in ovarian cancer.

The expression of claudin family is dysregulated in various cancers
To 3. Claudins expression were correlated with the prognosis of ovarian cancer To identify which of these genes have clinical signi cance, we studied the relationship between these differentially expressed genes and the prognosis of patients with ovarian cancer using Kaplan-Meier plotter. As shown in Fig. 3, genes overexpression including CLDN3, CLDN4, CLDN6, and CLDN16 were found to be signi cantly correlated with poor overall survival (OS) (Fig. 3A) and progression free survival (PFS) (Fig. 3B) of patients with ovarian cancer.
Besides, high expression of CLDN10 and CLDN15 predicted good prognosis among ovarian cancer ( Fig. 3C-D).

GSEA of immunologic signature gene sets
To characterize the potential function of claudins, GSEA was performed using the gene expression data of ovarian cancer patients in TCGA. Immunologic signature gene sets were used. As shown in Fig. 4, we found that CLDN6 and CLDN10 were related to effector differentiation of B cell, CD4 T cell, and CD8 T cell.

Correlation Analysis between claudins and the tumor microenvironment
To understand the role of claudins in immunity, we downloaded 379 RNA-seq FPKM (Fragments per kilobase per million) data of ovarian cancer from TCGA. Subsequently, the FPKM were converted to TPM (transcripts per million) [18] . ESTIMATE algorithm [19] was used to predict tumor purity based on TCGA ovarian cancer samples. Then, the relationship between claudins expression and tumor microenvironment was explored. As shown in Fig. 5A, a meaningful negative correlation between CLDN6 expression and immune score was observed (spearman correlation = -0.23, p < 0.001). And, there was a positive correlation between CLDN10 expression and immune score (spearman correlation = 0.21, p < 0.001) (Fig. 5B). Neither CLDN6 expression nor CLDN10 expression was correlation with stromal score. Immune score represents the in ltration of immune cells in tumor tissue.
Then, we examined the relationship between immune in ltration and claudins expression. RNA-seq TPM data (n = 379) from TCGA ovarian cancer were used to assess 22 immune cells subtypes concentrations through the CIBERSORT algorithm [20] . They were grouped by the median value of CLDN6 and CLDN10, respectively. Dendritic cells activated were found to be statistically signi cant different between CLDN6_high and CLDN6_low group. Several cell types were signi cantly different between the CLDN10_high and CLDN10_low group, including B cells naïve, B cells memory, T cells CD4 naïve, T cells CD4 memory activated, monocytes, M1 macrophage and dendritic cells activated Besides, the microarray expression values of ovarian cancer were used for calculation the abundances of six immune in ltrates (B cells, CD4 + T cells, CD8 + T cells, Neutrophils, Macrophages, and Dendritic cells) via TIMER algorithm [19] .
The gene expression levels correlated with tumor purity were displayed on the left-most panel ( Fig. 6A In order to more accurately describe the relationship of gene expression and immune cell in ltration, several methods including TIMER, CIBERSORT, quanTIseq, xCell, MCP-counter and EPIC algorithms were used to assess the immune in ltration of tumor tissue [21] . TIMER2.0 provides a platform for analysis immune in ltrates across diverse cancer types based on available TCGA RNA-seq data [22,23] . The correlations between claudins (CLDN6 and CLDN10) expression and various immune cells in ltration of ovarian cancer were shown in Table 2. As shown in Fig. 6C, CLDN6 was negative correlated to immune cell in ltration including B cell, CD8 + T cell, CD4 + T cell effector memory, M1 macrophage and myeloid dendritic cell. By contrast, CLDN10 was positive correlated to immune cell in ltration including B cell, CD8 + T cell, CD4 + T cell effector memory, M1 macrophage and myeloid dendritic cell (Fig. 6D).
Relevant evidences reported that cancer associated broblast (CAF) plays an important role in the progression of ovarian cancer [24,25] . Interestingly, we also found that CAF has a positive correlation with CLDN6 expression, but a negative correlation with CLDN10 expression. In ovarian cancer, increased in ltration of tumor-in ltrating lymphocytes (TILs) and more speci cally CD8 + T cells, has been proven to be associated with improved clinical outcome [26][27][28] .
These results suggest that CLDN6 and CLDN10 may participate in the immune cells in ltration of ovarian cancer, and these mechanisms may be the reasons for poor prognosis of ovarian cancer.

Relationship between claudins expression and gene markers of immune cells
To further illustrate the correlations between claudins (CLDN6 and CLDN10) and immune in ltration, we focused on the relationship between claudins (CLDN6 and CLDN10) and gene markers of various immune cells in ovarian cancer through the TIMER 2.0 databases. We analyzed the correlations between claudins (CLDN6 and CLDN10) expression and gene markers of different immune cells, including B cells, T cells (general), CD8 + T cells, macrophages, dendritic cells, neutrophils, monocytes, NK cells and Tregs in ovarian cancer ( Table 3). The purity-adjusted correlation heatmaps were shown on supplementary Fig. 2. After the correlation adjustment by purity, the results revealed the CLDN6 expression level was negatively correlated with most gene markers of dendritic cells, M1 macrophages, monocyte, NK cells, and tumor-associated macrophages (TAMs) in ovarian cancer. By contrast, the expression of CLDN10 was positive correlated with gene markers of dendritic cells, T cell (general) and TAMs in ovarian cancer.
Studies have shown that the in ltration of these immune cells in the tumor microenvironment is related to the tumor immunotherapy response [29] . Immune cell-based immunotherapy [30] including NK Cells [31] and dendritic cells [32] play important roles in the treatment of ovarian cancer. Taken these analyses together, our research showed that CLDN6 and CLDN10 may play important roles in immunotherapy in the future.

Discussion
Claudin-6 and claudin-10 are important components of the claudin family. Claudin-6 had been demonstrated overexpression in ovarian papillary serous carcinomas by immunohistochemistry [33] , and may be a novel targeted therapeutic for ovarian cancer as a receptor for clostridium perfringens enterotoxin (CPE) [34] . Previous research observed that claudin-10 is a glandular epithelial marker in epithelial ovarian cancer [35] . Studies have revealed that CLDN10 is not only related to OS of ovarian cancer, but also to the chemoresistance of ovarian cancer [36] . Recent evidences suggested that claudin-10 in an immune-related key gene and play a key role in the progression of papillary thyroid cancer [17,37] . Our research innovatively found that the prognostic potential of CLDN6 and CLDN10 were related to the tumor immune microenvironment in ovarian cancer.
In this study, we found that both CLDN6 and CLDN10 were high expression in ovarian cancer. Prognostic analysis showed that overexpression of CLDN6 is related to poor prognosis of patients with ovarian cancer. However, CLDN10 overexpression predicted better prognosis compared to CLDN10 low expression group. Then, our research found that CLDN6 overexpression was negatively related to immune in ltration, and CLDN10 overexpression was positive correlated to immune cell in ltration. Moreover, we identi ed that CLDN6 and CLDN10 were related to gene markers of dendritic cells, NK Cells and TAMs. These results may explain why the overexpression of CLDN6 and the low expression of CLDN10 predict poor overall survival of ovarian cancer.
Relevant evidence has emerged that immune-related gene expressions and TILs were related to prognosis, recurrent [38] and chemotherapeutic response [39] of ovarian cancer. Growing evidence shown that the presence of TILs may improve clinical outcome of ovarian cancer patients [40] . Immune cell-based immunotherapy [30] including NK Cells [31] and dendritic cells [32] play important roles in the treatment of ovarian cancer. Our results suggested that CLDN6 may be involved in tumor immune evasion, and may represent ideal candidate for immunotherapy in ovarian cancer. Further studies on the combined application of molecular targeted therapy and immunotherapy may be meaningful.

Conclusions
Page 7/27 CLDN6 and CLDN10 were prognostic biomarkers, and correlated with immune in ltration in ovarian cancer. Our results revealed new roles for CLDN6 and CLDN10 in ovarian cancer, and they were potential therapeutic targets in the treatment of ovarian cancer.    Treg: Regulatory T cell; *P < 0.05; **P < 0.01; ***P < 0.001 Figure 1 The  Gene set enrichment analysis (GSEA) of c7 (immunologic signatures) for CLDN6 and CLDN10.  Supplementary Files