Front. Oncol.Frontiers in OncologyFront. Oncol.2234-943XFrontiers Media S.A.10.3389/fonc.2022.1081510OncologyOriginal ResearchThe upregulation of CLGN in hepatocellular carcinoma is potentially regulated by hsa-miR-194-3p and associated with patient progressionCuiZhongyuan1†WangJielong1†ChenGang2LiDongliang1ChengBianqiao3*LaiYanhua4*WuZhixian1*1Department of Hepatobiliary Disease, Dongfang Hospital, School of Medicine, Xiamen University, Fuzhou, China2Department of Gastroenterology, Liuzhou Workers’ Hospital (The Fourth Affiliated Hospital), Guangxi Medical University, Liuzhou, China3Department of Gastroenterology, Fuzhou Second Hospital, Fuzhou, China4Department of Transplantation, People’s Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China
Edited by: Wenyu Lin, Massachusetts General Hospital and Harvard Medical School, United States
Reviewed by: Linbin Lu, Xijing Hospital, China; Xiaoqiong Duan, Institut National de la Transfusion Sanguine, France
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Background
Patients with hepatocellular carcinoma (HCC) have poor prognosis, especially in advanced stages. Targeted therapy is the main treatment for advanced HCC patients, but the optimal targets for HCC remain poorly understood. The main purpose of this study was to identify potential novel prognostic markers and therapeutic targets.
Methods
Firstly, differentially expressed genes (DEGs) in HCC were identified from the Gene Expression Omnibus (GEO) database. The expression, significance in prognosis, and potential mechanisms of DEGs were analyzed using GEPIA, TIMER, HPA, Kaplan Meier Plotter, CBioPortal, miRWalk, TargetScan, and ENCORI databases. Immunohistochemical staining was used to determine the protein expression levels of potential candidate genes.
Results
The mRNA levels of MND1, STXBP6, and CLGN were significantly increased in HCC (p< 0.01). HCC patients with elevated CLGN mRNA levels had poorer overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and disease-specific survival (DSS) (p < 0.05). Higher MND1 mRNA levels significantly correlated with poorer DFS in HCC patients (p< 0.05). However, there was no significant correlation between STXBP6 expression and prognosis of HCC (p> 0.05). Further analysis revealed that patients with elevated CLGN mRNA expression in advanced pathology stages had poorer prognosis (p< 0.01). In addition, CLGN protein levels were elevated in HCC compared to their levels in normal tissues. The mRNA levels of CLGN had no significant correlation with the abundance of six common tumor infiltrating lymphocytes in HCC (COR < 0.5). Moreover, the mutation rate of CLGN was less than 1% in HCC patients (10/1089). Finally, the expression level of hsa-miR-194-3p in HCC was significantly lower than that in normal tissues (p < 0.05), and prognosis of HCC with low expression of hsa-miR-194 was poor (p < 0.05).
Conclusion
The upregulation of CLGN in HCC is significantly associated with poor patient prognosis, especially in the advanced stages, and may be regulated by hsa-miR-194-3p. These findings suggest that CLGN may be closely related to the progression of HCC, and is a potential therapeutic target and prognostic indicator for patients with advanced HCC.
Primary liver cancer remains the sixth most common cancer and the third leading cause of cancer-related deaths worldwide in 2020, according to the latest statistics (1). Hepatocellular carcinoma (HCC) encompasses 75% -85% of liver cancer cases (1). Most HCC is in advanced stages at the time of diagnosis and is resistant to conventional cytotoxic drugs. Currently, systemic therapy for patients with advanced HCC includes molecularly targeted agents, immune checkpoint inhibitors, or a combination of both (2–4). However, a substantial proportion of patients have yet to benefit from systemic therapy (5, 6). Recent studies have identified several novel biomarkers that can predict HCC prognosis. Lu et al. showed that serum α-fetoprotein trajectories were associated with overall survival of patients with intermediate-stage HCC after transarterial chemoembolization (7). However, it is imperative to identify the most effective predictive biomarkers to facilitate individualized and targeted treatments. Therefore, it is necessary to screen more biomarkers to improve patient diagnosis, and prognosis and identify therapeutic targets for precision therapy.
In recent years, bioinformatic databases have provided abundant transcriptomic and clinical data (8, 9), which are convenient for the analysis of relevant markers with potential significance (10–12). In this study, we explored several databases for molecular markers of HCC and investigated their expression levels in clinical specimens.
MethodsScreening of DEGs in HCC patients
Tumor and normal tissue Gene expression datasets GSE54236 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE54236) (13) and GSE121248 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121248) were downloaded from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) (14). D ifferentially expressed genes (DEGs) were analyzed using the online tool GEO2R. Gene Expression Profiling Interactive Analysis (GEPIA, http://gepia.cancer-pku.cn/) (15) and Tumor Immune Estimation Resource database (TIMER, https://cistrome.shinyapps.io/timer/) (16) were used to further verify the DEGs. A p-value of <0.05 was statistically significant.
The significance of DEGs in the prognosis of HCC
GEPIA was used to analyze the relationship between DEGs and overall survival (OS) and disease-free survival (DFS) in HCC patients. Kaplan Meier Plotter (http://kmplot.com/analysis/index.php?p=service&cancer=liver_rnaseq) (17) was used to verify the relationship between candidate gene expression levels and OS, progression-free survival (PFS), relapse-free survival (RFS), and disease-specific survival (DSS) in HCC patients. Then, Kaplan Meier Plotter was used to explore the relationship between candidate genes and OS in patients with different pathological stages. Patients were trichotomized (T1 vs. T3).
CLGN protein expression in HCC and normal tissues
Ethics Statement: The study was conducted in accordance with the principles of the Declaration of Helsinki (18). The collection of HCC specimens was approved by the Ethics Committee of Liuzhou Workers’ Hospital (No.KY2022051).
Immunohistochemical Staining: Samples from 24 HCC patients who underwent surgical resection at Liuzhou Workers’ Hospital were collected. The acquisition of specimens was approved by the Ethics Committee of Liuzhou Workers’ Hospital.
Five-micrometer sections were obtained from paraffin-embedded tumor and non-tumor specimens. All sections were dewaxed in xylene and rehydrated in alcohol, followed by wet autoclave pretreatment in citrate buffer for antigen retrieval (10 min at 120°C, pH=6.0) and then rinsed with phosphate buffer saline. Immunohistochemical staining with antibody to CLGN (Anti-Calmegin/CLGN Antibody, Rabbit: A05261-1, Boster Biological Technology Co. Ltd.) was performed using the avidin-biotin- peroxidase complex method. The primary antibody (1:200 dilution for CLGN) was applied to the sections and allowed to bind for 1 h at room temperature. The sections were then incubated with biotinylated anti-mouse/rabbit antibody for 30 min and an avidin-biotin-peroxidase reagent for 10 min. After color development with diaminobenzidine, the sections were counterstained with hematoxylin.
In addition, PATHOLOGY module in HPA (https://www.proteinatlas.org/) database was used to verify the expression of CLGN protein in HCC patient specimens and normal liver tissue.
Analysis of mutation and immune cell infiltration levels
The CBioportal database (https://www.cbioportal.org/) (19) was used to analyze the mutation of CLGN in HCC patients. The relationships between the expression levels of CLGN and six immune cells (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells) in HCC were estimated using the TIMER algorithm. Statistical significance was set at p values of <0.05 and correlation coefficients (COR) of ≥ 0.5.
Screening of regulating microRNAs
MiRWalk (http://mirwalk.umm.uni-heidelberg.de/) (20) and TargetScan (http://www.targetscan.org/vert_72) (21) databases were used to predict microRNAs (miRNAs) that regulate CLGN mRNA expression. The Encyclopedia of RNA Interactomes (ENCORI, http://rna.sysu.edu.cn/encori/mirTarPathways.php) (22) database was used to analyze the expression levels of candidate miRNAs in HCC and normal tissues. Kaplan Meier Plotter was used to analyze the relationship between the levels of candidate miRNAs and prognosis of HCC. A p value of <0.05 was considered statistically significant.
Data processing and visualization
Gene expression data were cleaned and visualized using R (Version 3.6.3) and the R packages ggplot2 and VennDiagram. The cleaning algorithm for the gene expression data included removal of non-coding genes, miRNA, and blank probes; FDR ≤0.05 and FC ≥2; retaining one level from one gene that had several high or, consistently, low expression levels in different specimens. We removed genes that had both high expression and low expression in different specimens. Cytoscape (Version: 3.7.2) and cytoHubba plugin were used to analyze miRNAs with the potential to regulate CLGN mRNA expression.
ResultsSignificant DEGs in HCC
The DEG analysis revealed 290 genes with significantly high expression and 518 genes with significantly low expression in the GSE54236 (G1) dataset (Figures 1A, C). In the GSE121248 (G2) dataset, 319 genes were significantly upregulated, and 611 genes were significantly under-expressed (Figures 1B, C). There were 121 genes with high expression and 249 genes with low expression in both the datasets (Figure 1C). After removing the genes that have been reported, we found that the expression levels of MND1, STXBP6, and CLGN in HCC were significantly higher than those in normal tissues.
Screening of differentially expressed genes in GSE54236 (G1) and GSE121248 (G2) datasets. (A, B) Gene expression levels in GSE54236 (G1) and GSE121248 (G2) datasets, with blue dots indicating significantly low expression and red dots indicating significantly high expression. (C) The number of genes with high or low expression in both datasets.
The expression levels of MND1, STXBP6, and CLGN mRNA in HCC w ere verified. The results showed that the MND1, STXBP6, and CLGN mRNA levels in HCC were significantly higher than those in normal tissues (p < 0.01, Figures 2A-C). In addition, the mRNA expression of CLGN was high in breast invasive carcinoma, kidney chromophobe, kidney renal papillary cell carcinoma, lung adenocarcinoma, lung squamous cell carcinoma prostate adenocarcinoma, and uterine corpus endometrial carcinoma (p < 0.01, Figure 3).
The mRNA expression levels of MND1, STXBP6, and CLGN in HCC (GEPIA). (A-C) The mRNA expression levels of MND1, STXBP6, and CLGN in HCC were significantly higher than in normal tissue. *p < 0.01.
The mRNA expression of levels of CLGN in several common human tumors. The mRNA of CLGN was upregulated in liver and other tumors (TIMER).
Relationship between DEGs and prognosis of HCC
The prognostic value of MND1, STXBP6, and CLGN in HCC patients was explored. HCC patients with higher mRNA levels of CLGN had poorer OS and DFS (p< 0.05, Figures 4A, B). There was no significant correlation between MND1 mRNA levels and OS (p> 0.05; Figure 4C), and patients with higher MND1 mRNA levels had poorer DFS (p< 0.05, Figure 4D). However, there was no significant correlation between the mRNA levels of STXBP6 and OS or DFS in HCC patients (p > 0.05, Figures 4E, F).
The relationship between the mRNA levels of MND1, STXBP6 and CLGN and the prognosis of HCC (GEPIA). (A, B) HCC patients with higher mRNA levels of CLGN had poorer overall survival and disease-free survival (p< 0.05). (C) No significant relationship between MND1 mRNA levels and patients’ overall survival was observed (p > 0.05). (D) Patients with higher MND1 mRNA levels had poorer disease-free survival (p < 0.05). (E, F) There was no significant correlation between the mRNA levels of STXBP6 and overall survival and disease-free survival in HCC patients (p > 0.05).
The relationship between CLGN mRNA levels and the prognosis of HCC was also investigated. The results showed that the mRNA levels of CLGN were significantly correlated with OS, PFS, and DSS in HCC patients (p< 0.05, Figures 5A-C and Table 1). However, there was no significant relationship between CLGN mRNA levels and RFS (p> 0.05, Figure 5D and Table 1). Furthermore, the mRNA level of CLGN was significantly correlated with the OS in different pathology stages in HCC patients. Specifically, HCC patients with higher mRNA expression of CLGN in advanced stages (T3, T3+T4) had poorer OS (p < 0.01, Figures 6C, D and Table 2). No significant correlation was found between CLGN mRNA levels and OS in patients with early-stage HCC (T1-T2) (p > 0.05, Figures 6A, B and Table 2).
The relationship between CLGN mRNA and prognosis of HCC (Kaplan Meier Plotter). (A–C) HCC patients with higher CLGN mRNA expression have poorer OS, PFS, and DSS, p < 0.05. (D) There was no significant relationship between CLGN mRNA level and RFS, p > 0.05.
Correlation between the CLGN mRNA expression and the survival of HCC patients.
Gene
Survival
Patients
HR
p Value
Median survival (months)
Low
High
CLGN
OS
244
1.57
0.0401
81.9
56.2
RFS
211
1.42
0.0929
29.77
17.9
PFS
248
1.76
0.0024
29.77
11.83
DSS
242
2.10
0.0106
104.17
84.4
The relationship between the CLGN mRNA level and the OS in different pathology stages in HCC patients. (Kaplan Meier Plotter). (A, B) There was no significant correlation between the CLGN mRNA level and the OS in HCC patients in early stages (T1 and T2), p> 0.05. (C, D) HCC patients in advanced T stages (T3 and T3+T4) have higher CLGN mRNA expression and poorer OS, p < 0.05.
Correlation between the CLGN mRNA expression and patient OS at different pathological stages.
Stage
Patients
HR
p Value
Median survival (months)
Low
Low
1
170
0.92
0.84
81.9
84.4
2
83
1.43
0.46
108.6
46.6
1+2
253
1.35
0.34
108.6
84.4
3
83
3.14
0.0054
82.9
14
3+4
87
2.84
0.0058
54.1
14
CLGN protein expression in clinical specimens
The p rotein expression of CLGN in tumor and normal tissues of clinical specimens from patients with HCC was investigated. Immunohistochemical staining showed that the CLGN protein was significantly regulated in HCC compared with normal liver tissues in 58% (14/24) of cases (Figure 7A). The HPA database results also showed that CLGN protein levels were higher in HCC than in non-tumor tissues (Figure 7B).
The expression of CLGN protein in HCC and adjacent tissues. (A) Three typical cases of CLGN protein upregulation in HCC in 24 clinical specimens. (B) The expression of CLGN protein in HCC is higher than non-cancerous liver tissue (HPA).
<italic>CLGN</italic> mutation in HCC and the correlation between <italic>CLGN</italic> expression and tumor infiltrating lymphocytes
CLGN mutations were analyzed in 1089 patients with HCC from six data sources. The results showed that CLGN was mutated in < 1% (10/1089) of patients (Figure 8A). Furthermore, there was no significant correlation between CLGN expression and the levels of B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, or dendritic cells in HCC (COR < 0.5 (Figure 8B).
CLGN mutations in HCC patients and the correlation between CLGN expression and tumor infiltrating lymphocytes. (A)CLGN mutations occurred in 10 (< 1%) of 1089 patients from six data sources (CBioportal). (B) There is no significant correlation between the mRNA of CLGN and the infiltrating levels of B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells in HCC, COR < 0.5 (TIMER).
miRNAs that regulate <italic>CLGN</italic>
Firstly, 4357 and 634 miRNAs that potentially regulate CLGN were predicted in the miRWalk and TargetScan databases, respectively. Duplicate data from the two groups were removed, and their intersection contained 248 potential miRNAs (Supplementary 1). As calculated with Cytoscape, the top 14 miRNAs that were most likely to regulate CLGN mRNA expression were hsa-miR-642b-3p, hsa-miR-7114-5p, hsa-miR-6130, hsa-miR-4738-3p, hsa-miR-520g-3p, hsa-miR-6759-5p, hsa-miR-4446-3p, hsa-miR-6843-3p, hsa-miR-4482-5p, hsa-miR-202-3p, hsa-let-7a-5p, hsa-miR-6080, hsa-miR-2681-5p, and hsa-miR-194-3p (Figure 9A). A further analysis revealed that hsa-miR-194-3p was significantly underexpressed in HCC (Fold Change = 0.72, p < 2.1e-5 and FDR< 0.001, Figure 9B). HCC patients with low hsa-miR-194 expression had poorer OS than those without (p < 0.001, Figure 9C).
miRNAs that likely regulate the expression of CLGN mRNA (miRWalk and TargetScan). (A) The 14 miRNAs that most closely related to CLGN mRNA. (B) The expression of hsa-miR-194-3p in HCC is significantly lower than in normal tissue, p < 0.05 (ENCORI). (C) HCC patients with lower hsa-miR-194 expression have poorer OS than those without, p < 0.05 (Kaplan Meier Plotter).
Discussion
CLGN (Calmegin) is a testis-specific endoplasmic reticulum chaperone protein (23, 24). Previous studies have shown that CLGN acted as a chaperone for one or more sperm surface proteins to mediate the interaction between sperm and eggs during spermatogenesis (23). Therefore, CLGN may play an important role in spermatogenesis and infertility. A recent study found that CLGN was up-regulated in aldogen-producing adenomas and was related to the generation of aldosterone (25). However, the role of CLGN in several malignant tumors, including HCC, remains unclear.
In this study, it was found that the mRNA and protein of CLGN were highly expressed in HCC compared with normal liver tissues. Furthermore, patients with higher CLGN mRNA levels had poorer prognoses, and CLGN mRNA levels were valuable in predicting the prognosis of patients with advanced pathology. These results suggest that CLGN is associated with malignant progression in HCC patients. Additionally, CLGN was found to be significantly upregulated in invasive breast cancer, chromophobe renal cell carcinoma, papillary renal cell carcinoma lung adenocarcinoma, lung squamous cell carcinoma, prostate adenocarcinoma, and uterine corpus endometrial carcinoma. To the best of our knowledge, no studies have investigated the role of CLGN in these tumors, which is worth of further investigation.
However, the relationship between MND1 and STXBP6 in HCC remains unknown. Notably, Zierhut et al. found that MND1 was necessary for meiosis homologue repair (26). Zhang et al. found that MND1 was upregulated in lung adenocarcinoma and was an independent risk factor for overall survival (27). Furthermore, MND1 was a prognostic biomarker for renal clear cell carcinoma (28). Lenka et al. found that STXBP6 hypermethylation was associated with adverse clinical outcomes in patients with lung cancer (29). A nother recent study showed that the expression level of STXBP6 predicted the response to PD-1/PD-L1 immunotherapy in patients with cancer (30). In this study, we found that MND1 and STXBP6 were upregulated in HCC, but no significant correlation was found between their expression and patient prognosis .
Gene mutations are a common tumorigenic mechanism in liver cancer (31–34). In this study, it was found that CLGN was rarely mutated in HCC patients, which suggests that the pathological effects of CLGN may not be exerted through genetic mutations. The immune microenvironment is closely related to tumor progression (35–37). Therefore, we also analyzed the relationship between CLGN mRNA levels and the abundance of tumor-infiltrating lymphocytes in HCC; however, no significant correlation was found. Based on this, we hypothesized that CLGN might influence the progression of HCC by promoting cell proliferation or inhibiting tumor cell apoptosis, which requires further study in the future.
MicroRNAs (miRNAs) are small non-coding RNAs composed of approximately 20 nucleotides that regulate gene expression by binding to the 3’-UTR of the target mRNA (38). Recent studies have shown that miRNAs were an important regulator of mRNA expression (39–41). hsa-miR-194-3p was significantly underexpressed in HCC, and patients with lower hsa-miR-194 expression had poorer prognosis. A study found that hsa-miR-194-3p might target MECP2 to promote breast cancer progression and reduce sensitivity to rapamycin (42). Recent studies have shown that hsa-miR-194-3p might be associated with colorectal cancer progression (43). However, its specific therapeutic and prognostic value in tumors requires further investigation. In this study, we discovered that hsa-miR-194-3p may also play an important role in HCC progression by regulating CLGN expression.
Our findings suggest that CLGN is a potential prognostic marker for HCC and is associated with HCC progression, however, several limitations are associated with our study. Specifically, the relationship between CLGN expression and patient prognosis has not yet been verified at the center. Additionally, laboratory research on the cancer-promoting mechanisms of CLGN were not available, and the sample size used for immunohistochemistry in this study was small. Therefore, a large-scale verification study is required in the future.
Conclusion
CLGN is upregulated in HCC and significantly correlates with patient prognosis, especially in the advanced stages. In addition, the mRNA levels of CLGN were found to be potentially regulated by hsa-miR-194-3p. These results suggest that CLGN may have important therapeutic and prognostic value in HCC patients.
Data availability statement
The datasets analyzed during the current study are available on Gene Expression Omnibus (GEO) (accession numbers: GSE54236, GSE121248), Gene Expression Profiling Interactive Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), Kaplan Meier Plotter, The Human Protein Atlas (HPA), cBioPortal, miRWalk, TargetScan, and The Encyclopedia of RNA Interactomes (ENCORI).
Ethics statement
The studies involving human participants were reviewed and approved by Ethics Committee of Liuzhou Workers’ Hospital. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.
Author contributions
ZC: Data analysis and writing of the first draft. BC, YL and ZW: Data analysis, manuscript editing, review, and approval. JW, ZC, and GC: Data analysis, data collection and experiments. DL: Data analysis, manuscript editing and review. All authors have read and approved the final manuscript.
Funding
This study was supported by the Science and Technology Innovation Joint Fund Project of Fujian Province (No. 2019Y9044) and Natural Science Foundation of Fujian Province (No. 2020J011131).
Acknowledgments
We are grateful to the generous data contributors, developers, and maintainers of the public databases.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2022.1081510/full#supplementary-material
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