Expression of yhwaz and gene regulation network in hepatocellular carcinoma.

The adaptor protein 14-3-3ζ is encoded by the yhwaz gene and implicated in a wide range of biological processes. In tumorigenesis, 14-3-3ζ recognizes specific phosphorylation motifs and interacts with hundreds of target proteins and is, thus, involved in the regulation of tumor proliferation, migration and differentiation. In the present study, bioinformatics tools were used to analyze data from The Cancer Genome Atlas and Gene Expression Omnibus databases and the expression of yhwaz, and gene regulation networks were identified as potentially relevant in hepatocellular carcinoma (HCC). In HCC, yhwaz expression was demonstrated to be upregulated and significantly associated with poor prognosis. Expression levels of microRNAs targeting yhwaz were associated with improved prognosis in patients with liver cancer. Gene networks that are regulated by yhwaz were found to be involved in cell cycle regulation and tumorigenesis, indicating the potential use of the expression levels of yhwaz in liver tissue as predictive biomarkers in patients with liver cancer. In the present study, yhwaz was identified as a gene of interest through data mining gene expression databases and its involvement in regulatory networks in HCC was indicated. Therefore, further in vitro and in vivo studies on the role of yhwaz in the carcinogenesis of HCC would be greatly beneficial. Copyright: © Lin et al.

Introduction

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated mortality, with >700,000 new cases being diagnosed annually throughout the world (1). HCC is the result of complex interactions between genetic and non-genetic host factors, including exposure to environmental chemicals and viruses. In >90% of cases, a primitive chronic liver disease, e.g., cirrhosis, usually develops and creates a procarcinogenic environment in its final stage (2).

The yhwaz gene encodes 14-3-3ζ, which belongs to a family of highly conserved dimeric proteins that are considered master regulators of intracellular signaling (3–5). 14-3-3ζ has been shown to interact with numerous protein kinases, enzymes, receptor proteins, structural and cytoskeletal proteins, proteins associated with cell cycle and transcriptional control and proteins involved in apoptosis (6). Upregulated expression of yhwaz is frequently observed in several types of cancer (including lung and liver cancer) (7–9). For example, yhwaz is upregulated in >40% of cases of breast cancer and is able to activate transforming growth factor-β/SMAD signaling during the epithelial-to-mesenchymal-transition, thus promoting tumor progression (10). 14-3-3ζ interacts with β-catenin, GLI family zinc finger 2, Yes-associated protein 1 and the downstream effectors of the Wnt, Hedgehog and Hippo signaling pathways, all of which are involved to varying degrees in a number of different types of cancer (such as breast cancer or lymphocytic leukemia) (11–14). Therefore, 14-3-3ζ may potentially be used as a prognostic biomarker for the diagnosis of certain types of cancer.

The upregulation of yhwaz in patients with HCC has been frequently examined (15) and 14-3-3ζ protein expression levels have been found to be significantly upregulated in hepatoma cell lines. In HCC cell lines with upregulated 14-3-3ζ expression, knockdown of 14-3-3ζ using RNA interference was reported to inhibit cell proliferation by activating the c-jun N-terminal kinase and p38/mitogen-activated protein kinase (MAPK) (16). Additionally, knockdown of 14-3-3ζ was observed to enhance radio-induced apoptosis in liver cancer stem-like cells (17). Wang et al (18) demonstrated that 14-3-3ζ was upregulated in the hepatocarcinomatous environment, attenuated the anti-tumor function of tumor-infiltrating T cells and may have partially been transferred from liver cancer cells to T cells via exosomes. A recent study revealed that 14-3-3ζ regulated the stability of heme oxygenase 1, which in turn promoted cancer cell proliferation via activation of STAT3 signaling in HCC (19). Nonetheless, the prognostic roles of yhwaz at the mRNA level in HCC remain to be clearly elucidated. In the present study, bioinformatics tools were used to analyze the functional effects of yhwaz expression in liver cancer. The expression of yhwaz was shown to be elevated in liver cancer tissues and cell lines and this upregulation was associated with poor prognosis. Additionally, it was demonstrated that mutations in yhwaz may have important implications in the survival rates of patients with liver cancer. By contrast, upregulated expression levels of microRNAs (miRNAs/miRs) that targeted yhwaz were associated with improved prognosis. The results demonstrated that the regulatory network of 14-3-3ζ and its interacting proteins serve an important role in the development and prognosis of HCC, suggesting the potential application of 14-3-3ζ as a therapeutic target for liver cancer. Additionally, the results of the present study support additional in vitro and in vivo studies on the functional effects of 14-3-3ζ expression in HCC.

Materials and methods

Bioinformatics tools and databases

Several bioinformatics tools were used to analyze yhwaz expression in patients with HCC. The specific tools that were used are listed in Table I.

Table I.

Bioinformatics tools used for analysis in the present study.

Databases	Samples	(Refs.)
HCCDB	Tissues	(20)
TCGA	Tissues	(21)
GTEx	Tissues	(22)
UALCAN	Tissues	(23)
Oncomine	Tissues	(24)
KEGG	N/A	(25)
Kaplan-Meier plotter	Tissues	(26)
cBioPortal	N/A	(27,28)
TargetScan	N/A	(29)
GSEA	N/A	(30,31)
GeneMANIA	N/A	(32)
GEPIA	Tissues	(33)

GEPIA, Gene Expression Profiling Interactive Analysis; HCCDB, Integrative Molecular Database of Hepatocellular Carcinoma; GSEA, Gene Set Enrichment Analysis; N/A, not applicable.

Integrative molecular database of hepatocellular carcinoma (HCCDB)

The HCCDB is a database that contains information on HCC expression (20). In the current database release, HCCDB archived 15 public HCC gene expression datasets (HCCDB1, 3, 4, 6–9, 11–18) containing a total of 3917 samples from The Cancer Genome Atlas (TCGA) (21).

Genotype-tissue expression (GTEx)

Among the 15 datasets from GTEx (https://www.gtexportal.org) (22), 12 datasets contain both tumor and the adjacent normal samples, whereas only tumor samples are available for the three remaining datasets.

UALCAN

UALCAN is an interactive web resource for studying cancer transcriptome data (23). In particular, 50 healthy individuals and 371 patients with primary HCC were used to analyze the association among yhwaz levels and their clinical characteristics.

Oncomine

Oncomine database is a bioinformatics initiative aimed at collecting, standardizing, analyzing, and delivering cancer transcriptome data to the biomedical research community (24). Two microarray datasets Roessler Liver (43 samples) and Roessler Liver 2 (445 samples) were used for analysis in this study. Based on these open source bioinformatics platforms, yhwaz expression profiles were obtained for both human HCC tissues and cell lines.

Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis

KEGG (25) is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies.

Kaplan-Meier plotter

The Kaplan-Meier plotter (26) with the log-rank test was used to determine disease prognosis, including overall survival (OS) time and post-progression survival (PPS) time. Clinical data from TCGA were used for Kaplan-Meier plotter analysis in order to evaluate the clinical relevance of yhwaz mRNA expression levels in HCC. In this project 364 (male, 250; female, 121) HCC RNA-seq samples were used.

CBioPortal

CBioPortal (27,28) can be used to download and analyze large-scale cancer genomics datasets and was used in the present study to analyze mutations in yhwaz. In this project 1065 HCC samples were used for analysis.

TargetScan (version 7.1)

TargetScan (29) was used to predict the biological targets of miRNAs by searching for the presence of conserved 8mer and 7mer sites that matched the seed region of each miRNA.

Gene set enrichment analysis (GSEA)

GSEA (30,31) is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states.

GeneMANIA

GeneMANIA (32) is a flexible, user-friendly web interface for constructing protein-protein interaction (PPI) network, generating hypotheses about gene function, analyzing gene lists, and prioritizing genes for functional assays.

Gene expression profiling interactive analysis (GEPIA)

GEPIA (33) is a newly developed interactive web server for analyzing the RNA sequencing expression data of 9,736 tumors and 8,587 normal samples from the TCGA and the GTEx projects, using a standard processing pipeline.

Tumor grade and tumor stages

The tumor grade is divided into four subtypes: Grade 1, well differentiated (low grade); grade 2, moderately differentiated (intermediate grade); grade 3, poorly differentiated (high grade); and grade 4, undifferentiated (high grade). The tumor stage class depends on the tumor-node-metastasis staging system (AJCC 8th edition) (34).

Statistical analysis

Data are expressed as mean ± SD and analyzed for significance using GraphPad Prism 6.00 software (IBM Corp.). Difference between two-groups was assessed using Student's t-test. One-way ANOVA followed by Newman-Keuls post hoc testing (95% confidence) was used to determine difference among more than two groups. The survival analysis was illustrated by Kaplan-Meier curves with log-rank test. Univariate and multivariate survival analyses were performed using the likelihood ratio test of the stratified Cox proportional hazards model of SPSS 17.0 (IBM Corp.). P<0.05 was considered to indicate a statistically significant difference.

Results

Yhwaz is upregulated in HCC cell lines and tissues

The results from the analysis of the data in the GTEx portal revealed that ywhaz is expressed in multiple organs and tissues (Fig. S1). As yhwaz has been reported to affect a number of different types of cancer, such as liver, lung and breast (3), HCCDB, an analytical tool for gene expression profiling, was used to determine yhwaz expression in tumor and other tissues. As presented in Fig. 1A and Table II, yhwaz expression was significantly higher in tumor tissues compared with tissue adjacent to HCC tissues. Additionally, in patients with cirrhosis, yhwaz expression was higher compared with healthy human liver tissues. Liver HCC tissues exhibited upregulated expression levels of yhwaz compared with healthy liver tissue (Fig. 1B). In order to investigate the changes in yhwaz expression between HCC and adjacent non-tumor tissues, yhwaz expression profiles were used from different independent bioinformatics databases. Based on the gene expression profiles obtained from the UALCAN database, yhwaz was determined to be upregulated in the majority of HCC tissues (Fig. 1C). To confirm this finding, two microarray datasets from the Oncomine database (24) were analyzed (Fig. 1D and E). yhwaz expression levels were significantly increased in HCC tissues compared with in healthy liver tissues. Taken together, these data demonstrate that increased mRNA expression of yhwaz contributed to HCC, indicating its potential role in liver cancer.

Figure 1.

yhwaz expression levels in HCC. (A) mRNA expression levels of yhwaz in cancer tissues. (B) yhwaz expression levels in normal and HCC liver tissues. *P<0.05. (C) RNA expression levels of yhwaz in data obtained from UALCAN. ***P<0.001. (D and E) mRNA expression levels of yhwaz in HCC tissues and the surrounding normal liver tissues. ***P<0.001. HCC, hepatocellular carcinoma.

Table II.

Summary of yhwaz expression profiles based on HCCDB datasets.

Datasets	P-value	Type	Nums	Mean	SD	IQR
HCCDB3	7.20×10−15	HCC	268	10.43	3.269	4.115
		Adjacent	243	8.609	1.632	1.771
		Cirrhotic	40	11.55	1.868	2.095
		Healthy	6	7.790	1.401	1.458
HCCDB4	7.58×10−66	HCC	240	8.692	0.5139	0.6828
		Adjacent	193	7.886	0.2552	0.2674
HCCDB6	2.62×10−52	HCC	225	9.271	0.8106	0.9875
		Adjacent	220	8.014	0.7027	0.8710
HCCDB18	5.66×10−28	HCC	212	6.626	0.8582	1.135
		Adjacent	177	5.774	0.5318	0.5900

HCCDB, Integrative Molecular Database of Hepatocellular Carcinoma; Nums, Number of samples; IQR, interquartile range; SD, standard deviation.

Yhwaz expression may be a prognostic factor in HCC

Although yhwaz has been demonstrated to participate in the development of multiple types of cancer, there are no clear reports on the association between its expression and clinical prognosis in HCC. The prognostic efficacy of the mRNA expression of ywhaz in patients with HCC was analyzed using the Kaplan-Meier plotter (26). As presented in Fig. 2A-C and Table II, increased expression of yhwaz was found to increase the risk of death and decrease survival probability in female (Fig. 2A) and male (Fig. 2B) patients with HCC alone or all both sex combined (Fig. 2C; Table III). Therefore, yhwaz expression analysis was performed with regard to the clinicopathological characteristics of patients. As presented in Fig. 2D, yhwaz expression in African-American patients with HCC was significantly higher compared with Caucasian patients. The expression levels of yhwaz were shown to increase with tumor grade (Fig. 2E). Based on tumor stages (34), the ywhaz expression level was significant higher in patients of all tumor stages compared with healthy individuals, but yhwaz expression levels in stage 3 cancer were significantly higher compared with stage 1 (P<0.01; Fig. 2F), and there were no other significant difference amongst the other stages. The expression levels of yhwaz decreased with age in patients with HCC (Fig. 2G). The weight of patients seemed to have less influence on the expression of yhwaz, with the only significant difference observed between normal weight patients and obese patients with HCC (Fig. 2H), and Together, these data suggest that high expression levels of yhwaz may predict tumors with increased malignancy.

Figure 2.

Association between yhwaz expression and clinical characteristics of patients with HCC. (A-C) Kaplan-Meier analysis of OS time and PPS time in patients with HCC based on yhwaz expression. (D-H) TCGA clinical data and UALCAN were used to categorize patients with HCC according to the expression levels of yhwaz. Data are presented as the mean ± standard error of the mean. *P<0.05, **P<0.01, ***P<0.001 vs. normal. Grade 1, well differentiated (low grade); Grade 2, moderately differentiated (intermediate grade); Grade 3 poorly differentiated (high grade); Grade 4 undifferentiated (high grade); HCC, hepatocellular carcinoma; OS, overall survival; PPS, post-progression survival; TCGA, The Cancer Genome Atlas.

Table III.

Association between yhwaz expression and sex in patients with hepatocellular carcinoma.

Sex	Gene IDs	HR	95% CI	P-value
Female	7534	5.20	2.05–13.19	0.00011
Male	7534	2.02	1.29–3.16	0.0016
All	7534	1.74	0.95–3.20	0.07

HR, hazard ratio; CI, confidence interval.

Yhwaz mutations affect the outcome of patients with HCC

Mutations in a gene may not always affect the function of the coded proteins. In the cBioPortal data sets, based on the TCGA, there were 8 studies (35–40) on HCC, and mutations, amplification and deep deletions were observed in the yhwaz sequence in these datasets (Fig. 3A). yhwaz was mutated or otherwise altered in 98 (7.00%) of the 1,487 patients. These alterations were amplified in 90 cases (6.00%), deep deletion in 2 cases (0.13%) and mutations in 6 cases (0.40%). Therefore, amplification was the most common type of yhwaz alteration in HCC. The 6 mutations identified are shown in Table IV, and the single nucleotide polymorphisms seen were S207I, N108S, R127G and C94S. The biological interaction network of yhwaz was next identified in HCC. The tab Network in cBioPortal was used to show yhwaz neighboring genes that were altered with a frequency >15% (Fig. 3B; Table V). The neighbor genes of yhwaz with highest frequency of alterations were CRTC2 (38.1%), SDC2 (34.4%) and F11R (29.2%). OS and disease-free survival were significantly decreased in patients with yhwaz alterations compared with individuals without alterations (Fig. 3D), suggesting that alterations in yhwaz may affected the survival of patients with HCC.

Figure 3.

yhwaz mutation types in HCC. (A) Mutation types in patients with HCC. (B) Network view of the yhwaz neighborhood in LIHC. yhwaz seed genes (indicated with a different colour), and all the other genes were automatically identified as altered in LIHC. Darker red indicates increased frequency of alteration in LIHC. The interaction types are derived from BioPAX: Blue connections indicate that the first protein controls a reaction that changes the state of the second protein; red connections indicate proteins are members of the same complex. (C and D) Overall survival time and disease-free survival time of patients with HCC with alterations in the yhwaz gene. BioPAX, Biological Pathway Exchange; HCC, hepatocellular carcinoma; LIHC, liver HCC.

Table IV.

Known mutations in the yhwaz gene.

Sample ID	Protein change	Type of mutation	Copy no.	COSMIC	Allele frequency (T)	No. of mutations
CHC1915T	N108S	Missense		1		39
CHC703T	R127G	Missense				104
CHC1915T	N108S	Missense		1		36
H093892	S207I	Missense	Diploid		0.04	74
TCGA-DD-A115-01	C94S	Missense	ShallowDel		0.08	66
TCGA-DD-A115-01	C94S	Missense	ShallowDel		0.07	80

Table V.

Type and frequency of yhwaz neighbor gene alterations in patients with hepatocellular carcinoma.

Gene symbol	Amplification	Homozygous deletion	Upregulation	Downregulation	Mutation	Total alteration
YWHAZ	15.3	0.3	23.6	0	0.3	30.8
AGPT1	16.7	0.3	7.5	0	1.4	23.1
CRTC2	12.2	0	34.2	0	0.8	38.1
CSNK1D	6.9	0.6	11.1	0.6	0	15.8
DEPTOR	17.5	0.3	14.7	0	0.3	28.3
F11R	11.4	0	24.2	0	0.3	29.2
MAPK14	3.1	0.3	20.3	1.1	0.6	22.5
NTRK1	11.9	0	1.9	0	1.1	15.0
PPP2CA	0.6	0	13.9	3.1	0.6	17.5
PPP2R2A	0	6.1	2.5	9.7	0.8	18.1
PPP2R5A	8.9	0	24.2	0	0	28.3
PTP4A3	16.4	0.3	11.7	0	0.8	23.9
SDC2	15.3	0.3	21.9	2.5	0.3	34.4
SHC1	13.6	0	8.9	0	0.8	20.6

Increased expression of miRNAs that target yhwaz are associated with improved survival time in patients with HCC

miR-22 has been reported to target yhwaz and inhibit its expression in HCC cells (41). miRNAs that targeted yhwaz were predicted using TargetScan. As presented in Fig. 4A, miR-22 and miR-1/miR-206 were predicted to exhibit a higher probability of binding with yhwaz. miR-451 negatively regulated the expression of yhwaz through binding with the 3′untranslated region of yhwaz (42). miR-155 and miR-140 were also predicted to exhibit a high probability of binding with yhwaz. For reasons not yet known, the survival curves for miR-140-3p (Fig. 4G) exhibited a late stage crossover. The most mentioned miRNAs that were predicted to bind with yhwaz, were associated with improved survival time in patients with HCC when expression was upregulated (Fig. 4B-G; Table VI). Together, these data show that miRNAs that were predicted to target yhwaz were associated with improved survival time in patients with HCC.

Figure 4.

miRNAs targeting yhwaz and the effect of miRNA expression levels on survival in patients with HCC. (A) miRNAs predicted to target yhwaz. (B-G) Kaplan-Meier analysis of survival times in patients with HCC based on miR-22, miR-1, miR-451, miR-155, miR-206 and miR-104 expression, all of which were predicted to target yhwaz. HCC, hepatocellular carcinoma; miRNA/miR, microRNA; OS, overall survival; PPS, post-progression survival.

Table VI.

Association between yhwaz targeting miRNAs and survival time in patients with hepatocellular carcinoma.

miRNAs	Gene IDs	HR	95% CI	P-value
miR-22	Has-miR-22	0.47	0.32–0.67	2.6×10−5
miR-1	has-miR-1	0.6	0.41–0.87	0.0072
miR−451	has-miR-451	0.68	0.36–1.28	0.23
miR−155	has-miR-155	0.51	0.28–0.91	0.021
miR−206	has-miR-206	0.37	0.24–0.59	1.2×10−5
miR−140	has-miR-140-3p	0.74	0.45–1.21	0.23

miRNA/miR, microRNA; hsa, homosapien; HR, hazard ratio; CI, confidence interval.

KEGG pathway analysis of co-expression genes correlated with yhwaz and its networks of kinase and miRNA targets in HCC

To further examine the targets of yhwaz in HCC, the KEGG pathway analysis was used to determine the kinase and miRNA target networks of associated gene sets generated by Gene Set Enrichment Analysis (GSEA) (30,31). KEGG pathway analysis showed enrichment in tumor necrosis factor, proteoglycans in cancer and miRNAs in cancer pathways (Fig. 5A). The miRNA-target network was associated with miR-149 (GAG CCA G), miR-133A/miR-133B (GGG ACC A) and miR-296 (GGG GCC C). The most significant target networks were the kinase-target networks associated primarily with the MAPK2, Rho Associated Coiled-Coil Containing Protein Kinase 1 and Polo-like Kinase 1 (Table VII). The protein-protein interaction network constructed by GeneMANIA (32) revealed associations amongst genes for MAPKAPK2 and miRNA-149. The GSEA for MAPK2 is responsible primarily for regulating the cell cycle, kinase activity and the immune response (Fig. 5B), and the GSEA for miRNA-527 (Fig. 5C) was involved primarily in the regulation of cell activation, kinase activity and leukocyte activation.

Figure 5.

Enrichment analysis of yhwaz functional networks in HCC. (A) KEGG analysis of yhwaz co-expression genes in HCC. (B and C) Protein-protein interaction network and functional analysis of gene sets that were enriched in the target network of MAPKAPK2 kinases and miR-527. Different colors of the network edge indicate the bioinformatics methods applied: Co-expression, website prediction, pathway, physical interactions and co-localization. The different colors of the network nodes indicate the biological functions of the set of enrichment genes. HCC, hepatocellular carcinoma; KEGG, Kyoto Encyclopedia of Genes and Genomes; MAPKAPK2, mitogen-activated protein kinase-activated protein kinase 2; TNF, tumor necrosis factor.

Table VII.

Kinase and miRNA target networks of yhwaz in hepatocellular carcinoma.

Enriched category	Geneset	Leading EdgeNum	FDR
miRNA target	GAGCCAG, MIR-149	46	0.039256
	GGGACCA, MIR-133A, MIR-133B	52	0.038166
	GGGGCCC, MIR-296	21	0.037802
Kinase target	Kinase_MAPKAPK2	12	0.043584
	Kinase_ROCK1	19	0.035556
	Kinase_PLK1	41	0.030585

miRNA, microRNA; FDR, false discovery rate.

Discussion

The 14-3-3 family of proteins serve various roles in signaling and interact with several protein partners, including their function as adaptors that stimulate protein-protein interactions (3,41). Among the 14-3-3 proteins, the 14-3-3ζ isotype is one of the most studied members of this family (42). 14-3-3ζ interacts with numerous key cellular proteins involved in tumor development and progression (43). The importance of 14-3-3ζ in the development and progression of cancer has been demonstrated in a number of different types of cancer (44). In the present study, bioinformatics analysis was used to determine the prognostic value of yhwaz in liver cancer, and the results revealed that yhwaz expression was upregulated in HCC tissues and cell lines. Upregulated levels of yhwaz were significantly associated with a poor prognosis. Mutations in yhwaz significantly affected the survival time of patients with HCC, and miRNAs that targeted yhwaz were associated with outcomes of HCC.

14-3-3ζ has been suggested to be a potential prognostic marker and therapeutic target in a number of different types of cancer (43). 14-3-3ζ overexpression increases Akt phosphorylation and further increased hypoxia-inducible factor-1α expression in HCC cells (45,46). In the present study, yhwaz expression was upregulated in the major and different sub-types of HCC. 14-3-3ζ has been hypothesized to bind with the hepatitis B virus (HBV) protein X (HBx) and maintain its protein stability in HCC cells. In cancer cells where 14-3-3ζ was silenced, the cells exhibited decreased migratory and invasive capacities, and this was accompanied by decreased expression of HBx (47). Together, these data suggest that upregulated expression of 14-3-3ζ may increase the risk of HBV infection.

14-3-3ζ targets and affects the phosphorylation of a number of proteins, a number of which are involved in tumor-promoting processes, such as regulation of autophagy and tumor suppressor pathways (48). Thus, alterations in yhwaz expression may result in cancer of the liver through regulation of these pathways and processes. The most common type of alteration observed in HCC was amplification, which was observed in 6% of cases. Multiple yhwaz mutations have been observed in patients with liver cancer, the majority of which are primarily phosphorylation sites. p-AKT is the one of the targets of 14-3-3ζ, upregulation of both 14-3-3ζ. p-Akt in patients with HCC predicts a poor prognosis, and 14-3-3ζ triggers activation of the Akt signaling pathway, thus contributing to the development of HCC (49). However, in patients with upregulated expression of miRNAs that target ywhaz, prognosis was predicted to be improved compared with patients with lower expression levels of the same miRNAs. Enrichment analysis of yhwaz co-expression genes determined that the majority of the interacting genes were involved in processes associated with cancer progression, and yhwaz target GSEA may assist in identifying important networks of target kinases and miRNAs.

The present study used the online tools to perform target gene analysis on tumor data from public databases. At the same time, the limitation is that transcriptome sequencing can only detect static mutations; it does not directly provide information on protein activity or expression levels. These issues should be addressed in subsequent research using molecular biology techniques. The other one limitation is that the LIHC samples contained a relatively small number of stage 4 patients, but the clinical reality is that most patients with HCC are diagnosed for the first time when the disease progresses, and thus, the prognosis is extremely poor. Therefore, the results of the present study should be validated in clinical samples including a full coverage of different ethnic groups and HCC stages.

The present study provided theoretical evidence of the importance of yhwaz expression in hepatocarcinogenesis and highlighted its potential as a marker in HCC. Based on the results of the present study, it may be hypothesized that targeting 14-3-3ζ in patients with liver cancer may effectively improve the survival rates and prognosis of patients.