Original Research | Open Access
Vol.8 (2022) | Issue-4 | Page No: 116-150
Wei Zhao1#, Xinyu Xiao1#, Yu Gao1,2, Shanshan Liu3, Xiuzhen Zhang1, Changhong Yang1, Qiling Peng1, Ning Jiang2*, Jianwei Wang1*
Affiliations + Expand
1. School of Basic Medical Science, Chongqing Medical University, Chongqing, China
2. Department of Pathology, Chongqing Medical University, Chongqing, China
3. Department of Hepatobiliary Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
# These authors contributed equally to this work
* Corresponding Author
Important Dates + Expand
Date of Submission: 13-Aug-2022
Date of Acceptance: 18-Oct-2022
Date of Publication: 30-Dec-2022
Aim: To study the role and mechanism of nuclear receptor-binding domain 2 (NSD2) in the occurrence and development of hepatocellular carcinoma (HCC).
Materials and methods: HCCDB, MERAV, and GEPIA databases were used to explore the expression of NSD2 in HCC/control samples. UALCAN analyzed the association of NSD2 expression with clinicopathological parameters. The HPA and TCGA databases validated the prognostic value of NSD2. The cBioPortal and g: Profiler were used to analyze the effect of NSD2 alterations on HCC. To further explore its molecular mechanism, GO and KEGG enrichment pathway analyses were carried out in the LinkedOmics database. Immunohistochemistry and Western blot were applied to detect NSD2 expression in HCC/control samples.
Results: NSD2 expression in HCC tissues was distinctly higher than in normal liver tissues and was negatively associated with the overall survival of HCC patients. Cox-regression analysis demonstrated that NSD2 could be regarded as an independent risk factor for patients with HCC. Gene enrichment analysis exhibited that the NSD2-associated signaling pathways in HCC were mainly involved in various cellular processes causing tumorigenesis.
Conclusions: NSD2 plays a key role in the progression of HCC and might be used as a new diagnostic and prognostic biomarker.
Keywords: Hepatocellular carcinoma, nuclear receptor-binding domain 2, biomarker, diagnosis, prognosis
Primary liver cancer is one of the most common cancers and the fourth leading cause of cancer-related deaths in the world, and hepatocellular carcinoma (HCC) consists of 90% of all liver cancers.[1] As early clinical symptoms of HCC are not obvious, most patients have already been at an advanced stage when they are diagnosed. Due to the high invasiveness and high mortality of HCC, most patients could survive for only 2~3 months after definite diagnosis.[2] Although current screening methods using biomarkers in HCC such as alpha-fetoprotein (AFP), des-γ-carboxy prothrombin (DCP), and so on are gradually improving, their early detection rate and specificity are still low.[3],[4] Despite improvements in the treatment strategies of HCC nowadays (resection, chemotherapy, transplantation), its prognosis is still not satisfactory, with a 5-year overall survival rate of less than 20%. While the postoperative recurrence rate is greater than 70%.[5],[6] Therefore, it is imperative to explore some novel biomarkers for early diagnosis and prognosis of HCC.
So far, many studies have shown that epigenetics, which refers to diverse and reversible chemical modifications on DNA or histones, play an important role in the development of tumors and is a well-known target for therapeutic intervention.[7],[8],[9] In recent years, the nuclear receptor-binding domain (NSD) family has become a research hotspot because of its epigenetic stability and other characteristics such as histone methyltransferases and T cell activation.[10] It also plays a crucial role in chromatin regulation, amplification, mutation, and overexpression of tumor-associated genes in cancer, which implies that it is implicated in oncogenesis.[11],[12],[13] Especially, it is worth noting that NSD2, one of the NSD family, has a variety of complex mechanisms and correlates with the progression of many diseases such as multiple myeloma (hematologic malignancy) and Wolf-Hirschhorn syndrome. Thus, NSD2 is also referred to as MMSET (multiple myeloma SET domain) or WHSC1 (Wolf-Hirschhorn syndrome candidate 1). A few recent studies have reported that NSD2 upregulation is associated with cancer progression.[14],[15] On the other hand, some researches have shown that NSD2 is involved in the regulation of apoptosis and is sensitive to chemotherapy in osteosarcoma cells, and promotes RAS-driven transcription in lung cancer cells.[16],[17] However, little is known about its characteristics and functions as a tumor-associated gene of HCC. Therefore, providing vital information on NSD2’s potential as a viable treatment option for HCC patients is necessary.
In this situation, we seek to comprehensively elucidate the roles of NSD2 in HCC by databases and analyze its expression during HCC development and prognosis. In this study, both bioinformatic analysis and experiments have shown an increased expression of NSD2 in cancer tissues. Also, we have found that the NSD2 expression was negatively correlated with overall survival time in a cohort of 339 HCC patients using The Cancer Genome Atlas (TCGA) database. Additionally, gene enrichment analysis has revealed that NSD2-associated signaling pathways in HCC were especially involved in cellular processes causing tumorigenesis. Eventually, this study demonstrated the involvement of NSD2 in HCC and identified it as a novel and promising biomarker for the diagnosis and prognosis of HCC that will serve to increase the survival rate and reduce the mortality rate further in HCC patients.
HCCDB
HCCDB (hepatocellular carcinoma database) (http://lifeome.net/database/hccdb) with 15 datasets and high coverage (approximately 4,000 clinical samples) is a free one-stop online resource, especially for HCC study. It has been used to construct a model about global differential gene expression of HCC through a user-friendly interface, and make an analysis of uniformly expressed differential genes across multiple datasets.[18] This tool can be utilized to analyze gene expression and co-expression networks in different types of liver tissues.
GEPIA dataset
GEPIA (Gene Expression Profiling Interactive Analysis), is used to comprehensively analyze 8,587 normal samples and 9,736 tumor samples from cancer genome maps and genotypic tissues (http://gepia.cancer-pku.cn/index.html). And its RNA sequencing expression data were analyzed by using a standard processing pipeline for expression (GTEx - Genotype-Tissue Expression) projects and correlation analysis of gene expressions were performed on a given TCGA expression dataset.[19]
Human protein atlas
The Human Protein Atlas (HPA) (http://www.proteinatlas.org), which is one of the most useful databases for protein research, uses transcriptome and proteomics techniques to study protein expression in different human tissues and organs.[20] Importantly, HPA provides different protein expressions, particularly histopathology in normal and tumor tissues/organs. Thus, NSD2 expression at the protein level in normal and cancerous tissues was assessed in HPA. Subsequently, the sub-localization of NSD2 was also verified in HPA.
UALCAN
UALCAN (http://ualcan.path.uab.edu), an online analytics tool, is used to explore the expression of mRNA and its relationship with different clinical indicators.[21] Its resources are mainly based on clinical data of TCGA. In this study, relationships between NSD2 mRNA level and clinical parameters were investigated through the UALCAN database.
cBioPortal and g: Profiler
The cBio Cancer Genomics Portal (cBioPortal) (http://cbioportal.org), including more than 5,000 tumor samples from 20 types of cancers, is an online analysis website mainly used to explore multidimensional cancer genomics data sets.[22] Neighboring genes of NSD2 were downloaded from cBioPortal in the present study, and subsequently an online tool g:Profiler (http://biit.cs.ut.ee/gprofiler/) was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis.[23]
Kaplan-Meier plotter
The Kaplan-Meier plotter (http://kmplot.com/analysis/) is used for survival analysis. Herein, we have analyzed the prognostic value of NSD2 expression in samples with HCC by this tool.
Linkedomics
LinkedOmics (http://www.linkedomics.org/login.php) database based on resources of 11,158 TCGA patients, is an open online biometric platform.[24] And, we have investigated differentially expressed genes linked to NSD2 in a cohort of HCC (n = 371) from the TCGA database and evaluated the correlation among genes via a Pearson correlation coefficient. Furthermore, the involvement of genes in the pathway of GO elements and KEGG analysis were evaluated.[25]
Western blot
Total protein was extracted from normal liver cell lines and cancer cell lines by RIPA buffer (cat: P0013, Beyotime, China) supplemented with a 1% (v/v) protease inhibitor cocktail. The total proteins boiled were electrophoresed on 10% SDS-PAGE gels and then separated proteins were transferred to PVDF membranes. After blocking by 5% skim milk the membrane was incubated with primary antibody against NSD2 overnight at 4°C. It was then incubated with HRP-conjugated secondary antibody (1:2,000, EarthOx, USA) for 1 h at room temperature. Protein bands on the blot were detected using an enhanced chemiluminescence kit. β-actin was used as a loading control.
Immunohistochemistry (IHC) staining
HCC tissues and adjacent tissues were collected from the First Affiliated Hospital of Chongqing Medical University after obtaining informed consent. All specimens of HCC patients were fixed with formalin, embedded in paraffin, and sectioned at a thickness of 3 μm. The sections were baked at 60°C for 1 h, dewaxed with xylene, and dehydrated with gradient alcohol. After antigen repair, the slides were treated overnight at 4°C with commercial rabbit polyclonal antibody against NSD2 (cat: A7938, ABclonal, China) at a dilution of 1:150, and all the remaining steps were performed according to the instructions provided with the OriGene (OriGene Technologies) kit. Finally, all slices were stained by 3, 3-diaminobenzidine (DAB) (cat: BL732A, Biosharp, China) and hematoxylin, sealed by neutral gum, and then observed under the light microscope. NSD2 staining intensity was scored as follows: no staining, 0; weak staining, 1; and strong staining, 2. Meanwhile, the percentage of positive tumor cells was scored as follows: 1%~25% as 1; 26%~50% as 2; 51%~75% as 3; and 76%~100% as 4. The final score of each section was calculated by multiplying these two scores, and NSD2 expression was determined as low (score < 4) or high (score ≥ 4).[6]
Statistical analysis
Cox proportional hazards model for univariate and multivariate analysis was used. All the data were analyzed by SPSS Version 22.0 (IBM, USA) and GraphPad Prism 8.0 (CA, USA). P < 0.05 was considered statistically significant.
Differential gene expression profiles and coexpression network of NSD2
Firstly, data from HCCDB was used to detect the mRNA level of NSD2 among different tissue types using a radar chart. The mRNA level of NSD2 expression in normal liver tissues was much lower than that in other normal tissues (liver/other normal: log FC = -1.27), while the mRNA level of NSD2 in liver cancers was much higher (HCC/Adjacent: log FC = 0.34) compared to adjacent normal liver tissues [Figure 1A]. Similarly, 10 out of 11 datasets in the HCCDB database showed that the NSD2 mRNA level in HCC tissues was much higher compared with adjacent normal liver tissues [Figure 1B]. Moreover, the NSD2 co-expression network in normal liver tissues, adjacent tissues, and HCC tissues was analyzed separately, and as expected, their co-expression network patterns were completely different [Figure 1C]. Functional cluster analyses of genes expressed in different tissues showed that co-expressed genes in normal tissues were mainly associated with activities of DNA helicase and histone acetyltransferase, in adjacent tissues mainly with activities of oxidoreductase and dioxygenase, and HCC tissues with the regulation of cell cycle and chromosomes [Supplementary Table 1], which suggested that NSD2 involved different signaling pathways in HCC. Further validation of NSD2 mRNA expression in different databases such as Metabolic gEne RApid Visualizer (MERAV) [Figure 1D] and GEPIA [Figure 1E] resulted in the same conclusion that a significantly higher mRNA level of NSD2 expression was observed in HCC samples.
Association between the mRNA expression of NSD2 and clinicopathological parameters as well as prognosis of HCC
To ascertain which clinicopathological parameters could be related to the level of NSD2, UALCAN was used. It is suggested that the NSD2 mRNA level of HCC patients was distinctly higher than that of healthy people [Figure 2A]. Among clinicopathological parameters, gender [Figure 2B], tumor stage and grade [Figure 2C, 2D], weight, and age [Figure 2E, 2F] of HCC patients were closely related to the mRNA expression of NSD2.
Subsequently, patient prognosis data analyzed by HPA exhibited that higher NSD2 expression had a significantly negative effect on the prognosis of HCC patients (P = 0.00026, median value of NSD2 expression as the cut-off) [Figure 3].
Univariate and multivariate Cox-regression analysis
To further analyze how NSD2 accompanies multiple factors to influence the prognosis of HCC, univariate and multivariate Cox-regression analyses were conducted. Patient data from TCGA (https://www.cancer.gov) were downloaded [Supplementary Table 2], and data from patients with complete clinical information were collected. Median FPKM value was used to divide the expression of NSD2 into two groups, and results of the chi-square test, Fisher’s exact test, and Spearman correlation analysis [Table 1 and 2] showed that age (P = 0.001), weight (P = 0.007), tumor stage (P = 0.004), and T classification (P = 0.041) influenced the expression of NSD2. These statistically significant parameters were further analyzed by univariate and multivariate Cox-regression analysis to determine whether NSD2 is an independent risk factor for the prognosis of HCC patients. As shown in Table 3, univariate Cox-regression analysis showed that compared with HCC patients with low NSD2 expression, HCC patients with high NSD2 expression had a significantly increased risk of death (P < 0.001). Multivariate Cox-regression analysis showed that expression of NSD2 may be a related factor to poor survival. Consequently, all these suggested that a high level of NSD2 could be an independent risk factor for prognosis in HCC.
Genomic alterations of NSD2 in HCC
TCGA sequencing data from cBioPortal was used to analyze the genetic alterations of NSD2 in HCC patients. Results showed that NSD2 was mutated in 31 of 360 (9%) patients [Figure 4A], and among these mutations, 6.39% had high NSD2 mRNA expression (23/360), 1.11% had missense mutations (4/360), 0.83% had amplification (3/360), and 0.28% had deep deletion (1/360). Importantly mutation map [Figure 4B] showed that mutation types of NSD2 were all missense mutations (4/4). In addition, Kaplan-Meier analysis revealed that NSD2 alterations were significantly associated with shorter overall survival (OS) [Figure 4C, P = 0.0108]. Next, to explore possible pathways NSD2 is involved in, neighboring genes linked to NSD2 mutations were downloaded from cBioProtal [Supplementary Table 3] and utilized the g: Profiler tool to enrich NSD2 and its top 50 frequently altered neighboring genes. The results showed that altered neighboring genes were mainly located in the microbody and chromosomal region and mainly involved in the cell cycle and chromosome segregation. Additionally, they were also associated with microtubule and ATP binding [Figure 4D and Supplementary Table 4].
Enrichment analyses of NSD2 and its correlated gene expressions in HCC
The genes negatively and positively correlated with NSD2 were obtained from mRNA sequencing data of HCC patients in LinkedOmics [Figure 5A]. The top 50 significant genes that were positively and negatively correlated with NSD2 have been listed in the heat map [Figure 5B, 5C, and Supplementary Table 5]. Subsequently, the results of GO elements exhibited that co-expressed genes of NSD2 were mainly located in mitochondria, blood microparticles, ribosome, microbody, and chromosomal region, and mainly involved in fatty acid metabolic process, mitochondrial gene expression, acute inflammatory response, cellular amino acid metabolic process, chromosome remodeling, etc. Additionally, these genes were primarily involved in the structural constituents of ribosomes, electron transfer activity, histone binding and lyase activity. Besides, analysis of the KEGG pathway indicated that these genes were critically involved in the cell cycle, oxidative phosphorylation, ribosome, and phosphatidylinositol signaling pathways [Figure 5D-G]. It is interesting to find that NSD2 could regulate most of the genes involved in the pathway of the cell cycle. Cell cycle related genes regulated by NSD2 in HCC have been listed in Supplementary Table 6, while the signal pathway of the cell cycle in KEGG is shown in Figure 6. Therefore, we surmise whether NSD2 participates in the progression of HCC by regulating the cell cycle of tumor cells.
Verification of NSD2 expression at the protein level in HCC tissues and cell lines
IHC images in the HPA database were analyzed to detect the expression of NSD2 in HCC tissues. The results showed that the expression of NSD2 in HCC tissues was higher than that in normal tissues, while it’s cell fluorescent staining indicated that subcellular localization of NSD2 was mainly enriched in the nucleus (eg. U-251 MG, U-2 OS, and A-431) as shown in Supplementary Figure 1. Moreover, the clinical HCC tissues and adjacent tissues were applied to verify the expression level of NSD2 by IHC, and results displayed that NSD2 expression in HCC tissues was significantly higher than that in paired adjacent tissues (P < 0.05, as shown in Figure 7A and Figure 7B, the information of fifteen patients as shown in Supplementary Table 7). In addition, the level of NSD2 in normal hepatic cell line LO2 and HCC cell lines HepG2 and Hep3B was further analyzed by western blot. The results were consistent with the above mentioned results where the level of NSD2 was significantly higher in HepG2 and Hep3B than in LO2 cells [Figure 7C].
HCC is one of the most aggressive and deadly cancer, as there is no reliable early detection method and its prognosis is very poor.[26] Although more and more molecular biomarkers are considered specific targets for diagnosis, treatment, and prognosis of HCC, the current early detection rate and evaluation of prognosis are still unsatisfactory.[4],[27],[28] Therefore, it is crucial to find a new reliable biomarker the for diagnosis and prognosis of HCC. NSD2 has been reported as a significant gene linked to cancer with its overexpression by regulating apoptosis and sensitivity to chemotherapy in individual studies. However, little is known about its characteristics and functions as a tumor-associated gene of HCC. In this study, it is demonstrated that NSD2 expression in HCC tissues was significantly higher than that in normal liver and adjacent tissues, indicating that NSD2 may be involved in HCC tumorigenesis and could be regarded as a novel biomarker for diagnosis and prognosis in HCC patients.
To identify the role of NSD2 in HCC, the level of NSD2 in HCC was analyzed multiple times in different databases, and the relationship between NSD2 expression and clinicopathological parameters as well as the prognosis of HCC patients was analyzed. Co-expression network of NSD2 was established to mine possible mechanisms where NSD2 participates in the progression of HCC. To further substantiate the conclusion, HCC tissues and HCC cell lines were employed.
The conclusion that an expression of NSD2 was higher in HCC tissues than in normal or adjacent tissues could be drawn from different databases. Importantly, the IHC results of our clinical samples also showed a higher level of NSD2 in HCC. Additionally, co-expressed molecules of NSD2 in adjacent tissues are involved in oxidation-reduction process, while the co-expressed molecules of NSD2 in HCC tissues were related to the dysregulation of cell cycle and chromosomes, resulting in excessive cell proliferation of tumor cells. Moreover, survival analysis revealed that NSD2 expression was negatively correlated with the survival of patients. All these results indicated that NSD2 may be involved in HCC tumorigenesis. Interestingly, we found that the higher expression of NSD2 was observed in female patients rather than males, so it is supposed that NSD2 involved in HCC may be associated with the level of sex hormone-related signaling pathway. Some studies have reported that estrogen receptors (ERs) regulated metabolic pathways to promote tumorigenesis and NSD2 facilitated the expression of Erα through BET protein BRD3/4 in breast cancer.[29],[30] Besides, we found that the expression of NSD2 was also associated with the age of patients, which was in accord with Tanaka H.’s report that NSD2 impacted cell aging by regulating the expression of histone H3 lysine 36 trimethylation (H3K36me3) as well as cell cycle-related genes in a retinoblastoma protein (RB)-mediated manner.[31] Apart from that, the influence of body weight on the expression of NSD2 reminded us of its relationship with fat metabolism. Zhuang et al. have shown that depletion of NSD2-mediated H3K36 methylation prevented induction of the master adipogenic transcription factor-peroxisome proliferator-activated receptor-γ (PPARγ).[32] Here, one important thing to note is that all cases were included when we ascertain which clinicopathological parameters could be related to the level of NSD2 using UALCAN database [Figure 2], but the cases with incomplete information were excluded from multivariate Cox-regression analysis [Table 1 and 2]. Since the sample size was small, it may cause statistical variation. Like other tumor-associated genes, NSD2 expression generally increased as HCC advanced [Figure 3, Table 1 and 2]. However, specifically at cancer stage IV the expression of NSD2 was unexpectedly decreased. There might be two reasons for this phenomenon: (1) since the patient is in the end stage and the condition is related to the liver which is a metabolic organ, gene expression level, in general, gets reduced which could be the cause of NSD2 reduction. (2) Compared with other stages, the sample size of stage IV was too small (only 6 cases). Lastly, univariate and multivariate Cox-regression analysis revealed that NSD2 expression had a significant influence on the survival of HCC patients. NSD2 is therefore reasonably confirmed to be one of the variables affecting the prognosis of HCC.
Evidence has shown that genetic alterations and dysregulated amplification play critical roles in the development of tumors.[33],[34],[35] The intrinsic carcinogenesis mechanism of NSD2 in HCC was explored by analyzing genetic alterations of NSD2. Our results identified many NSD2 genetic mutations in HCC tissues, which were significantly related to patient survival, and, interestingly, mutation types of NSD2 were all missense mutations. Swaroop et al. found a glutamic acid to lysine mutation at residue 1099 (E1099K) in NSD2 in childhood acute lymphocytic leukemia (ALL), which reduced cell apoptosis and enhanced proliferation, clonogenicity, adhesion, and migration.[36] Next, functional enrichment analysis in this study suggested that coexpressed genes with NSD2 were generally involved in cell cycle-related and metabolic processes, which was consistent with previous studies.[37],[38],[39] The identification of these pathways provide new strategies for the treatment and intervention of HCC patients with NSD2 dysfunction, which will also become the direction of our further research.
In summary, this study provides multi-level demonstrations for identifying the key role of NSD2 in carcinogenesis and its potential as a diagnostic and prognostic biomarker for HCC. Nevertheless, as exact mechanism of NSD2 involvement in HCC is still unclear, our future work will focus on this scientific question to confirm whether NSD2 could be utilized as a clinically useful biomarker.
FINANCIAL SUPPORT AND SPONSORSHIP
The authors have no financial support and sponsorship.
CONFLICTS OF INTEREST
The authors declare no competing financial interest.
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
HCC tissues and adjacent tissues were collected from the First Affiliated Hospital of Chongqing Medical University after obtaining ethics approval.
AUTHOR CONTRIBUTIONS
Wei Zhao, Ning Jiang and Jianwei Wang conceived and designed this study. Wei Zhao, Shanshan Liu and Changhong Yang collected and analyzed the relative data. Xiuzhen Zhang collected the clinical samples. Xinyu Xiao and Yu Gao performed the IHC experiments and Western blot. Wei Zhao drafted the article. Jianwei Wang and Qiling Peng revised the manuscript critically for important intellectual content. All the authors read and approved the final manuscript.
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Ge Ren1,2,3, Yawei Zhang1,2, Lei Ren1,2
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