Claudins family as potential prognostic indicators in ovarian cancer by bioinformatics analysis

doi:10.21203/rs.3.rs-1612879/v1

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Claudins family as potential prognostic indicators in ovarian cancer by bioinformatics analysis

https://doi.org/10.21203/rs.3.rs-1612879/v1

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To evaluate the expression of ten claudins(CLDNs) family members including CLDN1/3/4/5/6/7/9/10/11/16 and their prognostic and functional impacts on ovarian cancer (OC) patients,we applied GEPIA,HPA,KM plotter,STRING,Metascape,Kobas and cBioPortal databases to analyze that the mRNA and protein levels of CLDN1/3/4/7/16 expression were significantly upregulated in OC samples;the mRNA level of CLDN6/9/10 were highly expressed in OCs, however, CLDN5/11 were low expressed in OCs.Further,Kaplan-Meier plotter analysis revealed that CLDN3/4/10/16 were significantly associated with progression free survival(PFS) and overall survival(OS) of patients with OC.CLDN1/6/7 were significantly related to PFS of women with OC.Moreover,the anomalous mRNA expression of CLDN1/3/4/6/10/11/16 were linked to markedly prognosis in OC patients taking diverse chemotherapeutic drugs.CLDN1/3/4/6/7/9/10/11/16 were closely related to FIGO stages in OC patients.Then,Gene ontology(GO) and KEGG analysis showed that the CLDNs played important roles in tumor metastasis,immune response process and cellular adhesion process in ovarian cancer.The ten claudins protein family possessed eminent mutual connectivity in PPI,and it may be necessary to analyze CLDN protein family as a whole complex.The different genetic alterations of CLDNs comprised 1.37% mutation,31.16% amplification,0.17% structural variant,1.37% deep deletion,0.51% multiple alterations.Additionally,Our results of mRNA high-throughput sequencing confirmed that CLDN3/4/7 was significantly upregulated in ovarian cancer and could be used as marker genes,and related functions and pathways involved in the epithelial cell differentiation, immune response and cell tight junction.Our study confirms that the CLDNs is significant prognostic value for OC patients.CLDNs is linked to the epithelial cell differentiation,tumor metastasis and immune response of ovarian cancer,and could have a potential application prospect in immunotherapy of ovarian cancer.

CLDN

ovarian cancer

bioinformatics analysis

Ovarian cancer(OC) is the most lethal malignant cancer in gynecological tumors[1].Globally, about 239,000 new cases are diagnosed and 152,000 women die of this disease every year[2].Due to the asymptomatic nature of early ovarian cancer and lack of reliable tumor screening biomarkers, most ovarian cancer is diagnosed at advanced stage[3].The standardized treatment for ovarian cancer is operation combined with platinum-based chemotherapical treatment,however,the 5-year survival rate of OC patients is about 47%, mainly as a result of recurrence and chemotherapy resistance[4].In recent years, with identification of the breast cancer BRCA gene and homologous recombination deficiency (HRD),new therapies have emerged in the field of poly ADP-ribose polymerase (PARP) inhibitors[5-7].The immunotherapy and heated intraperitoneal chemotherapy(HIPEC)[8] have revolutionized the therapeutic model of epithelial ovarian cancer(EOC) and significantly improve the survival rate of patients generally considered to be a fatal cancer.Therefore, reliable prognostic biomarkers for OC are essential for the efficient intervention and treatment of patients to improve clinical outcomes.

Claudin (CLDN) family can form tight-junction chains, so it represents the backbone of tight junctions in various types of cells, especially vertebrate epithelial cells and endothelial cells[9].CLDN family includes 27 members in mammals and has some specific combinations expressed in given cell/tissue types[10].CLDNs are extremely important for human health, and when they are dysregulated, that can lead to the pathogenesis and progression of diverse tumors through anomalous CLDN signaling[11-15].For example, CLDN1 gene knockdown could enhance chemotherapy sensitivity,and inhibit cell proliferation and migration(p<0.05).The relation between methylation and expression of CLDN1 is extremely important in the invasiveness and recurrence of OC[16].Overexpression of CLDN4 in advanced ovarian cancer predicts shorter 5-year overall survival(OS) and progression-free survival(PFS) in univariable analyses[17].However,according to what we are informed, there is no correlational study by using bioinformatics analysis to comprehensively explore the impact of CLDN family on the occurrence and development of OC.

In this study, we aimed to analyze available online mRNA and protein expression datasets to explore the different expression of CLDNs in OC tissues and normal ovarian samples.In addition, we evaluated the prognostic impact of CLDN family mRNA on OC patients and its correlation with clinicopathological factors in OC patients. Moreover,we also predicted possible functions and pathways involved in CLDNs mutations.The present study provided the potential molecular mechanisms of tumorigenesis and progression of OC and the novel drug therapeutic targets for OC.

2.1 GEPIA.

The transcriptional expression of CLDNs in 426 OC tissues and 88 cancer-free ovarian tissues from GTEx project and TCGA database were analyzed by the Gene Expression Profiling Interactive Analysis(GEPIA)(http://gepia.cancer-pku.cn).The criteria for statistical differences was p＜0.01(T-test) and Log2 Fold Change(|Log2FC|) cutoff was＞2.

2.2 HPA.

The Human Protein Atlas(HPA)(https://www.proteinatlas.org) is an open public database that shows the protein expression level of CLDNs in OC and cancer-free ovarian tissues by immunohistochemistry.In our study, we revealed the protein expression level of the CLDN family in human cancer-free ovarian tissues and serous cystadenocarcinoma(NOS) tissues to evaluate whether the protein expression level of CLDNs is consistent with that of mRNA from the GEPIA.

2.3 KM Plotter.

We used KM plotter(http://kmplot.com/analysis/) to analyze OS of 1656 OC patients and PFS of 1435 OC patients at the each CLDN mRNA levels,moreover,also explored the correlation between CLDNs and clinical parameters.In detail,clinical parameters include pathological subtype, histological grade, clinical stage, TP53 mutant/wild type and chemotherapeutic drugs that were collected from this database.Based on the best cutoff for automatic matching,the samples were divided into two groups of low-expression and high-expression.The hazard ratio (HR),95% confidence interval (95% CI), and p value were exhibited.p< 0.05 showed statistical difference.

2.4 Establishment of PPI network.

The interaction among CLDN family proteins was analyzed by STRING PPI network (https://string-db.org/).The minimum combined score was 0.4 considered statistically significant.

2.5 GO enrichment and KEGG pathway analysis.

Gene ontology(GO) enrichment analysis of CLDNs was performed by Metascape database. KEGG pathways were enriched of CLDNs by Kobas (KEGG ontology based annotation system) database.GO enrichment and KEGG pathway analysis were visualized in bar chart. p value < 0.05 was considered statistical difference.

2.6 cBioPortal for Cancer Genomic Alterations.

The cBioPortal (http://cbiop ortal .org) is a procurable datasets for interactive exploration of multiple cancer genomics.Genomic alteration types and alteration frequency in OC were analyzed through the cBioPortal database.The genomic alterations of CLDNs comprised mutation,amplification,structural variant,deletion and multiple alterations.

2.7 mRNA high-throughput sequencing to verify the expression and function of CLDNs in OC

The collection of 4 pairs of pathologically confirmed fresh ovarian cancer and cancer-free ovarian samples from the Liaoning Cancer Hospital was performed by mRNA high-throughput sequencing technology with the approval of Medical Ethics Committee Of Liaoning Cancer Hospital(Approval No.20220245),and in accordance with all relevant guidelines and regulations.All patients participating in this study signed informed consent forms. We also analyzed the differential genes between ovarian cancer and normal ovary by volcanic plot and heat map, and the related KEGG signal pathway and GO biological function of the differential gene sets enriched by GSEA.The mRNA library sequencing was performed on the Illumina NovaSeq6000 by Gene Denovo Biotechnology Co.,Ltd (Guangzhou, China).

2.8 Statistical analysis

The CLDNs expression levels of OC tissues and cancer-free ovarian tissues were compared by unpaired t-test.Log-Rank test was used to draw Kaplan-Meier survival curves for survival analysis.p< 0.05 was considered statistical difference.

3.1. CLDN mRNA and protein expression in patients with OC.

We analyzed the mRNA expression of the CLDNs in OCs compared to normal ovarian tissues by using GEPIA database,CLDN1/3/4/6/7/9/10/16 were highly expressed in OCs (p<0.05), however, CLDN5 and CLDN11 were low expressed in OCs (p<0.05)(Figure 1A-J).With available immunohistochemical staining by HPA, we estimated the CLDNs protein expression between NOS and normal ovary(Figure 2).The immunohistochemical staining images other than CLDN6 and CLDN9 cannot be obtained in the HPA,other CLDN protein images are available.CLDN1/3/4/7/16 were overexpressed in NOS tissues compared to normal ovarian tissues;CLDN3/4/7/16 showed negative staining in normal ovarian tissues.

3.2 survival analysis of CLDNs in patients with OC.

Further,we analyzed the effect of CLDNs mRNA expression on the prognosis of patients by KM plotter.The results revealed that CLDN3/4/10/16 were prominently associated with OC patients` OS and PFS.The results also showed that CLDN1,CLDN6 and CLDN7 were significantly related to PFS of women with OC.The expression level of CLDN5,CLDN9 and CLDN11 had no correlation with prognosis of OC patients(Figure 3 a-t).

The prognostic impact of CLDN1 mRNA was assessed(Figures 3(a) and 3(b),and Table S1). The up-regulation of CLDN1 was associated with worsen PFS in all OCs, serous OCs,clinical stage III+IV,pathological grade 2,TP53 mutated patients.Additionally,the up-regulation of CLDN1 mRNA indicated worse OS in patients received taxol,and worse PFS in patients treated with taxol ,platin and taxol+platin chemotherapy.

We found that up-regulation of CLDN3 was linked to worsen OS and PFS of patients with all OCs and TP53 wild type;In addition,serous histologyical type and receiving platin chemotherapy OC patients who had worse PFS,and the OC patients with clinical stage III+IV and receiving taxol chemotherapy had worse OS. (Figures 3(c) and 3(d) and Table 1)

Table 1. The prognostic value of the CLDN3 mRNA expression in ovarian cancer

	Cases	Overall survival HR (95% CI)	p value	Cases	Progression-free survival HR (95% CI)	p value
Histology
All ovarian cancers	1656	1.14(1-1.3)	0.045*	1435	1.16(1-1.33)	0.043*
Serous OC	1207	1.15(0.99-1.34)	0.065	1104	1.2(1.03-1.4)	0.019*
Endometrioid OC	37	3.03(0.5-18.16)	0.2	51	2.94(0.67-12.77)	0.13
Clinical stage
I+II	135	0.52(0.24-1.12)	0.09	163	0.64(0.35-1.18)	0.15
III+IV	1220	1.19(1.02-1.39)	0.023*	1081	1.11(0.95-1.3)	0.2
Pathological grades
1	56	0.52(0.2-1.33)	0.16	37	1.87(0.41-8.46)	0.41
2	324	1.14(0.84-1.54)	0.4	256	1.11(0.8-1.54)	0.52
3	1015	1.11(0.94-1.32)	0.21	837	1.15(0.96-1.38)	0.12
TP53
mutated	506	1.21(0.95-1.56)	0.13	483	1.25(0.99-1.58)	0.055
Wild type	94	0.55(0.31-0.97)	0.037*	84	0.47(0.27-0.81)	0.0054**
Chemotherapy
taxol	793	1.26(1.01-1.57)	0.041*	715	1.1(0.91-1.32)	0.33
platin	1409	1.14(0.99-1.31)	0.072	1259	1.17(1.02-1.36)	0.03*
taxol+platin	776	1.22(0.99-1.51)	0.066	698	1.11(0.92-1.34)	0.29

*p＜0.05；**p＜0.01；***p＜0.001；****p＜0.0001

The prognostic impact of CLDN4 was assessed(Figures 3(e) and 3(f) and Table 2). over- expressed CLDN4 was related to worsen OS and PFS of patients with all OCs, serous OCs,clinical stage III+IV,pathological grade 3,TP53 mutated and receiving taxol,platin and taxol+platin chemotherapy regimens.Elevated CLDN4 also showed OC patients with worse OS in histological grade 2 and worse PFS in histological grade 1.

Table 2. The prognostic value of the CLDN4 mRNA expression in ovarian cancer

	Cases	Overall survival HR (95% CI)	p value	Cases	Progression-free survival HR (95% CI)	p value
Histology
All ovarian cancers	1656	1.34(1.18-1.54)	1.2e-05****	1435	1.22(1.06-1.41)	0.0047**
Serous OC	1207	1.35(1.15-1.59)	3e-04***	1104	1.46(1.24-1.72)	3.5e-06****
Endometrioid OC	37	4.75(0.79-28.46)	0.06	51	2.18(0.86-5.55)	0.092
Clinical stage
I+II	135	0.51(0.23-1.13)	0.089	163	1.25(0.7-2.25)	0.45
III+IV	1220	1.38(1.18-1.61)	4.8e-05****	1081	1.41(1.21-1.65)	1.2e-05****
Pathological grades
1	56	0.71(0.25-2.04)	0.53	37	3.71(1.23-11.2)	0.013*
2	324	1.7(1.25-2.31)	0.00062***	256	1.39(0.99-1.94)	0.054
3	1015	1.35(1.14-1.61)	0.00063***	837	1.38(1.15-1.66)	0.00061***
TP53
mutated	506	1.45(1.13-1.84)	0.0027**	483	1.93(1.52-2.46)	4.9e-08****
Wild type	94	0.76(0.44-1.32)	0.32	84	1.25(0.74-2.11)	0.4
Chemotherapy
taxol	793	1.34(1.11-1.62)	0.0023**	715	1.3(1.08-1.57)	0.006**
platin	1409	1.38(1.19-1.59)	1.2e-05****	1259	1.27(1.1-1.46)	0.00095***
taxol+platin	776	1.33(1.1-1.62)	0.0033**	698	1.31(1.09-1.59)	0.005**

*p＜0.05；**p＜0.01；***p＜0.001；****p＜0.0001

We explored the effect of CLDN5 mRNA on prognosis of OC patients(Figures 3(g) and 3(h) and Table S2).The OC patients with pathological grade 3 and TP53 wild type had worse OS.High expression of CLDN5 was related to worsen PFS of patients with serous OCs,pathological grade 1 and TP53 mutated.

The prognostic impact of CLDN6 was estimated(Figures 3(i) and 3(j) and Table S3). Elevated CLDN6 mRNA was associated to worsen OS of OC women with endometrioid Histological subtype,pathological grade 2 and receiving platin chemotherapeutic treatment.Up-regulation of CLDN6 also showed worse PFS in OC patients with all OCs,serous OCs,endometrioid OCs,all clinical stages,pathological grade 2/3,all TP53 states,receiving taxol,platin and taxol+platin chemotherapeutic treatments.

Next,we evaluated the prognostic effect of CLDN7 mRNA on OC patients(Figures 3(k) and 3(l) and Table S4).The Endometrioid histology and all clinical stages were related to OC patients` worse OS.Overexpression of CLDN7 was related to worse PFS of patients with all OCs,pathological grade 3 and all TP53 states.

Further,we assessed the impact of CLDN9 mRNA on prognosis of OC women(Figures 3(m) and 3(n) and Table S5).The patients with TP53 mutation had worse OS,and with serous,endometrioid OCs,all clinical stages,pathological grades 2/3 and all TP53 states had worse PFS.

The prognostic effect of CLDN10 mRNA was also estimated(Figures 3(o) and 3(p) and Table 3).The up-regulation of CLDN10 was linked to worsen OS and PFS of patients with all OCs,serous OCs,TP53 wild type and receiving platin chemotherapy.Up-regulation of CLDN10 also showed worse OS in women with clinical stage III+IV,pathological grade 1/3,and worse PFS in patients with TP53 mutation.

Table 3. The prognostic value of the CLDN10 mRNA expression in ovarian cancer

	Cases	Overall survival HR (95% CI)	p value	Cases	Progression-free survival HR (95% CI)	p value
Histology
All ovarian cancers	1656	0.73(0.64-0.83)	1.6e-06****	1435	0.83(0.73-0.95)	0.0067**
Serous OC	1207	0.76(0.65-0.89)	0.00045***	1104	0.83(0.72-0.96)	0.013*
Endometrioid OC	37	0.23(0.04-1.36)	0.076	51	2.31(0.86-6.15)	0.086
Clinical stage
I+II	135	0.59(0.26-1.33)	0.2	163	0.54(0.29-1.01)	0.05
III+IV	1220	0.81(0.7-0.94)	0.0051**	1081	0.91(0.79-1.05)	0.19
Pathological grades
1	56	0.35(0.13-0.9)	0.023*	37	-	0.0075
2	324	0.75(0.55-1.03)	0.078	256	0.74(0.54-1.02)	0.061
3	1015	0.72(0.61-0.85)	8.7e-05****	837	0.9(0.75-1.07)	0.22
TP53
mutated	506	0.86(0.69-1.08)	0.21	483	1.36(1.07-1.74)	0.013*
Wild type	94	0.56(0.32-0.99)	0.044*	84	0.53(0.3-0.94)	0.028*
Chemotherapy
taxol	793	0.83(0.68-1.02)	0.07	715	1.17(0.97-1.42)	0.11
platin	1409	0.75(0.65-0.87)	7.4e-05****	1259	0.85(0.74-0.98)	0.021*
taxol+platin	776	0.83(0.67-1.01)	0.063	698	1.15(0.95-1.4)	0.15

*p＜0.05；**p＜0.01；***p＜0.001；****p＜0.0001

Then,we estimated the impact of CLDN11 mRNA on prognosis of OC patients(Figures 3(q) and 3(r) and Table S6).Elevated CLDN11 was related to worse OS of patients with clinical stage III+IV.Up-regulation of CLDN11 was associated with worse PFS of patients with serous OCs,all clinical stages,pathological grade 3,all TP53 states and receiving platin chemotherapy.

Finally,we evaluated the prognostic impact of CLDN16 mRNA on OC patients(Figures 3(s) and 3(t) and Table 4).All OCs,taxol ,platin and taxol+platin chemotherapeutic treatments were linked to OC patients` worsen OS and PFS.The OC women with pathological grade 1 and TP53 mutated had worse OS,and with endometrioid OC,Clinical stage I+II and pathological grade 3 had worse PFS.

Table 4. The prognostic value of the CLDN16 mRNA expression in ovarian cancer

	Cases	Overall survival HR (95% CI)	p value	Cases	Progression-free survival HR (95% CI)	p value
Histology
All ovarian cancers	1656	1.16(1.02-1.32)	0.02*	1435	1.33(1.17-1.51)	8.3e-06****
Serous OC	1207	0.93(0.79-1.08)	0.33	1104	1.11(0.96-1.29)	0.15
Endometrioid OC	37	0.42(0.07-2.51)	0.33	51	3.75(1.47-9.54)	0.003**
Clinical stage
I+II	135	1.93(0.88-4.22)	0.094	163	2.08(1.17-3.68)	0.01*
III+IV	1220	1.08(0.93-1.25)	0.34	1081	0.94(0.81-1.1)	0.45
Pathological grades
1	56	2.85(1.07-7.56)	0.028*	37	20.34(2.61-158.19)	6.2e-05
2	324	1.33(0.97-1.82)	0.077	256	1.35(0.96-1.9)	0.084
3	1015	0.87(0.74-1.03)	0.11	837	1.2(1.01-1.43)	0.042*
TP53
mutated	506	0.76(0.59-0.97)	0.028*	483	0.84(0.65-1.07)	0.16
Wild type	94	1.26(0.72-2.22)	0.41	84	0.68(0.4-1.16)	0.15
Chemotherapy
taxol	793	1.32(1.06-1.64)	0.012*	715	1.23(1.03-1.48)	0.023*
platin	1409	1.2(1.04-1.38)	0.012*	1259	1.23(1.08-1.41)	0.0015**
taxol+platin	776	1.32(1.06-1.64)	0.014*	698	1.25(1.04-1.51)	0.016*

*p＜0.05；**p＜0.01；***p＜0.001；****p＜0.0001

3.3 Prediction of the PPI networks of CLDNs

Next, we used STRING to reveal the potential interactions of CLDNs family members in the protein-protein interaction (PPI) network.Perhaps most exciting discovery was that ten claudins protein-protein interacting with each other that were obtained by nodes and edges (Figure. 4A). Claudins protein family may act as nodes with eminent mutual connectivity in the PPI network,therefore, we believed that quantitative and systematic analysis of claudins protein as a whole complex was highly necessary.

3.4 GO enrichment analysis and KEGG pathways of CLDNs

To obtain comprehensive biological properties of ten CLDNs, the enrichment analysis of GO functions and KEGG signal pathways were performed through Metascape and Kobas (KEGG ontology based annotation system) database.The results of KEGG pathway enrichment analysis by using Kobas database demonstrated that TOP5 pathways of CLDNs included Leukocyte transendothelial migration,Cell adhesion molecules(CAMs),Hepatitis C,Tight junction,Pathogenic escherichia coli infection(Figure 4B).The GO enrichment analysis showed that CLDNs differentially enriched in biological adhesion,cellular process,positive regulation of biological process,multicellular organismal process,viral process,biological process involved in interspecies interaction between organisms,response to stimulus,locomotion,localization(Figure 4C).Both KEGG and GO results revealed the CLDNs played important roles in the functions of tumor metastasis,immune response process and cellular adhesion process in ovarian cancer.

3.5 Analysis of genetic alterations of CLDNs

With the cBioPortal open tool for OC cohort in TCGA to analyze the CLDNs alterations and correlations, we found that different genetic alterations of CLDNs comprised 1.37%(8 cases) mutation,31.16%(182 cases) amplification,0.17%(1 case) structural variant,1.37%(8 cases) deep deletion,0.51%(3 cases) multiple alterations. CLDNs were changed in 202 specimens out of 584 OC women(35%).CLDN11(24%) was the most frequently altered genes in the all CLDN family members,including amplification and missense mutation.CLDN16(15%) was the second most frequently altered genes and also included amplification and missense mutations. Amplification was the most frequent gene alteration of CLDN1(15%)(Figure 5).

3.6 mRNA high-throughput sequencing verified CLDN3/4/7 may be useful markers in OC

By mRNA high-throughput sequencing,the results showed that CLDN3, CLDN4 and CLDN7 were indeed significantly highly expressed top genes in ovarian cancer, which was consistent with the prediction results of the previous databases(Figure 6A).Other significantly elevated genes in OC included RUNX1,NLRP3,EBI3,TLR7 and et al,which may be used as potential marker genes(Figure 6C).The results of Gene sets enrichment analysis of KEGG pathways showed that differential gene sets were mainly related to tight junction pathway(Figure 6B).In addition,Gene sets enrichment analysis of GO functions demonstrated that capital GO enrichment in the biological process(BP) including epithelial cell differentiation,epithelium development,antimicrobial humoral response,FC epsilon receptor(FcεR) signaling pathway,immunoglobulin production,cell fate commitment(Figure 6D)

In recent years, PARP inhibitors (PARPi) seems to be a prospective choice for the treatment of EOCs in BRCA mutation and BRCA wild-type[18]. Despite more and more clinical trials and approved reagents, PARPi has limited efficacy due to treatment merely prolongs survival time for several months and does not bring any long-term benefits[19].The resistance of BRCA-related tumors to PARPi shows that this therapy could not be as efficacious as previously thought[20-22].Studies have reported that in addition to BRCA1/2, there are other genes involved in homologous recombination repair (HRR),such as Rad51,Rb1,ATR,ATM,Fanconi anemia,BARD1,BRIP1,NF1,PALB2,EMSY,CDKN2A[23,24].The recovery of HR pathway function or the HR genes reversal mutation has been proved to be the main mechanism of acquired platinum chemotherapy resistance[25].Therefore,to explore more therapeutic approaches and drug resistance mechanisms that can effectively target molecular vulnerabilities of resistant OC for improving the prognosis of patients[26].

With the development and wide application of high-throughput technology, more and more kinds of public databases appear, such as GEO,TCGA,GEPIA,oncomine,cBioPortal,HPA,KM Plotter and et al,which makes it very convenient to obtain the datas of genomics, transcriptomics and proteomics from these databases.As far as we know, we take the lead in appling bioinformatic techniques to comprehensively evaluate the impact of CLDNs on patients with OC.

Claudins(CLDNs),a group of cellular tight junction(TJ) proteins, are able to transfer mechanical strength,maintain cellular polarity and paracellular movement[27].The alterations of tight junction structure and function may lead to multiple of diseases, especially adenocarcinoma of various organs[28, 29].In the process of tumor metastasis, tight junctions around tumor cells could be destroyed or "loosened" to induce diffusion and migration.Therefore, claudins, comprising CLDN1,CLDN3,CLDN4,CLDN6,CLDN7,CLDN8,CLDN10,CLDN14 and CLDN17, can play a key role in tumorigenesis and metastasis[13, 30-35].

In this study, we analyzed the differential expression of CLDNs between OC specimens and cancer-free ovarian tissues,and contrary to the widely believed that CLDNs expression would down-regulate during tumorigenesis and metastasis[28],however,the results of our analysis showed that the mRNA and protein level of CLDN3,CLDN4,CLDN7 and CLDN16 were remarkably up-regulated in OC tissues except that the mRNA expression of CLDN5 and CLDN11 was down-regulated.This seems to be explained by alterations of claudins expression in a tissue-specific manner which is related to the two opposite effects of tumor-promoter or tumor-suppressor produced by molecular interactions[15].For example,CLDN7 deficiency accelerates experimental colitis and related tumorigenesis by regulating the integrity of intestinal epithelium[36].CLDN7 can also be highly expressed in the dominant cell population with rapid proliferation in human pancreatic cancer[37].Claudin-3 depletion decreased tumor cellular stemness and increased cisplatin sensitivity in nonsquamous non-small-cell lung(NSCLC)[38].The overexpression of CLDN4 was associated with tumor invasion, lymph node and distant metastasis in pancreatic ductal carcinomas (PDC)[39].One acceptable mechanism is that upregulation or abnormal tissue expression of some claudin proteins may lead to neoplasia by directly changing the structure and function of TJ. Furthermore, it is postulated that claudins may also affect cell signaling pathways[28].

According to the results of GO and KEGG pathway enrichment analysis, we found that CLDNs were closely related to epithelial cell differentiation,tumor immunity and metastasis.As we know,tumor metastasis is related to the aggressive behavior of tumors, in which cell membrane proteins, receptors and extracellular matrix (ECM) proteins serve key biological functions[40].The crosstalk between ovarian cancer cells (endogenous) and tumor microenvironment components (exogenous) is involved in reprogramming immune responses and accelerating tumor growth and metastasis. The ways of tumor-microenvironment communication primarily include both indirect cytokine-mediated interaction and direct intercellular communication between tumor cells and stromal cells,which play important roles in promoting the invasion and metastasis of ovarian cancer[41].Immunotherapy raises the anti-cancer immune response through various methods, such as immune stimulating cytokines, neoplasma antigen vaccines and immune checkpoint inhibition (ICI).ICIs include cytotoxic T lymphocyte associated protein 4 and its ligands (CTLA-4:B7/CD80) and programmed death receptor-1 and its ligand(PD-1:PD-L1)[42].Genomic variations occurring in tumor cells may produce tumor antigens, which can be recognized by the immune system as nonself antigen and trigger cellular immune response to kill tumor cells[43-45].However,tumor cells reduce local immune responses and permit immune escape by upregulating immune checkpoints[46].By combining CTLA-4 and PD-1 or PD-L1,ICIs prevent the interreaction between tumor cells and T cells, thus restoring T cell cytotoxicity[47, 48].

The studies of IMagyn050/GOG3015/ENGOT-OV39 and the JAVELIN Ovarian 100 trial failed to demonstrate the significant benefit of PD-L1 inhibitor in patients with advanced ovarian cancer,therefore the application of ICIs in ovarian cancer requires other biomarker efficiency analysis to define the potentially susceptible crowd[49, 50].Ovarian cancer has a limited response to immunotherapy,however, the appraisement of susceptible/resistant targeted therapy subsets based on tumor biomarker stratification could enhance the predictability of immunotherapy response.That will bring new therapeutic opportunities for OC patients with chemotherapy or targeted drug resistance.Consequently,it is necessary to combine immunotherapy with chemotherapy, radiation, anti-angiogenesis reagent and PARPi[51].Studies have confirmed that platinum-based chemotherapy may block STAT6 mediated immunodepression in the tumor microenvironment by downregulating PD-L2 expression on human dendritic cells and cancer cells,thus reinforcing the ability of T cells to recognize and kill tumors[52, 53].Paclitaxel chemotherapy increases the infiltration level of CD8+ T cells in mouse models of ovarian cancer by upregulating the expression of MHC-I and PD-L1, that may also improve the immunotherapeutic efficacy of ovarian cancer[54].Earlier studies have confirmed that VEGF upregulates PD-1 expression in the intratumoral CD8+ T cells, which may be downregulated via anti-VEGF drugs[55].In patients with advanced melanoma, the combined application of ipilizumab(a CTLA-4 inhibitor) and bevacizumab(an anti-VEGF drug) can strengthen the accumulation and infiltration of T cells,and the expression of intracellular adhesion molecule 1 (ICAM1) and vascular cell adhesion protein 1 (VCAM1) which both limiting the transmigration of tumor-infiltrating lymphocytes(TILs).In addition, specific cytokines essential for cancer interference,including C-X-C Motif Chemokine 10(CXCL10),tumor necrosis factor-alpha (TNF-α) ,interleukin-1 alpha (IL-1α) and et al, were increased significantly after the combined therapy of ipilimumab and bevacizumab(Ipi-Bev)[56].PARPi has been proved to strengthen tumor antigenicity which can sensitize tumors to ICI therapies and improve the curative effect of HRD-related OCs to immunotherapy by producing a higher mutation burden, which can increase neoantigen expression[51].In a phase I/II TOPACIO trial,the combined treatment of Niraparib and pembrolizumab is promising antitumor activity and tolerable for ovarian carcinoma patients,and objective response rate(ORR) was 18% (90% CI, 11%-29%) and disease control rate(DcR) was 65% (90% CI, 54%-75%)[57].

In conclusion, our study is the first to confirm that CLDN family is linked to the tumor metastasis and immune response of ovarian cancer,and CLDNs may have potential application prospects in immunotherapy of ovarian cancer.CLDNs may play opposite roles of cooperation and confrontation in ovarian cancer metastasis and immune response through protein interaction.Moreover,the anomalous mRNA expression of CLDN1/3/4/6/10/11/16 was prominently linked to prognosis of OC patients receiving different chemotherapeutics.CLDN1/3/4/6/7/9/10/11/16 was closely related to FIGO stages in OC patients.CLDN3/4/10/16 are markedly related to OC patients` prognosis and can be managed as prognostic markers.These novel discoveries not only reveal the molecular alterations and interaction relationships in CLDNs but also afford the theoretical basis for future research in this field.Our mRNA high-throughput sequencing results further verified the significant upregulation of CLDN3/4/7 in ovarian cancer.The enrichment analysis of differential gene sets between ovarian cancer and normal ovarian samples considered that CLDNs may regulate the occurrence, development and treatment outcome of ovarian cancer by participating in immune response, epithelial differentiation and tight junction pathway.

Competing Interests Statement

The authors declare no competing interests.

Author contributions

Conception and design of the study: Q.L, X.Z. Data acquisition and analysis: Q.L. Interpretation of data: Q.L.Drafting the work: Q.L.Revising it critically for important intellectual content: X.Z. Study supervision: X.Z. All authors approved the final version of the manuscript.

Funding

This research was supported by grants from the Science and Technology Planning Project of Shenyang (Grant No. 1900971).

Data Availability

Our datasets of Bulk tissue Transcriptome sequencing generated and analysed during the current study are available in the GEO database,https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE203130,the accession number is GSE203130,the token number is qvsxcmscvhetpgj.

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No competing interests reported.

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Claudins family as potential prognostic indicators in ovarian cancer by bioinformatics analysis

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