Expression of SUMO and NF-κB genes in hepatitis B virus-associated hepatocellular carcinoma patients: An observational study

Abstract

Alterations in signaling pathways and modulation of cell metabolism are associated with the pathogenesis of cancers, including hepatocellular carcinoma (HCC). Small ubiquitin-like modifier (SUMO) proteins and NF-κB family play major roles in various cellular processes. The current study aims to determine the expression profile of SUMO and NF-κB genes in HCC tumors and investigate their association with the clinical outcome of HCC. The expression of 5 genes – SUMO1, SUMO2, SUMO3, NF-κB p65, and NF-κB p50 – was quantified in tumor and adjacent non-tumor tissues of 58 HBV-related HCC patients by real-time quantitative PCR and was analyzed for the possible association with clinical parameters of HCC. The expression of SUMO2 was significantly higher in HCC tumor tissues compared to the adjacent non-tumor tissues (P = .01), while no significant difference in SUMO1, SUMO3, NF-κB p65, and NF-κB p50 expression was observed between HCC tumor and non-tumor tissues (P > .05). In HCC tissues, a strong correlation was observed between the expression of SUMO2 and NF-κB p50, between SUMO3 and NF-κB p50, between SUMO3 and NF-κB p65 (Spearman rho = 0.83; 0.82; 0.772 respectively; P < .001). The expression of SUMO1, SUMO2, SUMO3, NF-κB p65, and NF-κB p50 was decreased in grade 3 compared to grades 1 and 2 in HCC tumors according to the World Health Organization grades system. Our results highlighted that the SUMO2 gene is upregulated in tumor tissues of patients with HCC, and is related to the development of HCC, thus it may be associated with the pathogenesis of HCC.

1. Introduction

Hepatocellular carcinoma (HCC) remains a significant global health challenge, marked by its annual increase in both incidence and mortality rates. According to the Global Cancer Observatory (GLOBOCAN) 2020 data, HCC ranks 5th highest in incidence among men and 9th highest among women globally. In Vietnam, HCC stands as the leading cause of both incidence and mortality.^[1,2] The overall prognosis for HCC patients remains unfavorable due to the limited frequency of early detection and the high likelihood of recurrence.^[3] While numerous factors contribute to HCC development, chronic hepatitis B virus (HBV) infection plays a crucial role, particularly in regions with high HBV endemicity like Vietnam.^[4,5] The prevalent HBV chronic infection has long been identified as a significant risk factor for HCC development. The molecular mechanisms through which HBV induces HCC are complex, involving interactions among viral proteins, host cellular factors, and the tumor microenvironment. HBV can induce genetic instability and epigenetic modifications in host DNA, resulting in dysregulated expression of oncogenes and tumor suppressor genes.^[6] Moreover, HBV triggers chronic inflammation, altering the liver environment and fostering tumor formation by evading immune surveillance. Additionally, it activates various cancer-related signaling pathways and modulates cell metabolism.^[7]

Targeting SUMOylation pathways has emerged as a promising therapeutic strategy for treating HCC.^[8,9] SUMOylation is a post-modification process involving the covalent attachment of small ubiquitin-like modifier (SUMO) proteins to target proteins.^[10] In humans, 5 functional SUMO isoforms are encoded by the SUMO1, SUMO2, SUMO3, SUMO4, and SUMO5 genes, with SUMO2 and SUMO3 sharing about 92% identity.^[11] SUMO proteins play major roles in various cellular processes, including gene expression, signal transduction, DNA repair, and protein stability.^[12,13] Recent studies have revealed that the SUMO system plays an essential role in cancer progression by disrupting the balance between sumoylation and desumoylation of many oncoproteins and tumor suppressors.^[14] Altered expression levels or activities of SUMO proteins and SUMOylation enzymes have been observed in HCC tissues compared to adjacent non-tumor liver tissues.^[15,16] Therefore, abnormal expression of SUMO proteins could serve as a new biomarker for HCC.

Nuclear factor κB (NF-κB) comprises a family of transcription factors that play crucial roles in regulating immune and inflammatory responses, cell proliferation, apoptosis, and stress responses.^[17] This factor binds to the enhancer element of the immunoglobulin kappa light-chain in activated B cells.^[18] Five members of this family have been recognized, named as p65 (RelA), RelB, c-Rel, NF-κB1 (p105 and p50), and NF-κB2 (p100 and p52). Emerging evidence highlights NF-κB’s tumor-promoting role and its involvement in inflammation-driven cancer, closely linked to all cancer hallmarks.^[19] NF-κB also plays a fundamental role in regulating the immune response to infection, and aberrations in NF-κB regulation can lead to cancer.^[20] Among the NF-κB family members, NF-κB p65 (RelA) and NF-κB p50 have garnered particular attention due to their potent transcriptional activity and involvement in promoting tumorigenesis. Several studies have indicated that NF-κB p65 plays an important role in promoting HCC development by modulating the expression of genes within its signaling pathway.^[21,22] However, the specific role of NF-κB p65 and p50 in HCC remains complex and multifaceted, requiring further investigation to completely elucidate its contribution to disease pathogenesis.

Studies have indicated a close association between SUMO proteins and the NF-κB activation pathway, particularly involving the p65 subunit, in the development of HCC.^[23,24] However, the interplay between SUMOylation and the NF-κB signaling pathway, particularly regarding the expression of its genes, remains under investigation. In this study, our aim is to investigate the expression profiles of SUMO genes (SUMO1, SUMO2, SUMO3) and the NF-κB pathway (p65, p50) in patients with HCC and their association with clinical parameters.

2. Methods

2.1. Study subjects

The study enrolled 58 HBV-related HCC patients who underwent surgery as the initial treatment at the 103 Military Hospital, the 108 Military Central Hospital, and the Vietnam National Cancer Hospital in Hanoi, Vietnam. Patients were diagnosed with HCC based on the practice guidelines of the American Association for the Study of Liver Diseases (AASLD)^[25] and Vietnamese Ministry of Health guidelines. Diagnosis was confirmed through typical imaging features on computed tomography (CT) imaging or magnetic resonance imaging (MRI) accompanied by elevated levels of alpha-fetoprotein (AFP), or by pathological diagnosis. Patients were staged according to the Barcelona Clinic Liver Cancer (BCLC) classification system.^[26] HBV infection status of these patients was confirmed and other risk factors for the disease, such as hepatitis C virus infection and alcoholic liver disease, were also determined. Liver function was categorized according to Child-Pugh scores. All participants underwent blood tests for counts, total and direct bilirubin, prothrombin, albumin, alanine transaminase (ALT), aspartate transaminase (AST), and the tumor marker alpha-fetoprotein (AFP). Liver tumor and adjacent non-tumor tissue samples were frozen at −80 °C for gene expression analysis, while the remaining samples were processed for pathological assessment.^[27] The baseline characteristics of the patients are presented in Table 1.

Table 1.

Characteristics of 58 HCC patients.

Characteristics	n (%)	Characteristics
Age (yr)	59 (39–74)	Histologic characteristics
Gender		Trabecular	31 (53.4)
Male	52 (89.7)	Solid	20 (34.5)
Female	6 (10.3)	Pseudoglandular	3 (5.2)
Child-Pugh classification		Mixed	4 (6.9)
A	58 (100)	Histologic characteristics
Other groups	0 (0)	Usual	32 (55.2)
BCLC staging classification		Clear cell	12 (20.7)
0	2 (3.4)	Steatohepatic	4 (6.9)
A	47 (81.0)	Scirrhous	1 (1.7)
B	1 (1.7)	Chromophobe	1 (1.7)
C	8 (13.8)	Mixed	8 (13.8)
Number of tumors		Necrosis
1	49 (84.5)	Yes	21 (36.2)
2	4 (6.9)	No	37 (63.8)
3	2 (3.4)	Microvascular invasion
4	3 (5.2)	Yes	27 (46.6)
Tumor diameter (mm)	45 (15.0–113)	No	31 (53.4)
Tumor location		Clinical parameters	Median [Min–Max]
Right lobe	48 (82.8)	WBC (×106/mL)	6.56 (4–13.6)
Left lobe	8 (13.8)	RBC (×103/mL)	4.8 (2.61–6.82)
Both	2 (3.4)	HCT (%)	0.45 (0.3–0.53)
Portal vein invasion		PLT (×103/mL)	178.5 (80–463)
Yes	5 (8.6)	INR	1.06 (0.9–1.42)
No	53 (91.4)	Prothrombin (% of standard)	93.8 (58.8–118)
Distal metastasis		Glucose	5.08 (2.84–10.84)
Yes	5 (8.6)	AST (IU/mL)	42.8 (21.9–125)
No	53 (91.4)	ALT (IU/mL)	46 (13.4–173.9)
WHO grade classification		Total bilirubin (µmol/L)	12.3 (6.6–33.5)
Grade 1	1 (1.7)	Direct bilirubin (µmol/L)	3.15 (0.5–10.9)
Grade 2	52 (89.7)	Protein (g/L)	74.6 (55.9–84.8)
Grade 3	5 (8.6)	Albumin (g/l)	41.3 (29.7–46.8)
		AFP (IU/mL)	59.46 (1.51–3000)

AFP = alpha-fetoprotein, AST and ALT = aspartate and alanine aminotransferase, BCLC = Barcelona Clinic Liver Cancer, ES = Edmondson-Steiner, HBV = HCV, hepatitis B, and hepatitis C virus, HCC = hepatocellular carcinoma, HCT = hematocrit, IU = international unit, NA = not applicable, PLT = platelets, RBC = red blood cells, WBC = white blood cells.

2.2. Quantification of relative gene expression by quantitative real-time PCR

Total RNA was extracted from the 58 pairs of liver tumor and adjacent non-tumor tissue using the MasterPure Complete DNA and RNA Purification Kit (LGC, Biosearch Technologies, Teddington, UK) following the manufacturer’s protocols. The extracted total RNA samples were reverse transcribed into cDNA using the Maxima First Strand cDNA Synthesis Kit (ThermoFisher, Waltham). The cDNA was quantified by real-time quantitative PCR with GAPDH (Glyceraldehyde-3-phosphate dehydrogenase) used as the reference gene. The primer sequences designed for qPCR is to target the translated region and most of the transcripts of the target genes. The primer sequences cover the splicing positions of 2 exons to exclusively amplify the cDNA, which is reverse transcribed from mRNA, and not the genomic DNA sequence. The sequences of primers used in this study are presented in Table 2. Real-time quantitative PCRs were carried out in a final volume of 25 μL, containing 12.5 μL of SYBR Green PCR master mix (2×) (Roche Molecular Biochemicals, Basel, Switzerland), 0.5 µM of primer pairs specific for the target genes and the reference gene, 5 ng of cDNA samples, and RNase-free water up to the 25 μL reaction volume. Thermal cycling conditions were as follows: 95 °C for 2 minutes for initial activation, followed by 40 cycles of denaturation at 95 °C for 10 seconds, annealing at 62 °C for 10 seconds, and extension at 72 °C for 16 seconds. Melting curve analyses starting from 58 to 85 °C were performed after each run to confirm the specificity of the PCR products. All reactions were duplicated and repeated twice using the LightCycler System (Roche, Basel, Switzerland). The relative expression of target genes was normalized to the expression of GAPDH based on the ΔCt method.

Table 2.

Primers used for this study.

Primer	Sequence (5′–3′)	Product length (bp)
SUMO1-F	ACCGTCATCATGTCTGACCA	183
SUMO1-R	TGGAACACCCTGTCTTTGAC
SUMO2-F	GGGCAACCAATCAATGAAAC	198
SUMO2-R	AGTCAGGATGTGGTGGAACC
SUMO3-F	CTGGCCCTCAAGCATGTAAC	201
SUMO3-R	AAATCTGAGGCCACAACACC
NF-κB p50-F	TGGCACTGCCAACAGATGG	182
NF-κB p50-R	AACCTTTGCTGGTCCCACAT
NF-κB p65-F	CTGAATGCTGTGCGGCTCT	199
NF-κB p65-R	GCACCTTGTCACACAGTAGGAA
GAPDH-F	GGAGCGAGATCCCTCCAAA	197
GAPDH-R	GGCTGTTGTCATACTTCTCAT

2.3. Ethics statement

The study details were explained to each participant before sampling, and written informed consent was obtained from all study participants. The study received approval from the Institutional Review Board of the 103 Military Hospital, Hanoi, Vietnam.

2.4. Statistical analysis

Quantitative parameters including laboratory tests and relative gene expression values are given as means with standard deviation or medians with ranges where appropriate. The relative gene expression between tumor and adjacent non-tumor tissues was compared using the Wilcoxon signed ranks test. Spearman rank correlation coefficient was used to analyze the correlation of relative gene expression between 2 genes or between the expressions of the genes with clinical parameters. In addition, a generalize linear model that adjusts for confounding factors such as age, gender, and disease stage was used to determine the relationship between gene expression and clinical parameters. The SPSS software version 26.0 (SPSS Statistics, IBM, Armonk, NY) was used for all statistical analyses. The level of significance was set at a P value of <.05.

3. Results

3.1. Gene expression in HCC patients

The relative expression of the 5 genes – SUMO1, SUMO2, SUMO3, NF-κB p65, and NF-κB p50 – related to SUMOylation and the NF-κB pathway, respectively, was quantified and compared between HCC tumor and adjacent non-tumor tissues. The expression of SUMO2 was significantly higher in HCC tumor tissues compared to adjacent non-tumor tissues (P = .01, Fig. 1B). However, no significant difference in the expression of SUMO1, SUMO3, NF-κB p65, and NF-κB p50 was observed between HCC tumor tissues and non-tumor tissues (P > .05) (Figs. 1A, C, D, and E). These results indicate that SUMO2 is upregulated in HCC tumors and might be associated with the development of HCC.

Figure 1.

Gene expression in tumor and adjacent non-tumor tissues. (A) Relative expression of SUMO1. (B) Relative expression of SUMO2. (C) Relative expression of SUMO3. (D) Relative expression of NF-κB p65. (E) Relative expression of NF-κB p50. NS: not significant. P values were calculated by the Wilcoxon signed ranks test.

3.2. Correlation of mRNA expression between genes

The correlations of mRNA expression among the study genes in both HCC tumor and non-tumor tissues were analyzed. In HCC tissues, strong correlations were observed between the expression of SUMO2 and NF-κB p50 (Spearman rho = 0.83; P < .001), between SUMO3 and NF-κB p50 (Spearman rho = 0.82; P < .001), between SUMO3 and NF-κB p65 (Spearman rho = 0.772; P < .001) (Table 3). In non-tumor tissues, we observed a positive correlation between SUMO3 expression and NF-κB p65 (Spearman rho = 0.676; P < .001). The correlation of NF-κB p50 expression with SUMO3 and NF-κB p65 was moderately positive (Spearman rho = 0.652 and 0.644; P < .001; respectively). However, no significant correlation was observed between SUMO2 and NF-κB p65 expression (P = .067) (Table 3).

Table 3.

Correlation of relative expression between genes in tumor tissues and in adjacent non-tumor tissues.

Gene	SUMO1		SUMO2		SUMO3		NF-κB p65		NF-κB p50
	r s	P	r s	P	r s	P	r s	P	r s	P
SUMO1			0.272	.039	0.462	<.0001	0.547	<.0001	0.45	<.0001
SUMO2	0.412	.001			0.274	.037	0.242	.067	0.492	<.0001
SUMO3	0.544	<.0001	0.720	<.0001			0.676	<.0001	0.652	<.0001
NF-κB p65	0.428	.001	0.452	<.0001	0.772	<.0001			0.644	<.0001
NF-κB p50	0.483	<.0001	0.830	<.0001	0.820	<.0001	0.694	<.0001

r_s and P values in the lower-left area are the correlation of relative expression between genes in tumor tissues while those in the upper-right area are the correlation of relative expression between genes in adjacent non-tumor tissues.

Regarding gene expression between tumors and adjacent non-tumor tissues, we found that the expression of SUMO1 in non-tumor had a negative correlation with that of SUMO2 and NF-κB p50 genes in tumors (Spearman rho = −0.449 and −0.326; P < .001 and 0.013; respectively) (Table 4).

Table 4.

Correlation of relative expression between genes in tumor and adjacent non-tumor tissues.

		HCC tumor tissue
		SUMO1		SUMO2		SUMO3		NF-κB p65		NF-κB p50
		r s	P	r s	P	r s	P	r s	P	r s	P
Adjacent non-tumor tissues	SUMO1	−0.158	.236	−0.449	<.0001	−0.246	.062	−0.101	.448	−0.326	.013
	SUMO2	0.007	.956	0.242	.068	0.174	.192	0.111	.409	0.248	.061
	SUMO3	−0.041	.761	−0.034	.799	0.203	.126	0.251	.057	0.159	.234
	NF-κB p65	−0.137	.306	−0.257	.052	−0.162	.224	−0.162	.224	−0.120	.370
	NF-κB p50	−0.104	.436	0.047	.724	0.183	.169	0.183	.169	0.175	.189

3.3. Association of SUMO and NF-κB gene expression with clinical parameters

The association between gene expression and the progression of HCC was then examined. We observed that the expression of SUMO1, SUMO2, SUMO3, NF-κB p65, and NF-κB p50 was decreased in grade 3 compared to grades 1 and 2 in HCC tumors according to the World Health Organization (WHO) grades system (P = .039, 0.039, 0.039, 0.017, and 0.03; respectively) (Fig. 2). Conversely, we observed an opposite trend in the BCLC staging system; however; the difference was not statistically significant (P > .05) (Fig. 3). This result suggests that the expression of SUMOs and NF-κB (p65 and p50) contributes to the malignant progression of HCC.

Figure 2.

Genes expression in tumor tissue in WHO grades. (A) Relative expression of SUMO1. (B) Relative expression of SUMO2. (C) Relative expression of SUMO3. (D) Relative expression of NF-κB p65. (E) Relative expression of NF-κB p50. Grade 1: well differentiated; Grade 2: moderately differentiated; Grade 3: poorly differentiated. NS = not significant. P values were calculated by the Mann–Whitney test.

Figure 3.

Gene expression in tumor tissue in BCLC stages. (A) Relative expression of SUMO1. (B) Relative expression of SUMO2. (C) Relative expression of SUMO3. (D) Relative expression of NF-κB p65. (E) Relative expression of NF-κB p50. BCLC = Barcelona Clinic Liver Cancer; Stage 0: very early; Stage A: early; Stage B: immediate; Stage C: advanced. NS = not significant. P values were calculated by the Mann–Whitney test.

The correlation between gene expression and laboratory parameters of HCC patients was analyzed using Spearman correlation and generalize linear model that adjusts for confounding factors such as age, gender, and disease stage, no correlation was observed between the blood tests and the expression profile of the investigated genes in HCC tumor tissues.

4. Discussion

HCC is a prevalent malignancy and a leading cause of cancer-related deaths worldwide. Presently, the molecular pathogenesis leading to HCC is not fully understood, resulting in a low early diagnosis rate. Therefore, discovering molecular mechanisms and diagnostic biomarkers of HCC is of great clinical significance. Our results shows that the expression of SUMO1, SUMO2, SUMO3, NF-κB p65, and NF-κB p50 was associated with the development of HCC tissue.

Similar to the ubiquitination pathway, SUMOylation is a posttranslational modification process essential for various cellular processes. Posttranslational modification involves enzymatic modifications of proteins after their biosynthesis and is believed to significantly impact the progression of HCC and its therapeutic approaches.^[28] SUMOylation, along with other posttranslational modifications, can alter the characteristics of the target protein, such as its activity, location, stability, and interactions with other proteins.^[29,30] Additionally, SUMOylation plays a major role in transcriptional regulation, regulating many signaling pathways, steroid hormone receptor pathways, chromatin remodeling processes, and cell division processes.^[14] Consequently, an imbalance in posttranslational modifications can lead to the development of different diseases, including cancer.^[31] Irregular SUMOylation of specific proteins has been linked to several types of cancers, such as colorectal cancer, cervical adenocarcinoma, and cervical adenosquamous carcinoma.^[32] Inhibiting the SUMOylation of the target protein can impede the advancement of cancer cells and activate interferon signal transduction, thereby boosting the tumor immune response in the individual. Increasing evidence indicates that SUMO protein is significantly involved in HCC progression. Modulating SUMO protein expression could potentially disrupt HCC development, positioning SUMO as a promising target for HCC therapy. Moreover, varying levels of SUMO protein expression can influence the sensitivity of HCC to chemotherapy and impact resistance to HCC treatment.^[33]

Our study reveals a noticeable increase in the expression of SUMO2 in HCC tumors compared to adjacent non-tumor tissues. This finding suggests that SUMO2 may specifically play a significant role in the development and/or progression of HCC. This observation aligns with a study by Chen et al, which demonstrated increased SUMO2 mRNA expression levels in liver cancer tissues compared with adjacent tissues.^[34] Another previous study also showed that SUMO2 is upregulated and contributes to regulate the cell cycle in HCC.^[35] Using siRNA to knock down SUMO2 expression, the authors showed that downregulation of SUMO2 may inhibit the proliferation, clone formation, and invasive ability of liver cancer cells. Furthermore, recent studies have shown a significant increase in the expression level of SAE1 (SUMO-activating enzyme subunit 1) in HCC tumors.^[16] SAE1, a subunit of the heterodimeric E1 enzyme along with SAE2, activates the protein SUMO and has been implicated in promoting HCC progression mainly through SUMOylation.^[36] Interestingly, a previous study found higher cytoplasmic SUMO2/3 protein expression levels in HCC adjacent tissues than in HCC tumor tissues.^[37] Additionally, overexpression of SUMO2/3 reduces the proliferation ability of HCC cells. However, the authors noted the challenge of accurately distinguishing between SUMO2 and SUMO3 proteins due to their high sequence similarity, which prevents their differentiation by antibodies. On the other hand, recent reports indicate the upregulation of SUMO2 protein expression levels in HCC tissues compared to adjacent non-tumor tissues.^[16] These findings collectively underscore the role of SUMO in HCC and the potential of SUMO2 expression levels as a diagnostic marker for HCC. Although the upregulation of SUMO1 and SUMO3 in HCC tumors and their roles in HCC progression have been widely reported,^[23] SUMO1 and SUMO3 expression did not show significant differences between HCC tumor and non-tumor tissues.

Prolonged inflammation in the liver is the primary cause of HCC. Recent studies on HCC have underscored the contribution of NF-κB, a central factor in inflammation control and immunosuppression. Our study evaluated the expression levels of NF-κB p65 and p50, 2 members of the NF-κB family that play important roles in regulating inflammation and tumorigenesis. We observed that mRNA expression levels of NF-κB p65 and p50 were higher in HCC tumors compared with adjacent non-tumor tissues; however, the difference was not statistically significant. Silva-Gomez et al demonstrated that downregulation of NF-κB p65 expression can inhibit the progression of HCC.^[38] SUMOylation has been known to be involved in the pathogenesis of HCC by affecting various proteins in several signaling pathways, including the NF-κB pathway. Our results revealed that SUMO1, SUMO2, and SUMO3 expressions were significantly correlated with NF-κB p65 and p50 in HCC tissues, suggesting that NF-κB p65 and p50 may be SUMOylated by SUMO genes, leading to abnormalities in the cell cycle. A previous study has shown that SUMOylation of NF-κB p65 by SUMO1 protein can promote p65 nuclear import, increase NF-κB activity, and contribute to HCC.^[23] Our study indicates that the expression level of SUMO1 moderately correlates with NF-κB p65 and p50 in HCC tumors. We also found a strong correlation between SUMO3 expression levels and NF-κB p65 and p50. Liu et al^[37] similarly found that protein SUMO2/3 in HCC tumor tissues is closely related to NF-κB p65 expression. We propose that SUMO3 may also be involved in the SUMOylation of NF-κB p65 and p50 in HCC tumors. Although our results were found in the HCC patients with HBV infection, similar results could be found in HCC patients associated with other factors.^[35,36] Nevertheless, the interaction between SUMO proteins with NF-κB signaling pathway may be more likely subjected to HCC due to chronic viral hepatitis.

Finally, we compared the expression levels of SUMOs and NF-kB genes between early stage tumors and later stages. We observed that the mRNA expression of SUMOs, NF-κB p65 and p50 was lower in early (0 and A stage) compared to stages B and C of the BCLC staging system; however, the difference was not statistically significant. Studies suggest that increased expression of SUMOs and NF-kb may promote the progression of tumors to a more aggressive state.^[14,39] Nevertheless, with the WHO grades system, the expression of SUMO1, SUMO2, SUMO3, NF-κBs p65 and p50 in grade 3 was lower than that in grades 1 and 2 in HCC tumors. This contradictory result may be explained by the limited sample size of patients with WHO stage 3 HCC in our study. This could be one of the limitations of the current study. Another limitation is that the expression profile of the SUMO and NF-κB genes has not been validated by other methodologies, such as Western blot or immunohistochemistry. Therefore, these techniques should be added to confirm their expression in HCC tissues before considering them as biomarkers for HCC.

5. Conclusions

In conclusion, the current study revealed the expression profile of genes that are involved in the SUMOylation process and the NF-kB signaling pathway in HCC. Particularly, SUMO2 play a crucial role in the progression of HCC, thus potentially serving as a marker for HCC diagnosis. Further studies are needed to clarify the role of SUMO3 and NF-κB p65 and p50 in liver cancer.

Acknowledgments

We thank all patients for their participation.

Author contributions

Data curation: Nguyen Xuan Khai, Duong Quang Huy, Do Thi Trang, Ngo Tuan Minh, Truong Dinh Tien, Nguyen Viet Phuong, Nguyen Viet Dung, Ngo Thu Hang.

Funding acquisition: Nguyen Xuan Khai, Nguyen Huy Hoang.

Investigation: Nguyen Xuan Khai, Duong Quang Huy, Do Thi Trang, Ngo Tuan Minh, Truong Dinh Tien, Nguyen Viet Dung, Ngo Thu Hang.

Project administration: Nguyen Xuan Khai, Ngo Tuan Minh, Nguyen Viet Dung, Nguyen Huy Hoang, Nguyen Thi Xuan, Can Van Mao.

Resources: Nguyen Xuan Khai, Duong Quang Huy, Nguyen Viet Phuong, Nguyen Viet Dung, Nguyen Huy Hoang, Nguyen Thi Xuan.

Writing – original draft: Nguyen Xuan Khai, Ngo Tuan Minh, Le Van Khanh.

Supervision: Duong Quang Huy, Nguyen Huy Hoang, Nguyen Thi Xuan, Can Van Mao, Hoang van Tong.

Methodology: Do Thi Trang, Nguyen Thi Xuan, Hoang van Tong.

Conceptualization: Le Van Khanh, Nguyen Thi Xuan, Hoang van Tong.

Formal analysis: Le Van Khanh, Hoang van Tong.

Visualization: Le Van Khanh.

Software: Nguyen Thi Xuan.

Validation: Can Van Mao, Hoang van Tong.

Writing – review & editing: Hoang van Tong.