Introduction

Head and neck squamous cell carcinoma (HNSCC), the sixth most common malignancy worldwide, arises from the oral cavity, pharynx, and larynx mucosal epithelium [1]. Conventional treatments for HNSCC include surgery, radiotherapy, and chemotherapy, but they are incompletely effective, with only 50% of patients being cured [2]. Therefore, the exploration of molecular targeted therapy for HNSCC is becoming a current treatment trend [3]. New prognostic biomarkers are urgently needed to accurately forecast the progression of precancerous lesions in HNSCC, thereby predicting overall survival and optimizing treatment regimens.

In addition, cullin ring ubiquitin ligases (CRLs), which consist of 4 distinct parts: CULs, ring-finger proteins (RINGs), adaptor proteins, and substrate recognition receptors/proteins, which can catalyse the movement of ubiquitin to the substrate, play a fundamental role in regulating cell cycle, gene expression, apoptosis, etc. [4] Several recent studies have reported the potential involvement of CRLs in the progression of several types of cancer [5–7]. The CUL gene family has been reported to be evolutionarily conserved, and at present it consists of 8 distinct members in the human genome: CUL1, CUL2, CUL3, CUL4A, CUL4B, CUL5, CUL7, and CUL9 [8].

Several previous studies have suggested that the differential transcriptional levels of CULs may also play a vital role in mediating the signal transduction pathways related to cancer. For instance, CUL2 E3 ligase complexes may participate in the von Hippel-Lindau (VHL) signalling transduction mechanism in clear cell renal cell carcinoma [9]; thus, CUL3 can serve as major regulator of human malignancies and emphasize the importance of developing novel agents targeting this protein to prevent or treat the tumourigenesis. However, the potential functions of distinct CULs are still unknown in HNSCC. Thus, an in-depth study about the possible involvement of different CULs in HNSCC is needed to reveal the molecular pathways related to the occurrence and development of HNSCC and might reveal novel prognostic as well as clinical treatment biomarkers for this high morbidity tumour. The purpose of this study is to investigate and identify the predictive role of different CULs in HNSCC occurrence and progression.

Material and methods

Expression level analysis of different CULs

In the present research, we explored the transcriptional levels of CULs in multiple cancers and their potential relationship with individual stages, tumour grade, and prognosis in HNSCC by using the University of ALabama at Birmingham CANcer (UALCAN) (http://ualcan.path.uab.edu/analysis.html) [10] and The Cancer Genome Atlas (TCGA) databases (http://cancergenome.nih.gov) [11]. A Kaplan-Meier plotter (http://kmplot.com/analysis/) was used to explore the prognosis of transcriptional levels of different CULs in HNSCC, and thereafter the information about the potential interactions among gene expression and the overall survival (OS) of cancer patients was processed easily.

Functional enrichment analysis of different CULs

The possible relationship between CULs and their neighbouring genes was built by STRING (https://string-db.org/) [12] and visualized by Cytoscape [13]. Furthermore, the “stat” R package was used to identify the top 20 similar genes that have been linked with CUL expression in HNSCC from the TCGA database. We used Metascape (http://metascape.org) to perform the function enrichment analysis of CULs and their similar genes by using Gene Oncology (GO) and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) [14].

Immune infiltration analysis of different CULs

In the present study, we used TIMER (https://cistrome.shinyapps.io/timer/) [15] and TISIDB (http://cis.hku.hk/TISIDB/index.php) [16] to study the possible interactions among CUL expression levels and immune cell infiltration, immune-related molecular markers, and multiple types of immunomodulators. Finally, we used a heatmap to demonstrate the coaction display details in scatterplots and provide the partial Spearman correlation and p-values, as shown in Supplementary File — Tables S1 and S2.

Patient tissue samples

Head and neck squamous cell carcinoma tissue samples (n = 10) and matched para-carcinoma tissue (n = 10) were obtained from the Department of Otolaryngology-Head and Neck Surgery of the Affiliated Hospital of Qingdao University. The Hospital Accreditation Committee of the Affiliated Hospital of Qingdao University (approval #QYFY WZLL 27078) and patients approved this study, and the confidentiality of patient information was maintained.

Cell culture

Hypopharyngeal cancer cells (FaDu), human oral epidermoid carcinoma cells (KB), and human normal epithelial cells (HNEpC) cells were cultured in Dulbecco’s Modified Eagle Medium (Meilunbio, China), while nasopharyngeal carcinoma (CNE-2) cells were cultured in RPMI1640 Medium (Meilunbio, China), containing 10% foetal bovine serum (FBS) (Procell, China), 100 µg/mL streptomycin, and 100 U/mL penicillin (Procell, China), maintained at 37°C in an atmosphere of 5% CO2, and grown to 70–90% confluence.

Plasmid construction and transient transfection

CUL2 and CUL4A were subcloned into PB-3FLAG-IRES2- EGFP-CMV-IRES2-puro-M13 vector, while CUL9 shRNA was inserted into in the pLKO.1 vector. Both vector and control plasmids were purchased from GeneChem Company. Transient transfection was performed with Lipofectamine 3000 following the instructions of the manufacturer.

Quantitative real-time polymerase chain reaction (RT-qPCR)

RNA from HNSCC tissue samples and cells was extracted using TRIzol reagent following the manufacturer’s instructions. After the RNA concentration was quantified using NanoDrop One (Thermo Fisher Scientific, United States), we reversed RNA into cDNA by using Evo M-MLV RT Premix for quantitative polymerase chain reaction (qPCR) (Accurate Biotechnology [Hunan] Co., Ltd).

Real-time qPCR (RT-qPCR) was performed to quantify mRNA expression of CUL2, CUL4A, and CUL9 via SYBRR Green Premix Pro Taq HS qPCR Kit [Accurate Biotechnology (Hunan) Co., Ltd]. For normalization of expression levels, 18sRNA and GAPDH were, respectively, used per tissue and cell sample. CUL2, CUL4A, CUL9, 18sRNA, and GAPDH primer sequences are described in Table 3. After normalization, the ΔΔCt method was used to compare the relative expression for different CULs.

Cell viability

Above cells, seeded at density of 5 × 103 per well in a 96-well plate, were transfected with control or OE-CUL2, OE-CUL4A, and CUL9 shRNA. After 48 h, we followed the instructions of the Cell Counting Kit-8 (Yeason) so that the attached cells were incubated with 100 μL of medium containing 10 μL of cell counting kit 8 (CCK-8) solution for between 30 minutes and 2 hours. The absorbance was measured at 450 nm. Cell confluence was calculated to reflect cell proliferation.

Wound healing assay

The cells were seeded in 6-well plates and transfected until they were fused to 60–70%. After 48 h, we used 200-µL pipet tips to create similar scratches. The plate was washed well once with phosphate-buffered saline (PB). Then, 2 mL of fresh media supplement was added without Fetal Bovine Serum (FBS). The images of the scratches were recorded in the same position at different time points. The scratch areas were quantitatively analysed by ImageJ software.

Statistical analysis

SPSS version 23 (IBM, Ehningen, Germany) or GraphPad Prism 8.0 (GraphPad Software, La Jolla, CA, United States) were used to analyse the data. We analysed the CULs mRNA expression between paired clinical tumours and normal tissues by using Student’s t-test because these experimental data were accorded with the normal distribution and homogeneous variance. It was also applied to explore the differences in CUL expression levels, proliferation, and migration in multiple HNSCC cell lines. Meanwhile, the Wilcoxon rank sum test was used to analyse the data that did not conform to the normal distribution. In all graphs, the mean value ± 1 standard deviation (SD) was performed. p < 0.05 was considered as statistical significance.

Results

Up-regulation of different CULs in patients with HNSCC

To investigate the transcriptional levels of different CULs in HNSCC, we used the TCGA database to analyse the mRNA levels of CULs in different types of tumour. The results displayed in Figure 2 indicate that the mRNA levels of CUL1/2/4A/4B/7 were significantly higher in HNSCC patients than in normal patients, while the mRNA level of CUL3 was markedly lower in HNSCC samples than in normal samples. The expression of CUL5 and CUL9 was statistically insignificant. Next, we also analysed the transcriptional level of CULs between HNSCC samples and normal samples in the TCGA database; the results of CULs mRNA expression in HNSCC tissues are consistent with Figure 1 (Fig. 3).

Figure 1. A model for regulating cancer cell growth by cullin ring ubiquitin (Ub) ligases (CRLs). E2 — ubiquitin-conjugating enzyme 2

Figure 2. Transcriptional expression of cullins (CULs) in different types of cancer diseases [The Cancer Genome Atlas (TCGA) database]. Difference of transcriptional expression was compared by the Wilcoxon rank sum test. Data type: mRNA. *p < 0.05, **p < 0.01, ***p < 0.001. ACC — adrenocortical carcinoma; BLCA — bladder urothelial carcinoma; BRCA — breast invasive carcinoma; CESC — cervical endocervical adenocarcinoma and squamous cell carcinoma; CHOL — cholangiocarcinoma; COAD — colon adenocarcinoma; ESCA — oesophageal carcinoma; GBM — glioblastoma; HNSC — head and neck squamous cell carcinoma; KICH — kidney chromophobe; KIRC — kidney renal clear cell carcinoma; KIRP — kidney renal papillary cell carcinoma; LAML — acute myeloid leukaemia; LGG — brain lower-grade glioma; LIHC — liver hepatocellular carcinoma; LUAD — lung adenocarcinoma; LUSC — lung squamous cell carcinoma; MESO — mesothelioma; OV — ovarian serous cystadenocarcinoma; PRAD — prostate adenocarcinoma; READ — rectum adenocarcinoma; SKCM — skin cutaneous melanoma; STAD — stomach adenocarcinoma; TGCT — testicular germ cell tumours; THCA — thyroid carcinoma; THYM — thymoma; UCEC — uterine corpus endometrial carcinoma; UVM — uveal melanoma

Figure 3AB. messenger ribonucleid acid (mRNA) expression of distinct cullin (CULs) family members in normal tissues and head and neck squamous cell carcinoma (HNSCC) tissues [The Cancer Genome Atlas (TCGA)]. mRNA expressions of 8 CUL family members were found to be over-expressed or low-expressed in primary unpaired or paired HNSCC tissues compared to normal samples. The transcriptional expression of CULs in unpaired HNSCC patients was compared by the Wilcoxon rank sum test, while using paired t test in paired HNSCC patients. *p < 0.05, **p < 0.01, ***p < 0.001, ns: no significance

Relationship between mRNA expression of CULs and the clinicopathological features in HNSCC patients

After the expression levels of CULs were found to be upregulated in HNSCC, we used UALCAN to explore the potential relationship between the mRNA levels of CULs and various clinicopathological features of HNSCC, including patients’ individual cancer stages and tumour grades. As shown in Figure 4, the transcriptional levels of 3 CULs were found to be significantly related to cancer stage in individual patients, and those in more severe tumour stages expressed significantly higher mRNA levels of CULs. The highest transcriptional level of CUL2/4A/4B was observed in stage 4 (Fig. 4B, D, and E), the highest transcriptional expression of CUL3 as well as CUL9 was found in the normal stage (Fig. 4C and H), and the highest mRNA expressions of CUL1 and CUL7 were noted in stage 2 (Fig. 4A and G). The higher transcriptional expression of CUL2/4A/4B in stage 4 is possibly related to poor prognosis. Similarly, as shown in Figure 5, the transcriptional levels of 7 CULs were primarily related to the tumour grade, and with increasing tumour grade the transcriptional level of CULs was observed to augment proportionately. The highest transcriptional level of CUL1/2/4A/4B/9 was found in grade 4 (Fig. 5A, B, D, E, H), but the highest mRNA level of CUL7 was noticed in tumour grade 2 (Fig. 5G). Nevertheless, the highest transcriptional level of CUL3 was observed in normal tissues, and with the increase in the tumour grade the mRNA level of CUL3 was detected to be downregulated (Fig. 5C). In brief, the above results indicated that the transcriptional level of 7 CULs was noteworthy and correlated with clinicopathological features in HNSCC.

Figure 4. Relationship between messenger ribonucleid acid (mRNA) expression of distinct cullin (CULs) family members and individual cancer stages of neck squamous cell carcinoma (HNSCC) patients. The highest mRNA expressions of CUL1/4A were found in stage 3 (A, D), while the highest mRNA expressions of CUL2/4B/7 were found in stage 4 (B, E, G). *p < 0.05, **p < 0.01, ***p < 0.001

Figure 5. Association of messenger ribonucleid acid (mRNA) expression of distinct cullin (CUL) family members with tumour grade of head and neck squamous cell carcinoma (HNSCC) patients. The mRNA expressions of 5 CUL family members were significantly related to tumour grade, and as tumour grade increased, the mRNA expressions of CULs tended to be higher. The highest mRNA expressions of CUL1/4A/7/9 were found in tumour grade 4 (A, D, G, H), while the highest mRNA expression of CUL2/4B was found in grade 3 (B, E). However, the highest mRNA expression of CUL3 was found in grade 1 (C). *p < 0.05; **p < 0.01; ***p < 0.001. TCGA — The Cancer Genome Atlas

Prognosis of transcriptional level of CULs in HNSCC

Next, we applied a Kaplan-Meier plotter (http://kmplot.com/analysis/) to assess the impact of variation in the transcriptional level of CULs on the prognosis in HNSCC (Fig. 6). The results showed that upregulation of CUL2 [hazard ratio (HR) = 1.41, p = 0.037] and CUL4A (HR = 1.43, p = 0.025) mRNA were significantly linked to shorter overall survival (OS) in HNSCC, while overexpression of CUL7 (HR = 0.77, p = 0.049) and CUL9 (HR = 0.51, p < 0.001) resulted in favourable prognosis in HNSCC patients.

Figure 6. Prognostic value of messenger ribonucleid acid (mRNA) expression of distinct cullin (CUL) family members in head and neck squamous cell carcinoma (HNSCC) patients (Kaplan-Meier Plotter). Higher mRNA expressions of CUL7/9 were significantly associated with favourable overall survival (OS) of HNSCC patients (B, G, H), while higher mRNA expression of CUL2/4A was significantly related to shorter OS of HNSCC patients (D). However, CUL1/3/4B/5 mRNA expression showed no correlation with prognosis in HNSCC patients (A, C, E, F). HR — hazard ratio

Co-expression, similar gene network, and interaction analyses of CULs in HNSCC

After studying the interaction between the transcriptional level of CULs and clinicopathological features as well as with the prognosis in HNSCC, we further investigated the latent co-expression of different CULs in HNSCC. We noticed that there were mild to moderate positive interactions between CUL1 and CUL3, CUL1 and CUL4A, CUL3 and CUL9 (Fig. 7A, p < 0.05). We found medium to strong positive correlations between CUL1 and CUL2, CUL1 and CUL5, CUL2 and CUL3, CUL2 and CUL4A, CUL2 and CUL5, CUL3 and CUL4B,CUL3 and CUL5,CUL4A and CUL5,CUL4B and CUL5,CUL4B and CUL7, CUL5 and CUL7, CUL7 and CUL9 (Fig. 7A, p < 0.01). Interestingly, we also noticed the negative correlations between CUL5 and CUL9, CUL4A, and CUL9 (Fig. 7A, p < 0.001). The relationship between CUL1-9 and their top 20 similar genes is shown in Figure 7B–I. We next designed a protein-protein interaction network analysis by STRING (www.string-db.org) to analyse the latent coactions among CULs and their associated genes (Fig. 7A). We further used the plug-in MCODE of Cytoscape to detect the top 10 hub genes with higher correlation: ATM, CDK1, ATRX, XRCC5, BARD1, CDK2, EZH2, PAXIP1, DDX6, and TAF1 (Fig. 8A, B).

Figure 7. Correlation heatmaps of cullins (CULs) and their most correlated genes in head and neck squamous cell carcinoma (HNSCC). A. Correlation heatmap of different expressed CULs in HNSCC. Red and blue cells indicate co-occurrence and mutual exclusivity, respectively; B–I. Correlation heatmap of CUL1-9 expression and its top 20 correlated genes. *p < 0.05; **p < 0.01; ***p < 0.001

Figure 8. Enrichment analysis of cullins (CULs) and their most correlated genes in head and neck squamous cell carcinoma (HNSCC). A. Gene-gene interaction network for CULs and their most correlated genes (Cytoscape); B. Top ten hub genes with a higher degree of connectivity; C. The functions of CULs and their most correlated genes were predicted by the analysis of gene ontology [Gene Oncology, and Kyoto Encyclopedia of Gene and Genomes (KEGG) by Metascape tolls]. Go and KEGG enrichment analysis predicted the functional roles of target host genes based on 4 aspects: biological process, cellular components, molecular functions, and KEGG pathway analysis

Predicted functions and pathways of similar genes with CULs

Thereafter, we used GO and KEGG in Metascape to explore the potential functions of CULs and their co-expressed genes. As shown in Figure 8C, various biological processes, for example GO:0044843 (cell cycle G1/S phase transition), GO:0000082 (G1/S transition of mitotic cell cycle), and GO:0044783 (G1 DNA damage checkpoint), were found to be significantly associated with the CULs’ co-expressed genes in HNSCC. Moreover, different cellular components, including skp1-cullin-F-box (SCF) ubiquitin ligase complex (GO:0019005), ubiquitin ligase complex (GO:0000151), and cullin-RING ubiquitin ligase complex (GO:0031461), were significantly connected with the CULs’ co-expressed genes. In addition, CULs’ co-expressed genes also notably influenced diverse molecular functions, such as ubiquitin-like protein transferase activity (GO:0019787), ubiquitin-protein transferase activity (GO:0004842), and ubiquitin protein ligase binding (GO:0031625). The results shown in Figure 8C suggest that CULs and their associated genes were primarily enriched in ubiquitin-mediated proteolysis (hsa04120), which was markedly associated with both the occurrence and progression of HNSCC.

Relationship between the transcriptional level of CULs and immune cell infiltration in HNSCC

We next analysed the correlation between the expression of CULs and immune infiltration degree in HNSCC using TIMER database. As Figure 9A and Figure S1 show, we noticed positive interactions between CUL1 and infiltration of CD4+ T cells, dendritic cells, neutrophil, and macrophages, while the transcriptional levels of CUL2, CUL3, CUL4B, and CUL9 were found to be positive in connection with the degree of B cells, CD8+ T cells, CD4+ T cells, dendritic cells, neutrophils, and macrophage infiltration (Supplementary File — Fig. S1, C, E, and H). The transcriptional level of CUL4A was found to be negatively correlated with the degree of CD8+ T cell infiltration, but it was positively connected with the degree of CD4+ T cell infiltration (Supplementary File — Fig. S1D). The CUL5 expression was significantly related to the degree of CD4+ T cell, macrophage, and dendritic cell infiltration (Supplementary File — Fig. S1F). In the meantime, the transcriptional level of CUL7 was significantly connected with the degree of B cell, CD4+ T cell, macrophage, and dendritic cell infiltration. The above results suggest that CULs may participate in the pathogenesis of HNSCC by regulating immune cells infiltration, especially T cells.

Figure 9. Interactions of cullins (CULs) expression and immune system. A. Correlation of CULs expression and immune cell infiltration in head and neck squamous cell carcinoma (HNSCC); B. Correlation heatmap of CULs expression and immune cell-related gene markers; C. Correlation heatmap of CUL expression and 28 tumour-infiltrating lymphocytes (TILs) types; D. Correlation heatmap of CUL2/4A/7/9 expression and 21 immunoinhibitor types; E. Correlation heatmap of CUL2/4A/7/9 expression and 45 immunostimulator types; F. Correlation heatmap of CUL2/4A/7/9 expression and 21 major histocompatibility complex (MHC) molecule types. C–F. The correlation values were normalized by row scale

Correlation between the expression of CULs and typical immune markers in HNSCC

Despite the above results indicating that CULs were not significantly connected with HNSCC prognosis, as observed through their potential interactions with immune infiltration, we next analysed the possible correlation between the transcriptional level of CULs and representative immune biomarkers. As shown in Figure 9B and in Supplementary File — Table S1, prominent correlations were found primarily for CULs and T cell markers such as STAT3, STAT8, CCR8, AHR, and FUT4.

Correlation between the expression of CULs, tumour-infiltrating lymphocytes (TILs), and immunomodulators in HNSCC

Several previous studies have shown that TILs may act as distinct prognostic indicators in multiple tumours [17, 18], and the above results suggest that CUL2/4A/7/9 may play a pivotal role in the survival of HNSCC. We next applied the TISIDB database to analyse the possible relationship between the immune-related characters of 28 TILs, 3 types of immunomodulators (21 major histocompatibility complex [MHC] molecules, 45 immunostimulators and 21 immunoinhibitors) and the expression of CUL2/4A/7/9. As displayed in Figure 9C–F and in Supplementary File — Table S2, CUL2 was found to be negatively connected to 8 TILs, 4 immunoinhibitors, 13 immunostimulators, and 6 of the 21 MHC molecules, but just 3 TILs and 5 immunostimulators were observed to be positively related to CUL2. However, for CUL4A, we noticed that just one immunoinhibitor, 4 immunostimulators, and one MHC molecule were associated with the gene transcriptional level, but 18 TILs, 14 immunoinhibitors, 31 immunostimulators, and 12 MHC molecules were negatively correlated with CUL4A. Lastly, only 6 TILs, 4 immunoinhibitors, 7 immunostimulators, and one MHC molecule were noted to be negatively associated with CUL9, but CUL9 was correlated to 9 TILs, 13 immunoinhibitors, 28 immunostimulators, and 12 MHC molecules. To sum up, it can be predicted that CUL2 perhaps takes part in the tumour-specific immune response by modulating immunomodulators, CUL4A can participate by regulating TILs, immunoinhibitors, immunostimulators, and MHC molecules, while CUL9 perhaps aids by affecting the various immunoinhibitors, immunostimulators, and MHC molecules.

Expression of different CULs in HNSCC tissues and cell lines

Because the tendency of CUL7 overexpression in tumours contradicts its prognostic trend, we obtained HNSCC tissue samples (n = 10) and matched para-carcinoma tissue samples (n = 10) to explore the transcriptional expression of CUL2/4A/9. The clinical materials of these HNSCC patients are shown in Table 2. The results suggest that the relative mRNA expression of CUL4A was significantly higher in tumour compared with in normal tissue, while CUL9 was lower in caner tissues (pCUL4A = 0.0019, pCUL9 = 0.0363; Fig. 10A). Moreover, we used multiple HNSCC cell lines to study the gene different expressions: HNEpC, CNE-2, FaDu, and KB. We found that CUL2 expression was higher but CUL9 was lower in tumour cell lines than HNEpC, which was regarded as a control cell line (pCUL2 < 0.001, pCUL9 in Fadu = 0.0363, pCUL9 in KB < 0.001; Fig. 10B).

Figure 10. The effects of cullin 2 (CUL2) on proliferation and migration of head and neck squamous cell carcinoma (HNSCC) cells. A. Different CULs expression in HNSCC tissues and cell lines; B. The relative expression of CUL2 messenger ribonucleid acid (mRNA) in HNSCC cells transfected with normal control (NC) or overexpressed CUL2 (OE-CUL2); C. The cell counting kit 8 (CCK-8) assay between 0 h and 48 h group in transfection with NC and OE-CUL2; D. The wound healing assay between 0 h and 24 h group in transfection with NC and OE-CUL2; E. The quantitative result of (D). *p < 0.05, **p < 0.01, ***p < 0.001

Effect of CULs on proliferation and migration of HNSCC cells

Subsequently, we built overexpressed CUL2 (OE-CUL2) or CUL4A (OE-CUL4A) plasmid and short hairpin RNAs of CUL9 (CUL9 shRNA), respectively, to identify the effects on the proliferation and migration of HNSCC cells. The 3 plasmids were transfected separately into CNE-2, Fadu, and KB. After 48 hours, we detected the relative expression of CULs mRNA to validate whether the transfection was successful (pCNE-2 < 0.001, pFadu < 0.001, pKB < 0.001; Fig. 10C, 11A, and 12A). Next, CCK-8 assay and wound healing assay were used to explore the function of different CULs in HNSCC cell lines. The results indicate that CUL2 can promote cellular proliferation (pCNE-2 = 0.0019, pFadu = 0.0015, pKB = 0.0051, Fig. 10D) and migration (pCNE-2 = 0.0021, pFadu < 0.001, pKB = 0.0046, Fig. 10EF), and CUL4A can enhance the migration (pCNE-2 = 0.0081, pFadu = 0.0317, pKB = 0.0090, Fig. 11C, D) and proliferation (pCNE-2 = 0.0058, pFadu = 0.0237, pKB = 0.0199, Fig. 10B) of HNSCC cells. However, CUL9 might inhibit the ability of cell proliferation (pCNE-2 = 0.0447, pFadu = 0.0051, pKB = 0.0449, Fig. 12B) and migration (pCNE-2 = 0.0095, pFadu = 0.0055, pKB = 0.0243, Fig. 12C, D).

Figure 11. The effects of cullin 4A (CUL4A) on proliferation and migration of head and neck squamous cell carcinoma (HNSCC) cells. A. The relative expression of CUL4A messenger ribonucleid acid (mRNA) in HNSCC cells transfected with normal control (NC) or overexpressed CUL2 (OE-CUL4A); B. The cell counting kit 8 (CCK-8) assay between 0 h and 48 h group in transfection with NC and OE-CUL4A; C. The wound healing assay between 0 h and 24 h group in transfection with NC and OE-CUL4A. E. The quantitative result of (C). *p < 0.05, **p < 0.01, ***p < 0.001

Figure 12. The effects of cullin 9 (CUL9) on proliferation and migration of head and neck squamous cell carcinoma (HNSCC) cells. A. The relative expression of CUL9 messenger ribonucleid acid (mRNA) in HNSCC cells transfected with normal control (NC) or short hairpin RNAs of CUL9 (CUL9 shRNA); B. The cell counting kit 8 (CCK-8) assay between 0 h and 48 h group in transfection with NC and CUL9 shRNA; C. The wound healing assay between 0 h and 24 h group in transfection with NC and CUL9 shRNA; D. The quantitative result of (C). *p < 0.05, **p < 0.01, ***p < 0.001

Discussion

Due to genetic factors that can contribute to an increased risk of HNSCC, it is urgent to find more novel molecular indicators to accurately predict the tumourigenesis, progression, prognosis, and potential therapeutic targets of HNSCC. It has been established that different members of the CUL family play a pivotal role in both the occurrence and development of HNSCC [19–21]. Although certain members of the CUL family have been shown to be referred to the pathogenesis of HNSCC, the distinct role of the CUL family in HNSCC remains unknown. The purpose of the present research study was to explore the expression, prognostic values, co-expressed genes, and immune cell infiltration of different CULs in HNSCC.

Our findings detected an upregulation of CUL1/2/4A/4B/7 mRNAs, while CUL3 mRNA was low-expressed, and the expression of CUL5/9 was not significant. Next, the transcriptional level of CULs was observed to be correlated with clinicopathological materials in HNSCC. In addition, higher mRNA expressions of CUL7/9 were significantly correlated to favourable OS of HNSCC, while lower mRNA expression of CUL2/4A was predominantly associated with that of HNSCC. Moreover, the functions and pathways of the CULs and 20 co-expressed genes in HNSCC were explored, and we found that the top 10 hub genes, including ATM, CDK1, ATRX, XRCC5, BARD1, CDK2, EZH2, PAXIP1, DDX6, and TAF1, were in correlation with CUL expression. Various biological processes such as cell cycle G1/S phase transition (GO:0044843), cellular components, including GO:0000151 and molecular functions, such as GO:0019787, were markedly regulated by CUL similar genes in HNSCC. These results suggest that CULs were more enriched in pathways related to cell proliferation and ubiquitin. Finally, we analysed the correlation between CUL expression and immune cell infiltration, especially T cells in HNSCC. The above results clearly indicat that since the tendency of CUL7 overexpression in HNSCC contradicts its prognostic trend, and CUL9 was the most significant gene related to overall survival in HNSCC, CUL2/4A//9 may serve as a potential marker of prognosis in HNSCC patients.

Several previous studies have indicated that cullin 2 (CUL2) could be overexpressed in some types of tumours, and that it is significantly associated with prognosis. For instance, in glioblastoma multiforme (GBM), increased CUL2 expression, which functions in encoding the scaffold protein CUL2 in the CRL2 E3 ligase, was found to predict GBM progression and prognosis [22]. Recently, it has been suggested that the transcriptional activity of CUL2 might vary according to the size of oral squamous cell carcinoma (OSCC) [23]. In the present research, we found that the mRNA expression of CUL2 was markedly elevated, and it was significantly connected with clinicopathological features, while it also was directly associated with the degree of infiltration of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. Also, a lower transcriptional level of CUL2 was observed in connection with the favourable OS of HNSCC. Therefore, we verified the overexpression of CUL2 in HNSCC cell lines and identified that CUL2 could accelerate the proliferation and migration of HNSCC cells, thereby clearly indicating an independent biomarker role of CUL2 in HNSCC.

Cullin 4A (CUL4A) is one of the most extensively studied CULs in cancer. A variety of previous studies have reported that increased expression of CUL4A could serve as a latent prognostic indicator in intrahepatic cholangiocarcinoma [24]. Mechanistically, overexpression of CUL4 could mediate the proliferation and apoptosis of colon cancer cells by modulating the Hippo pathway [25]. CUL4A has similar oncogenic effects in nasopharyngeal carcinoma. The expression of CUL4A has been directly related to cancer stage and prognosis in nasopharyngeal carcinoma [26]. Meanwhile, we found that an increased transcriptional level of CUL4A was shown in HNSCC samples, and the level of CUL4A mRNA could be correlated to clinic-pathological features. The transcriptional level of CUL4A was positively connected with CD4+ T cell infiltration. In addition, it was observed that an increased transcriptional level of CUL4A promoted cellular proliferation and migration, which was memorably linked to poor OS of HNSCC, indicating that CUL4A may actively control the occurrence of HNSCC by regulating T-cell immune response.

The conflicting roles of cullin 7 (CUL7) have been found in multiple types of human cancers. First, overexpression of CUL7 can play a major role in the tumourigenesis and progression of hepatocellular carcinoma (HCC) and potentially serves as an important biomarker for HCC [27]. Moreover, CUL7 promoted proliferation and invasion of breast cancer (BC) cells by causing down-regulation of protein p53 (p53) activity. In addition, studies have also proven that CUL7 can function as a new breast cancer oncogene and act as a potential treatment biomarker for BC [28]. Furthermore, the transcriptional level of CUL7 was found to be increased in primary lung cancer samples [29]. In the present research, conflicting findings about the function of CUL7 in HNSCC were obtained. First, increased mRNA expression of CUL7 was observed in HNSCC samples, and the transcriptional level of CUL7 was dramatically linked to clinicopathological features. However, an increased mRNA level of CUL7 was correlated with better OS in HNSCC, and the tendency of CUL7 overexpression in tumours might contradict its prognostic trend. As a result, more in-depth studies are needed to evaluate the exact function of CUL7 in HNSCC.

The role of cullin 9 (CUL9) in cancer remains unclear. A few recent studies have reported that the CUL9 (formerly Parc) gene can function in encoding the E3 ubiquitin ligase, which can directly bind to p53 and translocate in the cytoplasm. Moreover, CUL9 deletion led to spontaneous cancer progression and accelerated transgenic mice bearing a c-myc oncogene (EC-MYC)-induced lymphomas, and predisposed mice to cancer [30]. Likewise, the expression of CUL9 had no significance in the TCGA database, but in this study we found that the lower mRNA expression of CUL9 was noted in HNSCC samples and cells. Furthermore, higher transcriptional level of CUL9 was observed to favour the OS of HNSCC, which was in keeping with our experimental result. The bioinformatics analysis also suggested that CUL9 perhaps takes part in the regulation of the immune response primarily through controlling the potential relationship between immunoinhibitors, immunostimulators, and MHC molecules. Lastly, we found that knockdown of CUL9 could inhibit the capacity for proliferation and migration in HNSCC cell lines. Overall, our results suggest that CUL9 also played an important tumour-promoting role in HNSCC.

There are some limitations associated with our study. First, more in-depth research, which also include a greater number of samples, are needed to verify our conclusions and to decipher the clinical application of CULs in both the diagnosis and treatment of HNSCC. Second, we did not analyse the latent diagnostic and clinical treatment functions of CULs in HNSCC, and lastly, other limitations such as the lack of investigation of the downstream molecular mechanisms contributing to the tumour-promoting function of CULs in HNSCC and lack of preclinical validation should also be discussed. Thus, whether CULs could be used as symptomatic biomarkers or therapeutic indicators remains to be further studied.

Conclusion

On the one hand, multivariate bioinformatics analysis suggests that the transcriptional levels of CUL2/4A/9 serve as latent prognostic indicators for overall survival of HNSCC. On the other hand, the results also suggest that CUL2/4A/9 could affect the proliferation and migration of HNSCC cells in vitro. Overall, these results indicate that CUL2/4A/9 potentially function as novel independent indicators for predicting survival in HNSCC patients. Nevertheless, the detailed downstream mechanism regarding the role of CUL2/4A/9 in the prognosis of HNSCC needs more in-depth research.

Acknowledgements

The authors would like to thank all reviewers who participated in the review and MJEditor (www.mjeditor.com) for its linguistic assistance during the preparation of this manuscript.

Data availability

The data used to support the findings of this study are available from the corresponding author upon reasonable request.

Conflict of interest

The authors declare no conflict of interest.

Author’s contributions

Substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data: B.X., R.W., F.C., X.D. Drafting the article or revising it critically for important intellectual content: B.X., R.W., F.C., X.D. Final approval of the version to be published: J.Z., L.W., X.C., Y.J. All authors have reviewed and approved the submitted manuscript and agree to be accountable for all aspects of the work submitted.

Funding statement

This work was funded by National Natural Science Foundation of China (81770978).

Acknowledgements

The authors would like to thank all reviewers who participated in this research paper and MJEditor (www.mjeditor.com) for its linguistic assistance during the preparation of this manuscript.