Comprehensive analysis of the expression and prognostic value for SNRP members in hepatocellular carcinoma

Abstract

Background

Heterogeneity and epigenetic modifications lead to differences among treatment strategies, management and prognosis in hepatocellular carcinomas. The family of small nuclear ribonucleoprotein polypeptides (SNRPs) plays a crucial role in tumorigenesis and progression. However, the expression profile and prognostic impact of these family members are not clear. Here, we discuss the expression levels and prognosis of SNRPs. family members

Methods

We compared the transcript levels of each SNRPs member in pan-cancerous tissues by ONCOMINE and further analyzed the expression levels and tumor staging of these markers in hepatocellular carcinoma using UALCAN and GEPIA online databases, while assessing the prognostic value of their mRNA expression and performing functional enrichment analysis by Metascape software using Kaplan–Meier plotter database.

Results

These results showed that mRNA levels of each member of SNRP (B, D1, D2, D3, E, F, G) were significantly upregulated in hepatocellular carcinoma compared to normal tissue and were more highly expressed in patients with advanced hepatocellular carcinoma. mRNA expression of SNRPB, SNRPD1 and SNRPG was associated with poorer overall survival (OS), recurrence-free survival (RFS) and progression-free survival (PFS), which was considered to be statistically significant.

Conclusion

We systematically analyzed the mRNA expression and prognostic significance of each member of SNRPs in HCC and demonstrated the correlation, interaction network, gene alteration and functional enrichment among SNRPs members. Our data suggest that SNRPs members as oncogenes may be a potential indicator of HCC.

Background

Hepatocellular carcinoma (HCC) is the most common of primary liver cancer, remains a high mortality cancer globally ^[1]. HCC, which has the highest incidence in China compared to other countries, is now the third leading cause of cancer-related deaths and the fourth most common cancer in China in 2018 ^{[2, 3]}. Unlike other malignancies, obvious heterogeneity greatly affects the treatment and prognosis of HCC. More potential indicators need to be identified in the overall management of tumors in clinical practice.

The splicing process is accurately ensured by spliceosomes for stability and normalization ^[4]. Smith (Sm) proteins play a decisive role in maintaining the integrity of small nuclear ribonucleic acid (snRNA) to avoid nucleases and the downstream RNA processing steps ^[5]. The formation of heterodimeric (SmD1-SmD2 and SmB-SmD3) or heterotrimeric (SmE-SmF-SmG) subcomplexes is one of the important mechanisms of Sm proteins ^[6]. The small nuclear ribonucleoprotein polypeptide (SNRP) B, D1, D2, D3, E, F, G genes are core components of the spliceosomal small nuclear ribonucleoproteins (snRNPs), forming a 7-membered ring/Sm-core-complex that is precursors to major and minor spliceosome ^[6] to ensure RNA stability ^[5]. These complementary roles of SNRP members tumorigenesis and metastasis roles ^[7] have attracted value attention.

The increasing evidence showed the indispensable role of the splicing components in the initiation, angiogenesis, apoptosis, and invasion in cancers ^[7–10]. Relevant researches ^[11–15] have reported the differences and prognostic value of single SNRP members in different cancer types. The function of SNRPB as an oncogene served as a potential prognostic factor for HCC ^[11]. Another study ^[12] displayed the mRNA expression of SNRPB may be an effective therapeutic target for cervical cancer by interfering with alterations in the p53 pathway. In addition, high levels of SNRPD1 are considered as predictive biomarkers of tumorigenesis and poor prognosis in lung adenocarcinoma and ovarian cancers ^{[13, 14]}. Even, siRNA deprivation of SNRPE or SNRPD1 drives cell death through autophagy, resulting in a marked reduction in cell viability in breast, lung, and melanoma cancer cell lines ^[15]. In summary, current studies ^[11–15] described the expression of individual members of the SNRPs family in a variety of tumors; however, few studies have focused on the expression and prognostic value of the Sm core complex family (B, D1, D2, D3, E, F and G) in HCC patients.

In our study, we performed a comprehensive analysis of the expression and prognosis of core family members of seven SNRPs in HCC patients. In addition, we analyzed the interaction network, genetic alterations, and functional enrichment based on multiple datasets.

Methods

The study has been permitted by the Institutional Review Board of Peking University International Hospital. All methods were carried out in accordance with relevant guidelines and regulations. And there is not direct human participation in these databases.

Results

Differential expression of SNRP members in patients with HCC

Firstly, it was determined that genes for SNRP members are located on definite genomic sites ^[25,26] (Table 1). We analyzed the transcript levels of the entire cohort of 1858 assays in various cancer types using the ONCOMINE database ^[16] (Fig. 1). The results showed that significant unique analyses were found in the SNRPB (26 tests), SNRPD1 (32 tests), SNRPD2 (22 tests), SNRPD3 (12 tests), SNRPE (39 tests), SNRPF (15 tests) and SNRPG (23 tests) groups, respectively. SNRPB was significantly elevated in tumor tissues, especially in bladder, cervical, colorectal, gastric, head and neck, kidney, liver and breast cancers, with 2,136 samples. In addition, the levels of each SNRP member were high in patients with gastric and colorectal cancers. Compared with other cancers, liver cancer had the large sample size and strong mRNA expression of SNRPB, SNRPD1, SNRPD2, and SNRPE. In contrast, high levels of SNRPD3 are rarely found in tumor tissue. 

The results of ONCOMINE ^[16] described that the transcript levels of SNRPB, SNRPD1, and SNRPD2 were significantly elevated in HCC tissues ^[25,27]. But SNRPD3, SNRPF, and SNRPG had no data set to study. For SNRPE mRNA levels, it was upregulated in all three datasets of the TCGA database ^[24-27]. It was summarized in Figure 1 and Table 2. We also compared the transcript levels of SNRPs between HCC and normal tissues by using UALCAN ^[17] (Fig. 2a-2g). We found that SNRPB, D1, D2, D3, E, F, and G were all upregulated in tumor tissues. Besides, we analyzed the correlation among different genes in HCC tissues and determined that SNRPB and SNRPD1 had the highest correlation (Fig. 2h). In conclusion, our results showed that transcriptional expression of SNRPB, SNRPD1, SNRPD2, SNRPD3, SNRPE, SNRPF, and SNRPG was overexpressed in HCC patients. Table 3 shows multiple comparisons of significant unique analyses or median expression in HCC patients using ONCOMINE and UALCAN servers. SNRPB, SNRPD2, SNRPD3 and SNRPF; SNRPD1 and SNRPD2; SNRPD1, SNRPE and SNRPG were analyzed by best gene ranking percentile, with no differences. In addition, there was no significance between SNRPB and SNRPE; SNRPD1, SNRPD2, SNRPD3, SNRPF, and SNRPG by median expression.

Correlation between mRNA expression and tumor stages of SNRP members

We used GEPIA ^[18] to analyze the correlation between mRNA expression and cancer stage in patients treated with HCC. Although there were significant differences between SNRPB, D1, D2, D3, F and G groups at stages I, II, III and IV, there were no differences between SNRPE groups and tumor stage (Fig. 3). That is, the mRNA expression of SNRPB, D1, D2, D3, F and G had a significant relationship with the cancer stage of the patients and appeared higher in advanced stage cancers.

Prognostic value of SNRP members in patients undergoing HCC

Prognostic significance of mRNA expression, including OS, PFS, and RFS was under observation. It could be found that patients were classified as low (black) and high (red) risk based on their respective OS thresholds (Fig. 4). High levels of SNRPB, SNRPD1, SNRPE and SNRPG mRNA levels suggest a trend towards worse OS, but without significant differences. The cutoff values distinguishing between the high and low groups based on automatic selection of the best cutoff ^[20], can be seen in Fig. S1.

Increases in SNRPB, SNRPD1, SNRPD2, and SNRPG were associated with poor PFS (Fig. S2). The relevant cutoff values can be seen in Fig. S4. Furthermore, high mRNA levels of SNRPB SNRPD1, SNRPD2, SNRPE, and SNRPG led to shorter RFS (Fig. S5), while no similar findings were found for SNRPD3, and SNRPDF.  The cutoff value for each member can be showed in Fig. S7. 

There are several known prognostic factors for HCC, such as age, gender, WHO grade, p_T stage, and p_TNM stage. It was necessary to examine whether each member could independently predict prognosis. Univariate Cox analysis presented seven genes were positively associated with survival prognosis (Fig. 5, S3, S6). Moreover, p_T and p_TNM stages were also significantly related to OS (Fig. 5a), PFS (Fig. S3a), and RFS (Fig. S6a). Subsequent multivariate Cox regression analysis indicated that SNRPD1 was significantly correlated with OS (Fig. 5b), but failed to be an independent prognostic factor for PFS (Fig. S3b) or RFS (Fig. S6b). In conclusion, high levels of SNRPB, SNRPD1 and SNRPG were associated with prognosis of OS, PFS and RFS. Details are shown in Table 4.

Genetic alterations and correlations of SNRP members

 We analyzed genatic mutations and interactions in HCC patients by cBioPortal ^[21] (INSERM Cancer Cell 2014 dataset, MSK Clin Cancer Res 2018 dataset, INSERM Nat Genet 2015 dataset, MSK PLOS One 2018, AMC Hepatology 2014 dataset, RIKEN Nat Genet 2012 dataset, TCGA Firehose Legacy dataset, TCGA PanCancer Atlas dataset). The results (TCGA PanCancer Atlas dataset) illustrated that the percentages of gene alterations were 0.27% mutations (1/372), 0.53% deep deletions (2/372), 7.53% amplifications (28/372) in all SNRP members, respectively (Fig. 6a). The frequency of alterations in SNRPs b was analyzed by using the AMC Hepatology 2014 dataset, TCGA Firehose Legacy dataset, and TCGA PanCancer Atlas dataset (SNRPB, 0.5%; SNRPD1, 0.3%; SNRPD2, 0.8%; SNRPD3, 0.3%; SNRPE, 5%; SNRPF, 0.2%; SNRPG, 0.2%) (Fig. 6b). Then, we further presented the survival results based on genetic alterations. Unfortunately, we did not find significance among genetic alterations, OS or PFS, respectively (p = 0.792, 0.662, Fig. 6c, 6e). However, disease-free survival (DFS) was significant in the genetically altered and unaltered groups (Fig. 6d). The reasons why genetic alterations in SNRPs and prognosis did not seem to be associated with prognosis might be related to the context of the study in the database, the material methodology and the small sample size. Table 5 summarizes the OS or DFS data for the genetically altered and unaltered groups, including the total number and number of events. Only the DFS data for SNRPE had a P value <0.05.

Functional enrichment analysis of SNRP members 

To understand the function of SNRP members and their neighboring proteins, we used GO and KEGG pathways by Metascape ^[24]. The result indicated two major GO-biological processes (Fig. 7a), spliceosomal snRNP assembly (GO:0000387) and spliceosomal complex assembly (GO:0000245). U1 snRNP binding (GO:1990446) was only associated with the molecular function (Fig. 7b). The top 4 GO enrichments (Fig. 7c) were cellular components: methylosome, plCIn-Sm protein complex, U5 snRNP, and U7 snRNP. The top 2 KEGG enrichments (Fig. 7d) were structural complexes: Sm core complex; pathway: systemic lupus erythematosus. 

Interaction of correlated genes and proteins of SNRP members 

We briefly illustrated the correlation of SNRP members at the genatic level by Gene MANIA online tool ^[22] (Fig. S8a). The results demonstrated SNRP members share genetic thresholds very closely. Markedly, relationships were found among SNRP members regarding the PPI network. We used STRING ^[23] to determine the correlation of SNRP members at the protein expression level (Figure S8b).

Discussion

A growing number of studies have illustrated that SNRP members are upregulated in various types of cancer and play a vital role in cancer initiation and progression ^[7]. Recent studies ^{[13, 14]} have shown that SNRPD1 is a predictive biomarker for tumorigenesis and poor prognosis in lung and ovarian cancers. In addition, siRNA depletion of SNRPE, D1 led to a reduction of cell viability in breast, lung, and melanoma cancer cell lines ^[15]. However, since SNRPs are the major spliceosomal precursors of the Sm core complex ^[6], we need to study the complex as an integrator to explore the different roles in HCC tissues. We hypothesized that SNRP members might act as onco-promoters to affect the prognosis for HCC patients. Therefore, we performed a systematic analysis of the transcript levels and prognostic value of SNRP members in HCC.

We discussed that the mRNA levels of SNRPB, SNRPD1, SNRPD2, and SNRPE were upregulated in HCC tissues compared to normal tissues and illustrated high levels of SNRPD3, F and G did not present a significant disadvantage by ONCOMINE ^[16]. However, the high levels of expression of SNRPB, D1, D2, D3, E, F, G were found to be present in malignant tumors compared to normal tissues using UALCAN ^[17]. These two inconsistent results may be due to the diversity of the background and materials of such abundant researches.

The protein encoded by SNRPB is one of nuclear proteins found in U1, U2, U4, U6, and U5 snRNPs which affected pre-mRNA splicing and it may play an important role in snRNP combination ^[25]. Peng NF and his colleagues ^[11] showed that SNRPB expression was increased in HCC tissues. In our study, we found that SNRPB expression was significantly elevated in patients with advanced cancer, which is similar to the findings of Peng et al. The gene of SNRPD1 encodes for snRNP ^[25]. Studies ^{[13, 14]} reported the use of free-scale gene co-expression networks to assess the relationship between multiple gene datasets and clinical characteristics of patients, followed by confirmation of predictors by weighted gene co-expression network analysis (WGCNA). The mentioned studies indicated that the mRNA expression of SNRPD1 and its encoded protein were highly specific and sensitive for identifying tumor lesions as one of the predictive biomarkers of tumorigenesis and poor prognosis. In our report, we found mRNA expression of SNRPD1 was upregulated in HCC tissues and led to shorter OS, RFS and PFS, and these results were similar to previous studies. Furthermore, SNRPD1 was reported systematically for the first time in HCC patients. The protein encoded by SNRPD2 and SNRPD3 also belonged to the snRNP core protein ^[27]. It was shown to be involved in pre-mRNA splicing and snRNP biogenesis. There were few studies on SNRPD2 and SNRPD3 because SNRPD1-SNRPD2 or SNRPB-SNRPD3 preferentially form heterodimeric subcomplexes before forming Smcomplex ^[6]. We revealed that mRNA expression of SNRPD2 and D3 was up-regulated in HCC and correlated with cancer staging. However, there was no correlation between abnormal levels of SNRPD2 and SNRPD3. This suggested that SNRPD2 and D3 were at the high levels in tumor tissues, but may not be suitable as potential prognostic indicators. As with the heterodimeric subcomplexes of SNRPD2 and SNRPD3, SNRPE, SNRPF and SNRPG could form heterotrimeric subcomplexes that cooperate with other SNRP members to form 7- member ring structure/complex and participate in the splicing process ^[6]. The current study ^[15] assumed that SNRPE knockdown obviously led to reduced expression in mTOR pathway and protein levels, which partly explained the SNRPE-based autophagy phenomenon. According to Blijlevens and co-workers ^[28], high levels of SNRPG protein in v various types of cancer interact positively with cancer initiation, progression and metastasis. The expression of SNRPG in different cancers can be explained by high levels of protein, the mis-localization of unassembled or misassembled proteins ^[29]. Thus, SNRPG might contribute to the initiation and progression of different cancers ^[30–34]. We found that SNRPE was highly expressed in tumor tissues by using ONCOMINE ^[16], but the results of SNRPF and SNRPG groups were not similar in this study. In addition, the mRNA of SNRPE did not correlate with cancer stage and PFS. The different results compared to previous studies might be the small sample sizes or different cancer types.

In the study, we found that Gene MANIA ^[22] and STRING ^[23] analysis revealed close co-expression between SNRP members at the gene level, while co-expression at the protein level was compactly correlated.

To investigate the correlation of gene alterations, we revealed the frequency of gene alterations in SNRPs by using cBioPortal ^[21]. We studied the functional enrichment of the SNRPs by Metascape ^[24]. Our results indicated that SNRPs members are involved in functions that may include methylosome, U1, U5, U7 snRNP binding, Sm core complex, etc., which have been studied as involved in cell cycle, signal transduction, angiogenesis, apoptosis and invasion ^{[8–10,35−40]}. The spliceosome complex is formed by snRNP ^{[41, 42]}. Each snRNP (U1, U2, U4, U6, and U5) includes an snRNA integrated with a set of Sm core complex. The Sm core complexes (B, D1, D2, D3, E, F and G) form a 7-ring core structure/complex to encapsulate RNA. All SNRP proteins have conserved Sm structural domains to help form the Sm core of the snRNPs ^{[5, 43]}, thereby determining pre-mRNA processing ^[44]. However, further work is needed to understand the role and function of SNRP members.

There were some limitations in our research. First, all data were analyzed in our study from various online database tools, which c may be derived from various research contexts, bases and samples, and therefore further studies in larger samples are needed to demonstrate these. Then, no biological experiments, clinical specimens and cases were performed to validate the results. Next, in vitro and in vivo studies will be performed and may provide some further conclusions.

Conclusion

In this study, we systematically analyzed the mRNA expression and prognostic significance of SNRP members in HCC. In addition, we presented the correlations of co-expression and interaction networks, genetic alterations and function enrichment of SNRP members. Expression of SNRPB, SNRPD1, SNRPD2, SNRPD3, SNRPE, SNRPF, and SNRPG was upregulated in tumor tissues compared to normal tissues, and high levels of SNRPB, SNRPD1 and SNRPG resulted in poorer OS, RFS and PFS. In conclusion, SNRPB, SNRPD1, and SNRPG could act as the gene promoters and novel prognostic biomarkers for HCC.

Declarations

Ethics approval and consent to participate: All ethical approval, guidelines, and informed consent are available in each article, which is published and searchable in a public database. All methods were carried out in accordance with relevant guidelines and regulations. And there is not direct human participation in these databases.

Consent for publication: Not Applicable.

Availability of data and materials: Oncomine (http://oncomine.org.cutestat.com/); UALCAN (http://ualcan.path.uab.edu/); Gene Expression Profiling Interactive Analysis (GEPIA) (http://gepia.cancer-pku.cn/); The Kaplan-Meier (KM) Plotter (http://kmplot.com/analysis/); cBioPortal for Cancer Genomics (http://www.cbioportal.org/); GeneMANIA (http://genemania.org); STRING (https://cn.string-db.org/); Metascape (http://metascape.org);

Competing interests: All authors have completed the ICMJE uniform disclosure form. The authors have no conflicts of interest to declare.

Funding: Not applicable.

Authors' contribution:

(I) Conception and design: Ziwei Guo
(II) Administrative support: Jun Liang
(III) Provision of study materials or patients: Ziwei Guo, Chuanhao Tang
(IV) Collection and assembly of data: Ziwei Guo, Chuanhao Tang
(V) Data analysis and interpretation: Ziwei Guo, Chuanhao Tang
(VI) Manuscript writing: All authors
(VII) Final approval of manuscript: All authors

Acknowledgements: A preprint has previously been published ^[45].

Supplementary description: In supplementary materials, we split patients by auto select best cutoff for OS, PFS, and RFS in Fig. S1, S4, S7, and the prognostic value of PFS and RFS were showed in Fig S2, S5, the subgroup analyses shown in Fig S3, S6. Interaction network of SNRPs at the gene and protein levels in HCC patients in Fig. S8.

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Tables