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Abstract

BACKGROUND:

PPM1G, a member of the serine/threonine protease family, dephosphorylates various proteins and may be involved in cancer development. The role and mechanism of PPM1G in HCC still needs to be verified.

OBJECTIVE:

This study aims to explore the role of PPM1G in the occurrence, development and prognosis of HCC.

METHODS:

Using bioinformatics (UALCAN, cBioPortal, Linkedomics, STRING and GSEA) to analyze the expression of PPM1G mRNA in HCC, its clinical relevance and possible involved signaling pathways. The expression of PPM1G protein was determined by immunohistochemistry in 311 cases of HCC to evaluate the association between PPM1G and clinical features and prognosis.

RESULTS:

The expression of PPM1G was significantly upregulated in HCC ( $P<$ 0.001), correlated with the metastasis ( $P=$ 0.020), pathological grade of HCC ( $P=$ 0.032), microvascular invasion ( $P=$ 0.040), and HBV infection ( $P=$ 0.041). Cox multivariate regression showed high expression of PPM1G was an independent prognostic factor for HCC. Its role in HCC may relate to methylation and frequency mutation. Furthermore, the database showed PPM1G is involved in the signal pathway such as cell cycle, WNT pathway, and mTOR pathway in HCC.

CONCLUSION:

PPM1G showed an essential function involving in tumor-related pathways in HCC, providing a biological basis for targeted treatment of HCC clinically.

Keywords

PPM1G HCC progression prognosis

1. Introduction

Hepatocellular carcinoma (HCC) is the fourth cause of cancer-related death worldwide [1], which has a high-grade malignancy with poor prognosis, and presents a serious health problem [2]. Therefore, it is necessary to identify biomarkers for early diagnosis and evaluation of prognosis in HCC. These biomarkers would help us to gain a better understanding of the pathogenesis of HCC and find potential therapeutic targets [3].

PPM1G belongs to the PPM family of proteins and is a type 2C phosphatase with a unique acidic domain. The phosphatase activity of human PPM1G depends on Mn ${}^{2+}$ and Mg ${}^{2+}$ . Study showed that in humans, PP2C $\gamma$ is expressed ubiquitously, with the highest levels in the testes, heart, and skeletal muscle [4]. The serine/threonine phosphatase activity of PPM1G is essential for alternative splicing of specific pre-mRNAs, cell cycle control, and DNA damage response [5, 6, 7, 8].

In light of the involvement of PPM1G in cell cycle arrest and DNA damage response, the possibility of PPM1G related to tumorigenesis was noticed. Xu et al. [9] demonstrated that activity of PPM1G is modulated by PI-3K/AKT signaling pathway, which shifts the balance between the hyper- and hypo-phosphorylated 4E-BP1 and regulates the expression of Id1 at the translational level, thus promoting the occurrence and development of glioma. Nevertheless, Phannasi et al. [10] found that PPM1G is upregulated during the suppression of Moringa oleifera pod (bMO) on azoxymethane (AOM)/dextran sodium sulfate (DSS)-induced mouse colon carcinogenesis, which suggested that PPM1G may act as a tumor suppressor. The above reports showed that PPM1G has tissue-specific function in carcinogenesis and development. However, the role of PPM1G in the tumorigenesis and development of HCC remains to be determined.

In the present study, we first used bioinformatic analysis to detect the mRNA level of PPM1G in HCC, and then performed immunohistochemistry to analyze the correlation between the expression of PPM1G and clinicopathological features by our cohort. Gene ontology (GO) enrichment analysis, the Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis, and protein-protein interaction (PPI) network were used to explore the molecular mechanism of PPM1G in HCC.

2. Materials and methods

2.1 UALCAN

UALCAN (http://ualcan.path.uab.edu/) is an effective cancer data on-line analysis and mining site. The analysis performed in this study was mostly based on relevant cancer data in the TCGA database, which was used to determine the expression of PPM1G mRNA in HCC. Tumor samples were grouped by UALCAN to assess the relationship between the expression of PPM1G mRNA in HCC tissues and clinicopathological parameters. The database contained 371 cases of HCC and 50 cases of normal liver tissue. In addition, UALCAN was employed to identify the methylation patterns in HCC and normal tissues.

2.2 cBioPortal

cBioPortal (http://www.cbioportal.org/) data sources and analysis options originate from multiple sites such as TCGA, GDAC, and UCSC. This resource was used to visualize genetic changes in cancer samples, compare the frequency of changes, or synthesize genomic changes in a single sample. cBioPortal was also used to analyze the alterations in the expression of PPM1G mRNA in HCC based on data from the TCGA repository. The tab Oncoprint showed the overview of PPM1G alterations in HCC patients. The search variables included mutation, CNVs, and mRNA expression. In addition, the survival of patients with genetic alterations and that without genetic alterations were compared. Finally, the cBioPortal database was used to define the correlation between the expression profile and methylation of PPM1G in HCC.

2.3 Linkedomics

The LinkedOmics (http://www.linkedomics.org/) database is a Web-based platform designed to analyze 32 TCGA cancer-associated multi-dimensional datasets. The genes co-expressed with PPM1G were retrieved in LinkedOmics, and those with the correlation coefficient greater than 0.4 were analyzed. Enrichment analysis of the KEGG pathway and GO was conducted using OmicShare (https://www.omicshare.com/). GO enrichment analysis included Cellular component (CC), Biological process (BP) and Molecular function (MF).

2.4 STRING

In order to obtain the protein interaction network of PPM1G in human cells, the STRING (http://string-db.org/) database was searched using the terms “PPM1G” and “Homo sapiens”. The PPI protein interaction network was exported in TSV format, and the obtained source files were imported into Cytoscape (https://cytoscape.org/). The hub genes with a high degree of connectivity were obtained by visual analysis.

Figure 1.

mRNA level of PPM1G in liver hepatocellular carcinoma and its relationship with clinicopathological features (UALCAN). (A) Bar graph showing relative expression of PPM1G mRNA in normal tissue and HCC samples. (B) Bar graph showing relative expression of PPM1G mRNA in normal tissue or HCC samples corresponding to tumor grade 1, 2, 3, and 4 (1 represents highly differentiated, 2 represents moderately differentiated, 3 represents poorly differentiated, 4 represents undifferentiated). (C) Bar graph showing relative expression of PPM1G mRNA in normal tissue and HCC samples corresponding to tumor TNM (T: Tumor; N: Lymph node metastasis; M: Distant metastasis) stage 1, 2, 3, and 4. (D) Bar graph showing relative expression of PPM1G mRNA in normal tissue or HCC samples with metastasis. ${}^{*}p<$ 0.05, ${}^{**}p<$ 0.01, ${}^{***}p<$ 0.001.

2.5 GSEA

The gene expression matrix of 374 HCC patients downloaded from TCGA (https://portal.gdc.cancer.gov/) was selected as the pre-defined gene set. The matrix was divided into the high PPM1G expression group and the low PPM1G expression group according to the median value of PPM1G expression. GSEA software (https://www.gsea-msigdb.org/gsea/index.jsp) was used to analyze the effects of PPM1G expression level on gene sets of various biological pathways, and enrichment analysis was carried out by randomly combining 1000 times according to default parameters of GSEA software. In this study, the gene set with FDR $<$ 0.05 was used as a significantly enriched gene set to analyze the possible mechanism of PPM1G gene in HCC.

2.6 Immunohistochemistry staining

The tissue microassay (TMA) was purchased from Shanghai Biochip Co., Ltd. The TMA included 311 samples of cancer tissues obtained from HCC patients between 2008 and 2015 and 176 corresponding normal adjacent tissues. Paraffin slices were placed in an oven at 60–65 ${{}^{\circ}}$ C and baked for 60–120 min. After 3 dewaxing with dimethylbenzene, slides were immersed into gradient alcohol (100%, 100%, 95% and 75%) successively. After rinsed with distilled water for 1 minute, slides were washed with PBS for 3 times (not less than 5 minutes each time). The pressure cooker method was used for antigen repairing for 3 minutes, and then the slides were cooled in room temperature. After incubated with H ${}_{2}$ O ${}_{2}$ 15 minutes at room temperature, the slides were incubated with normal goat serum for 15 min at room temperature. Primary antibody (1:600) was added at 4 ${}^{\circ}$ C overnight. Biotin-labeled goat anti-rabbit IgG and HRP were added and incubated at room temperature for 15 minutes respectively. Then the slides were stained with DAB for 5–10 minutes.

Immunohistochemistry staining was evaluated according to previous study [11]. The staining score was based on four intensity grades (0: negative, 1: weakly positive, 2: moderately positive, 3: strongly positive) and the fraction of positive cells (0: $\leqslant$ 5%, 1: 6%–25%, 2: 26%–50%, and 3: 51–100%). The final score was the product of the intensity grade and the percentage grade, with 0–3 considered as a low expression, and $\geqslant$ 4 considered as a high expression of PPM1G.

Table 1
Expression of PPM1G in hepatocellular carcinoma tissues ( $n=$ 311)

Clinical parameters	Patients	PPM1G expression		$\chi^{2}$	$P$ value
		Low (%)	High (%)
Age (years)				0.222	0.637
$<$ 55	124	45 (36.3)	79 (63.7)
$\geqslant$ 55	187	63 (33.7)	124 (66.3)
Gender				0.004	0.949
Male	254	88 (34.6)	166 (65.4)
Female	57	20 (35.1)	37 (64.9)
Tumor size ${}^{*}$				0.737	0.391
$<$ 5 cm	181	65 (35.9)	116 (64.1)
$\geqslant$ 5 cm	122	38 (31.1)	84 (68.9)
Tumor number				2.534	0.111
Single	256	94 (36.7)	162 (63.3)
Multiple	55	14 (25.5)	41 (74.5)
Edmondson grade ${}^{*}$				5.428	0.020
I $+$ II	197	76 (38.6)	121 (61.4)
III	110	28 (25.5)	82 (74.5)
Metastasis ${}^{*}$				4.605	0.032
Negative	281	102 (36.3)	179 (63.7)
Positive	26	4 (15.4)	22 (84.6)
Microvascular invasion				4.236	0.040
Negative	117	45 (38.5)	72 (61.5)
Positive	116	30 (25.9)	86 (74.1)
Cirrhosis				0.240	0.624
Negtive	101	37 (36.6)	64 (63.4)
Positive	210	71 (33.8)	139 (66.2)
HBV				4.179	0.041
Negtive	61	28 (45.9)	33 (54.1)
Positive	244	78 (32.0)	166 (68.0)

2.7 Statistical analysis

SPSS 26.0 statistical software was used for data analysis. Categorical variables were represented as frequency, and the relationship between PPM1G expression and clinicopathological features of HCC was determined using the $\chi^{2}$ test or fisher’s exact test. The Kaplan-Meier method was used for survival analysis of prognostic value of PPM1G in HCC, and log-rank was used to test the significance of differences in survival. Univariate and multivariate analyses were performed using the Cox regression model to detect the independent prognostic factors.

3. Results

3.1 PPM1G mRNA in HCC and normal tissue

Based on the data in UALCAN, the level of PPM1G mRNA was significantly higher in HCC than in normal liver tissue ( $P<$ 0.001, Fig. 1A). Further analysis showed that the PPM1G mRNA level was positively correlated with HCC grade in HCC (Fig. 1B). Moreover, PPM1G expression was significantly correlated with HCC TNM stage (T: Tumor; N: Lymph Node; M: Metastasis). The expression was higher in TNM stage III than in TNM stage I and II (Fig. 1C), and was also higher in patients with distant metastases (M1) than those without distant metastases (M0) (Fig. 1D). These findings suggested that the high mRNA level of PPM1G in HCC may be associated with progression of HCC.

Table 2
Univariate and multivariate Cox regression survival analysis of clinicopathological parameters and PPM1G expression in hepatocellular carcinoma patients

Parameters	Univariate analysis			Multivariate analysis
	HR	95% CI	$P$	HR	95% CI	$P$
Age	0.65	0.41–1.04	0.07	NA
Gender	1.58	0.92–2.69	0.10	NA
Tumor size	1.95	1.22–3.13	$<$ 0.01	1.23	0.66–2.23	0.53
Tumour number	1.24	0.68–2.26	0.49	NA
Edmondson grade	2.78	1.74–4.46	$<$ 0.01	1.78	0.99–3.20	0.05
Metastasis	4.82	2.55–9.11	$<$ 0.01	4.23	1.72–10.41	$<$ 0.01
Microvascular invasion	2.11	1.25–3.56	$<$ 0.01	1.69	0.91–3.14	0.10
HBs antigen	1.17	0.65–2.10	0.60	NA
Cirrhosis	1.15	0.70–1.91	0.58	NA
PPM1G expression	4.13	2.16–7.91	$<$ 0.01	2.26	1.09–4.70	0.03

3.2 Correlation between PPM1G expression and clinical characteristics of HCC by immunohistochemical analysis

To further verify the expression of PPM1G, we performed IHC staining of TMA containing 311 HCC samples, and found that PPM1G was mainly localized in the nuclei (Fig. 2). Consistent with the results obtained by UALCAN data, PPM1G was upregulated in HCC tissues. The high expression of PPM1G in HCC was found in 64.63% (201/311) of cases, which was significantly higher than that in adjacent noncancerous tissue (25.57%, 45/176; $P<$ 0.05). The analysis of the relationship between PPM1G expression and different clinicopathological parameters demonstrated that the high protein level of PPM1G in HCC patients was related to Edmondson grade ( $P=$ 0.020), metastasis ( $P=$ 0.032), microvascular invasion ( $P=$ 0.040), and HBV infection ( $P=$ 0.041) (Table 1).

Figure 2.

Representative cases of high and low PPM1G expression detected by immunohistochemistry. (A) Cancer tissue, metastasis, high expression. (B) Cancer tissue, no metastasis, low expression. (C) Paracancerous tissue, low expression. Yellow or brown represents the positive staining of PPM1G; blue refers to the nucleus stained by hematoxylin.

Figure 3.

The survival curves of HCC patients with different levels of PPM1G expression based on databases and immunohistochemistry. (A) UALCAN, (B) GEPIA, (C) Kmplot, (D) immunohistochemistry.

3.3 Increased PPM1G expression predicts poor prognosis in HCC patients

We selected several databases to analyze the impact of the mRNA level of the PPM1G gene on the survival of HCC patients. The results showed that the overall survival of patients with low mRNA level of PPM1G was significantly longer than those with high mRNA level of PPM1G ( $P<$ 0.001) (Fig. 3A–C).

Survival analysis performed by the Kaplan-Meier method using our present 311 cases of HCC patients also documented that the survival time (38 $\pm$ 3.21 months) of patients with high PPM1G protein level was shorter than those with low PPM1G protein level (61 $\pm$ 2.70 months) ( $P<$ 0.001) (Fig. 3D). These results suggested that the high protein level of PPM1G correlates with poor prognosis of HCC patients.

Cox univariate regression analysis showed that the protein level of PPM1G ( $<$ 0.01), tumor size ( $P<$ 0.01), Edmondson grade ( $P<$ 0.01), microvascular invasion ( $P<$ 0.01), and metastasis ( $P<$ 0.01) were correlated with clinical outcome. Further Cox multivariate regression analysis revealed that distant metastasis ( $P<$ 0.01) and expression of PPM1G ( $P=$ 0.03) were both independent risk factors for prognosis of HCC (Table 2).

Figure 4.

Analysis of genetic mutations and DNA methylation level in PPM1G (A) Genetic mutations of PPM1G in HCC (cBioPortal). (B) Patients with PPM1G mutations have poor survival (cBioPortal). (C) The methylation level of PPM1G promoter in HCC (UALCAN). (D) Correlation between the expression level of PPM1G mRNA and methylation level of PPM1G promoter (cBioPortal).

Figure 5.

Correlation between differentially expressed genes and PPM1G level in HCC (LinkedOmics). (A) The Pearson’s test was used to analyze correlations between the level of PPM1G and genes differentially expressed in HCC. (B) and (C) Heat maps showing the top 50 genes negatively and positively correlated with PPM1G in HCC.

3.4 Analysis of genetic alterations and DNA methylation level of PPM1G gene

The PPM1G gene was altered in 9% (34/372) HCC patients (Fig. 4A). The most frequent alteration type was amplification, identified in 6 cases (2%). Importantly, patients with genetic alterations of PPM1G had lower overall survival than those without alterations (Fig. 4B).

Methylation within the promoter region of the PPM1G gene was significantly lower in HCC than in normal liver tissue ( $P<$ 0.001), and the PPM1G mRNA level decreased with the increase of DNA methylation (Fig. 4C and D).

3.5 Identification and functional analysis of genes co-expressed with PPM1G in HCC

Genes co-expressed with PPM1G were analyzed by LinkedOmics using mRNA sequencing data of 371 HCC patients from the TCGA. All genes associated with PPM1G are shown by the volcano plot in Fig. 5A, while Fig. 5B and C depict 50 significant genes that are positively or negatively correlated with PPM1G.

Co-expressed genes (correlation coefficient $<$ 0.04) were also downloaded and analyzed for GO and KEGG analysis (suppl.1). GO analysis demonstrated that these genes were located in the nucleus, which had biological functions such as protein binding and RNA binding, and mainly involved in the cell cycle, DNA metabolic process, DNA replication and other cancer-related biological processes (Fig. 6A–C). KEGG pathway analysis indicated that these genes were enriched in the cell cycle, spliceosome, pathogenic Escherichia coli infection, lysine degradation, and other related pathways (Fig. 6D).

Figure 6.

Significantly enriched GO annotations and KEGG pathways of PPM1G in HCC. (A) Cellular component, (B) Molecular function, (C) Biological process, (D) KEGG enrichment.

Ten of these pathways were selected based on FDR $<$ 0.05, and the GSEA results showed that high expression of PPM1G was enriched in RNA degradation, cell cycle, DNA replication, WNT signaling pathway, p53 signaling pathway, mTOR signaling pathway, MAPK signaling pathway, and T cell receptor signaling (Fig. 7).

Figure 7.

GSEA was used to analyze the pathways promoted by the high expression of PPM1G in HCC.

Figure 8.

The protein interaction network of PPM1G. (A) The protein-protein interaction of PPM1G in human cells. (B) Pearson’s correlation analysis between PPM1G and USP7. (C) The network diagram of the protein interaction of hub genes. The genes in the red, orange, and yellow circles are the hub genes, while the blue circle indicates other genes associated with the hub genes.

The protein network interacting with PPM1G analyzed by STRING showed that USP7 was one of the interacted proteins with PPM1G (Fig. 8A). So we analyzed the correlation between USP7 and PPM1G by GEPIA in HCC, and we found that USP7 correlated with PPM1G significantly ( $R=$ 0.52, $P<$ 0.05) (Fig. 8B). The molecular regulatory network among genes co-expressed with PPM1G in HCC were also analyzed and showed as Fig. 8C.

4. Discussion

Phosphorylation and dephosphorylation are key processes involved in the regulation of protein expression, which may play as an on-off role in cellular biological functions. Most studies on PPM1G (PP2C $\gamma$ ) have identified its mechanism as protein phosphatase. Here, we focused on its role and mechanism in HCC. In this study, bioinformatics data were used to analyze the expression and clinical significance of PPM1G mRNA level in HCC. The results documented that the PPM1G mRNA level in HCC is significantly higher than in normal liver tissue. Importantly, the PPM1G mRNA level in HCC patients was positively correlated with tumor TNM stage, grade and metastasis.

Next, immunohistochemistry was employed to determin the protein level of PPM1G using TMA containing 311 HCC samples and 176 adjacent noncancerous samples. The results demonstrated that PPM1G protein level was upregulated in HCC, and its high expression was positively correlated with tumor grade, metastasis, HBV infection and vascular invasion. PP2C isoforms have been implicated in signaling networks controlling cell differentiation, proliferation, growth, survival, and metabolism [12]. Previous studies [13] have also demonstrated that PPM1G has anti-apoptotic activity during neural development in mice. Once stimulated with the pro-inflammatory cytokine tumor necrosis factor- $\alpha$ (TNF- $\alpha$ ), the major transcriptional regulator NF- $\kappa$ B could induce inflammation with the coactivator PPM1G/PP2C $\gamma$ phosphatase [14]. Furthermore, PPM1G has also been shown to play a role in liver fibrosis, which fibrosis is thought to play an important role in the precancerous environment of liver [15, 16]. So we speculated that HBV may induce dysregulation of PPM1G through infection or inflammation. Therefore, we hypothesized that PPM1G might act as an oncogene in HCC.

Recent study [17] has also found PPM1G showed good performance in predicting overall survival for HCC patients by internal and external validation. Consistent with the previous study, we also showed that the high expression of PPM1G was positively correlated with a poor prognosis of HCC patients and was an independent prognostic factor by Cox multivariate regression analysis. Thus, PPM1G may associate with the occurrence, development, and prognosis of HCC.

Study found that these point mutants of PPM1G showed reduced binding to $\alpha$ -catenin, and this mutation disrupted the interactions of PPM1G with substrates, which may contribute to the active migration of tumor cells [18]. In the present study, we revealed that the amplification of PPM1G is the main cause of its association with worse survival. According to the UALCAN database, the extent of promoter methylation of PPM1G in the primary tumor group is lower than in the normal group. The degree of methylation regulates the biological characteristics of tumors, and may even be related to tumorigenesis. Studies also found that differentially methylated regions of PPM1G promoter are located in a sequence flanking a CpG island, which regulates gene expression [19, 20]. Therefore, we hypothesized that mutation and methylation may induce upregulation of PPM1G in HCC. Co-expressed genes with PPM1G were also explored and we found that these genes were enriched in the cell cycle, splicing and DNA replication et al. GSEA analysis showed that the tumor-related signaling pathways, such as cell cycle-related pathways, tumor-related pathway, WNT pathway, p53 pathway, and mTOR pathway, were enriched to a different extent in the samples with high expression of PPM1G. By employing the STRING protein interaction database and the Cytoscape software, we screened out 10 core genes in PPM1G regulatory network. Further analysis revealed that these genes were mainly enriched in the cell cycle, mitosis, and other pathways. These suggested that PPM1G might be involved in the initiation and development of HCC by regulating the expression of these hub genes, thus affecting the prognosis of patients.

In summary, high expression of PPM1G is associated with a worse pathological stage of HCC, which might play an important role in the progression of HCC. Additionally, PPM1G may be used as prognostic and survival indicator. However, role and molecular mechanism of PPM1G still needs to be further studied by experiments in vitro and in vivo.

Authors’ contributions

Conception: XMF.

Interpretation or analysis of data: QL.

Preparation of the manuscript: DLX.

Revision for important intellectual content: HW and WLJ.

Supervision: YYM.

Supplementary data

The supplementary files are available to download from http://dx.doi.org/10.3233/CBM-203248.

sj-xlsx-1-cbm-10.3233_CBM-203248.xlsx - Supplemental material

Supplemental material, sj-xlsx-1-cbm-10.3233_CBM-203248.xlsx

Footnotes

Acknowledgments

We thank the Department of Key Laboratory of Gastroenterology of Zhejiang Province for helping us to use the equipment. This work was supported by the project of science and technology of Zhejiang province (grant no. GF19H160085).

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High expression of PPM1G is associated with the progression and poor prognosis of hepatocellular carcinoma

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Materials and methods

2.1 UALCAN

2.2 cBioPortal

2.3 Linkedomics

2.4 STRING

2.6 Immunohistochemistry staining

Table 1 Expression of PPM1G in hepatocellular carcinoma tissues ( n = 311)

3. Results

3.1 PPM1G mRNA in HCC and normal tissue

Table 2 Univariate and multivariate Cox regression survival analysis of clinicopathological parameters and PPM1G expression in hepatocellular carcinoma patients

3.5 Identification and functional analysis of genes co-expressed with PPM1G in HCC

Authors’ contributions

Supplementary data

sj-xlsx-1-cbm-10.3233_CBM-203248.xlsx - Supplemental material

Footnotes

Acknowledgments

References

Table 1
Expression of PPM1G in hepatocellular carcinoma tissues ( $n=$ 311)

Table 2
Univariate and multivariate Cox regression survival analysis of clinicopathological parameters and PPM1G expression in hepatocellular carcinoma patients