Purpose: Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers worldwide, and alternative splicing is considered to play important roles in tumor progression. Our study is designed to identify alternative splicing events (ASEs) in human papillomavirus (HPV)–negative HNSCC.

Experimental Design: RNA sequencing data of 407 HPV-negative HNSCC and 38 normal samples were obtained from The Cancer Genome Atlas (TCGA), and splice junctions were discovered using MapSplice. Outlier analysis was used to identify significant splicing junctions between HPV-negative HNSCC and normal samples. To explore the functional role of the identified DOCK5 variant, we checked its expression with qRT-PCR in a separate primary tumor validation set and performed proliferation, migration, and invasion assays.

Results: A total of 580 significant splicing events were identified in HPV-negative HNSCC, and the most common type of splicing events was an alternative start site (33.3%). The prevalence of a given individual ASE among the tumor cohort ranged from 9.8% and 64.4%. Within the 407 HPV-negative HNSCC samples in TCGA, the number of significant ASEs differentially expressed in each tumor ranged from 17 to 290. We identified a novel candidate oncogenic DOCK5 variant confirmed using qRT-PCR in a separate primary tumor validation set. Loss- and gain-of-function experiments indicated that DOCK5 variant promoted proliferation, migration, and invasion of HPV-negative HNSCC cells, and patients with higher expression of DOCK5 variant showed decreased overall survival.

Conclusions: Analysis of ASEs in HPV-negative HNSCC identifies multiple alterations likely related to carcinogenesis, including an oncogenic DOCK5 variant. Clin Cancer Res; 24(20); 5123–32. ©2018 AACR.

Translational Relevance

Human papillomavirus (HPV)–negative head and neck squamous cell carcinoma (HNSCC) represents a distinct clinical entity from HPV-positive HNSCC. Recently, alternative splicing has been shown to be closely related to tumor progression. However, the characterization of alternative splicing in HPV-negative HNSCC is still largely undescribed. In this study, we identified 580 significant splicing events in HPV-negative HNSCC, and we identified a novel DOCK5 variant highly expressed in a separate primary tumor validation set using qRT-PCR. We demonstrated that the DOCK5 variant played an oncogenic role in HPV-negative HNSCC, which could promote proliferation, migration, and invasion in HPV-negative HNSCC cell lines, and patients with higher expression of DOCK5 variant showed decreased overall survival. Identification of alternative splicing in HPV-negative HNSCC allows for a promising avenue to identify novel therapeutic targets and expands the understanding of HNSCC carcinogenesis.

Head and neck cancer is the sixth most frequent malignant tumor worldwide, and more than 90% of these cancers are head and neck squamous cell carcinomas (HNSCCs). Despite great advances in surgery, radiotherapy, chemotherapy and even immunotherapy in the last decades, the 5-year survival rate for HNSCC is still relatively poor (1, 2). Compared with human papillomavirus (HPV)–positive HNSCC, patients with HPV-negative HNSCC have significantly worse prognosis (3, 4). Therefore, there is an urgent need to advance our understanding of the underlying molecular mechanisms associated with HPV-negative HNSCC carcinogenesis.

Alternative splicing events (ASEs) are a regulated process during gene expression that results in multiple mRNA and protein isoforms from a single gene. This process occurs in nearly all multiexonic genes and increases the coding capacity of the human genome (5, 6). Given that ASEs play an important role in the regulation of gene expression, aberrant splicing has thus been involved in a variety of human diseases including cancer (7). For instance, two splice variants of BCL2L1 have been described in cancer, BCL-XL and BCL-Xs, which arise from an alternative 5′ splicing site (8). The short isoform BCL-XS has proapoptotic effects, whereas the long isoform BCL-XL is antiapoptotic. In lymphoma and hepatocellular carcinoma, BCL-XL isoform is predominant and protects cancer cells from p53-mediated apoptosis (9–11). With the development of next-generation sequencing technologies and bioinformatics, more and more cancer-specific splicing patterns have been discovered. These splice variants could be used as hallmarks for cancer and potential therapeutic targets (12). In HNSCC, our previous study has identified several cancer-related ASEs such as LAMA3 and DST variants using microarray analysis (13). And through RNA sequencing analysis, a novel functional splice variant of AKT3 was identified in HPV-positive HNSCC, which could promote the proliferation of cancer cells (14). However, the pattern of ASEs in HPV-negative HNSCC has yet to be elucidated.

In the past few years, genomic information related to various types of cancer has been annotated in databases such as The Cancer Genome Atlas (TCGA). These RNA sequencing data make it possible for systematic analysis of ASEs including novel splice variants in cancer. In our current study, we reanalyze RNA sequencing data from the TCGA HPV–negative HNSCC cohort with MapSplice to detect splice variants and apply outlier analysis to identify tumor-specific ASEs. Compared with normal samples, we identified 580 significant alternative splicing alterations in HPV-negative HNSCC, including a splice variant of DOCK5 with a unique end site. DOCK5 is a member of DOCK (dedicator of cytokinesis) family, and members of this family act as guanine nucleotide exchange factors (GEFs) for small Rho family G proteins to regulate various physiologic processes such as cell development, autoimmunity, and bone homeostasis (15, 16). However, the role of DOCK5 is not well understood yet. In this study, through loss- and gain-of-function experiments, the DOCK5 variant is confirmed to promote proliferation, migration, and invasion in HPV-negative HNSCC cells. These results provide valuable clues toward elucidating the function of DOCK5 variant on HPV-negative HNSCC carcinogenesis.

Patient samples

Primary HPV-negative HNSCC tumor tissue samples (n = 27) and normal mucosal samples from uvulopalatopharyngoplasty (UPPP) surgeries of non–cancer-affected patients (n = 17) were obtained from the cohort described previously (17). All of these tissue samples were collected from the Johns Hopkins Tissue Core under an Institutional Review Board–approved protocol (#NA_00036235). Patient studies were conducted in accordance with the Declaration of Helsinki. Informed consents were obtained from all of the patients prior to participation in the study.

TCGA dataset

Raw RNA-seq data (fastq files) and clinical data of HPV-negative HNSCC and normal samples were obtained from the TCGA Research Network (TCGA Provisional version updated in 2016, http://cancergenome.nih.gov/). These TCGA data included 407 HPV-negative HNSCC and 38 normal tissues. RNA-Seq by Expectation Maximization (RSEM)–normalized gene expression values for the same samples were downloaded from the Broad GDAC Firebrowse website (http://firebrowse.org/).

Identification of splice variants

The method used for identification of cancer-specific splice variants was reported previously (14). Alignment of TCGA RNA sequencing data was conducted with MapSplice (18) to the GRCh37/hg19 genome assembly. Splice junction data from alignment were extracted for the following analysis. Expression values of junction were normalized as reads per million and log transformed. The junctions were filtered if there was no difference in expression between any tumor and any normal samples, as well as if the junctions mapped to X, Y, and MT chromosomes. The junctions were then mapped to known genes and exons based on GRCh37/hg19 genome assembly, and considered as putative splicing events if they were identified either as a skip (junction that skips a known exon), insertion (junction that starts or ends outside a known exon), or deletion (junction that starts or ends within a known exon). Expression values of these selected junctions were normalized by the RSEM values for the genes which were downloaded from TCGA. Outlier analysis was performed to identify the significant junctions between tumor and normal samples.

Integrative genome viewer validation

Putative significant junctions identified from outlier analysis were then visualized in Integrative Genome Viewer (IGV, Broad Institute; ref. 19). BAM files of RNA sequencing data were loaded into IGV, and reads coverage were visualized at start and end of each junction. Putative junctions were confirmed if the overall gene expression was observed in both normal and tumor tissues, and a unique novel splicing event was identifiable in tumor samples. Junctions were then categorized as either alternative start site, alternative end site, canonical skipping, insertion, deletion, intron retention, or noncoding.

Cell culture and reagents

Human HPV-negative HNSCC cell line BHY, UM-SCC17B, and Detroit562 were obtained from the Gutkind Laboratory at the University of California San Diego, Moores Cancer Center, and JHU011 cell line was obtained from Division of Head and Neck Cancer Research at the Johns Hopkins University. Cells were fingerprinted and confirmed using short tandem repeat analysis (20). BHY, UM-SCC17B, and Detroit562 cells were cultured in DMEM (Sigma Aldrich), whereas JHU011 cells were cultured in RPMI-1640 medium (Sigma Aldrich), supplemented with 10% FBS and 1% penicillin–streptomycin. All cells were maintained at 37°C in an atmosphere of 5% CO2 and 95% relative humidity.

siRNA transfection

BHY and JHU011 cell lines were transfected with siRNA reagents using Lipofectamine RNAiMAX (Thermo Fisher Scientific) according to the manufacturer's instruction. Three unique custom-designed siRNAs targeting the specific exon of DOCK5 variant were purchased from GE Dharmacon using ON-TARGETplus (Supplementary Table S1). ON-TARGETplus SMART pool DOCK5 siRNA (L-018931-00-0005) was used for knockdown of the overall DOCK5 gene expression, and a scrambled ON-TARGETplus Non-targeting pool siRNA (D-001810-10-20) was used as a negative control (NC), and the parental cancer cells without transfection were used as a blank control (Blank).

Stable transfection

The pLenti-C-mGFP-P2A-Puro empty vector (EV) was obtained from OriGene Technologies, and genes of DOCK5 wild-type and variant were synthesized and cloned into the vector by GenScript, Inc. Lentiviral particles were prepared for EV, DOCK5 wild-type, and DOCK5 variant using 293T cells as the packaging cells. UM-SCC17B and Detroit562 cells were infected with these lentiviruses and selected with 1 μg/mL Puromycin (InvivoGen).

Quantitative real-time PCR

To validate gene expression of DOCK5 wild-type (DOCK5 WT) and variant (DOCK5 Var), primers and probes sets were designed specifically to span the junction between the canonical two exons (DOCK5 WT) as well as the canonical exon and the unique tumor novel exon (DOCK5 Var) using PrimerQuest tools (Integrated DNA Technologies). The sequences of primer and probe were listed in Supplementary Table S1. Touchdown PCR was performed to identify appropriate length of PCR product for primers used. Quantitative RT-PCR (qRT-PCR) was used to determine the gene expression.

Total RNA was extracted from tissues and cells using an RNeasy plus mini kit (Qiagen), and reverse transcription was carried out with a high-capacity cDNA reverse transcription kit (Thermo Fisher Scientific). β-Actin was used as an internal control (Hs01060665_g1 TaqMan Gene Expression Assays, Thermo Fisher Scientific). PCR quantification was performed using the 2CT method.

Viability assay

Cells (3 × 103) per well were seeded into 96-well plates, and cell viabilities were measured at 24, 48, and 72 hours after transfection using Vita Blue Cell Viability Reagent (Bimake). After being incubated for 1 hour at 37°C in the assay solution, fluorescence (Ex = 530–570 nm, Em = 590–620 nm) was measured using a microplate reader (BioTek). All the experiments were repeated three or more times.

Colony formation assay

For colony formation assay, different groups of cells were seeded into 6-well plates (1 × 103 cells per well) and incubated for 2 weeks. Then the colonies were fixed with 4% paraformaldehyde and stained with crystal violet. Each experiment was repeated independently in triplicate.

Cell scratch assay

Cell migration ability was examined by cell scratch assay. Briefly, transfected cells were seeded on 6-well plates and incubated to almost full confluence. Scratching was performed with a 200-μL plastic pipette tip, and the cells were cultured in serum-free medium. The initial gap width (0 hour) and the residual gap width at 24 to 96 hours after scratching were observed and photographed under the inverted microscope. The experiment was performed in triplicate.

Transwell migration and invasion assay

Transwell migration assay was conducted using 8-μm pore size Corning Transwell migration chambers, and invasion assay was performed using Corning BioCoat Matrigel Invasion chambers (Corning Inc.) according to the manufacturer's protocol. Briefly, cells (1 × 105 cells for migration; 2 × 105 cells for invasion) with serum-free medium were seeded to the upper chamber. After incubation for 48 hours, nonmigrating or invading cells on the surface of the upper chamber were removed with a cotton-tipped swab. The migrated or invaded cells on the lower side were fixed with paraformaldehyde, stained with 1% crystal violet, and then counted in five random fields under microscope.

Western blot analysis

Total cell proteins were extracted with RIPA lysis buffer, and the concentrations were measured using the Protein Assay Kit (Bio-Rad). Equal amounts of protein were separated on Mini-PROTEAN TGX gels (Bio-Rad) and transferred onto polyvinylidene fluoride membranes (Millipore). After blocking with 5% BSA at room temperature for 30 minutes, the membranes were incubated with the relevant primary antibody at 4°C overnight, followed by incubation with secondary antibodies for 1 hour at room temperature. The primary antibodies of p38, p-p38, Erk, p-Erk, MEK1/2, and p-MEK1/2 were all obtained from Cell Signaling Technology (1:1,000). Anti-GAPDH (1:10,000, Cell Signaling Technology) was used as the loading control. Western blots were developed by ECL reagent (Pierce ECL Western Blot Substrate, Thermo Scientific).

Gene set analysis

Functional pathways associated with the oncogenic activities of DOCK5 variant were evaluated by gene set analysis. Hallmark gene sets were obtained from the Molecular Signatures Database (MSigDB, C2, Broad institute). Using the RNA sequencing data from TCGA HPV–negative HNSCC samples, gene set enrichment analysis was performed (21), and data were compared between high DOCK5 variant expression and low DOCK5 variant expression samples. Benjamini–Hochberg correction was applied to P values from gene set analysis to correct for multiple comparisons, and P < 0.001 was considered to be significant.

Statistical analysis

All assays were performed at least in triplicate, and the results of the quantitative data represent mean ± SD of three independent experiments. The statistical comparisons of two groups were determined with a two-sided unpaired Student t test (for equal variances) or Mann–Whitney U test (for unequal variances) using SPSS software (version 23.0; SPSS Inc.). P < 0.05 was considered statistically significant.

Identification of significant ASEs in HPV-negative HNSCC

For the TCGA RNA-seq data, a total of 4,660,670 putative junctions were identified by alignment with MapSplice. As shown in Fig. 1, after filtering junctions by multiple criteria, a total of 18,504 junctions were left for further analysis. Then these junctions were normalized by corresponding gene expression in each sample. Using an outlier analysis, 969 significant junctions were found differentially expressed in HPV-negative HNSCC tissues compared with normal tissues. Each junction with statistically significance was then visualized in the IGV to validate the presence of a true ASE when comparing tumors and normal samples. Finally, 580 (59.9%) of significant junctions were confirmed after IGV visualization, involving 501 unique genes (Supplementary Table S2).

Figure 1.

Pipeline for identification of significant ASEs through RNA-seq analysis. Initially, from MapSplice output, 4,660,670 raw junctions, representing splice variant isoforms, were present within TCGA HPV–negative HNSCC cohort. These junctions were normalized and then filtered to exclude junctions without variation or those on X, Y, and mitochondrial (MT) chromosomes. Then potential splice variants were identified on the basis of possible alternative splicing patterns, and 18,504 potential candidates remained. Outlier statistics were applied to identify candidates with differential expression between tumors and normal samples, of these, 969 splice variants were identified. Finally, these junctions were validated by IGV visualization, and 580 junctions, which mapped to 501 unique genes, were confirmed.

Figure 1.

Pipeline for identification of significant ASEs through RNA-seq analysis. Initially, from MapSplice output, 4,660,670 raw junctions, representing splice variant isoforms, were present within TCGA HPV–negative HNSCC cohort. These junctions were normalized and then filtered to exclude junctions without variation or those on X, Y, and mitochondrial (MT) chromosomes. Then potential splice variants were identified on the basis of possible alternative splicing patterns, and 18,504 potential candidates remained. Outlier statistics were applied to identify candidates with differential expression between tumors and normal samples, of these, 969 splice variants were identified. Finally, these junctions were validated by IGV visualization, and 580 junctions, which mapped to 501 unique genes, were confirmed.

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Characterization of significant ASEs

These 580 identified significant junctions were characterized as ASEs into the following categories: alternative start site (33.3%), alternative end site (20.2%), canonical variant or exon skipping (11.0%), insertion (17.1%), deletion (13.4%), intron retention (1.0%), and noncoding (4.0%; Table 1). These ASEs were frequently expressed across multiple tumors, and the prevalence of a given individual ASE among the tumor cohort was between 9.8% and 64.4% of tumors harboring the same ASE (Supplementary Table S3). Within the 407 HPV-negative HNSCC samples in TCGA, the number of ASEs identified in each tumor ranged from 17 to 290 (media, n = 106; Supplementary Fig. S1). As shown in Supplementary Fig. S1, based on the number of ASEs in each tumor, the patients are divided into a high and low ASEs group. We found that there was no association between the number of ASEs identified within a tumor and the clinical parameters such as age (P = 0.9213), smoking status (P = 0.7204), alcohol consumption (P = 0.0682), clinical stage (P = 0.1675), pathologic stage (P = 0.0728), and lymph node metastasis (P = 0.5397). The patients with higher numbers of ASEs were more commonly occurred in male than female (P = 0.0018; Supplementary Table S4). In addition, 10 of these identified significant junctions was also found in HPV-positive HNSCC as described previously (ref. 14; Supplementary Table S5), which indicated these 10 ASEs may play roles in both HPV-negative and -positive HNSCC.

Table 1.

Category of identified 580 ASEs associated with HPV-negative HNSCC

Types of splicing eventsNumber of junction (580)Percentage
Alternative start site 193 33.3% 
Alternative end site 117 20.2% 
Canonical variant or exon skip 64 11.0% 
Insertion 99 17.1% 
Deletion 78 13.4% 
Noncoding 23 4.0% 
Intron retention 1.0% 
Types of splicing eventsNumber of junction (580)Percentage
Alternative start site 193 33.3% 
Alternative end site 117 20.2% 
Canonical variant or exon skip 64 11.0% 
Insertion 99 17.1% 
Deletion 78 13.4% 
Noncoding 23 4.0% 
Intron retention 1.0% 

DOCK5 variant is highly expressed in HPV-negative HNSCC

Of these 580 identified significant junctions, junction chr8:25126401-25128306 within the gene DOCK5 was one of the most significant ASEs. Through IGV visualization, a novel exon with alternative end site was present in TCGA HPV–negative HNSCC samples, whereas normal samples were harboring canonically splicing exons; and the amino acid length of DOCK5 variant was much shorter than DOCK5 WT (Fig. 2A). In TCGA data, most tumor samples have higher expression of DOCK5 variant compared with normal samples, and the total gene expression of DOCK5 was unchanged across tumor and normal samples (Fig. 2B). Compared with normal tissues, the expression of the DOCK5 variant was also upregulated in tumors from diverse head and neck regions (Supplementary Fig. S2). To further confirm DOCK5 variant was specifically involved in HPV-negative HNSCC samples, qRT-PCR was applied to compare the expression of DOCK5 variant in a validation set of 27 HPV-negative HNSCC and 17 UPPP normal tissues. The results showed that DOCK5 variant was more highly expressed in tumor samples than UPPP normal tissues, whereas there were no significant changes in wide-type DOCK5 gene expression (Fig. 2C). Meanwhile, TCGA clinical data showed that higher expression of DOCK5 variant was associated with decreased overall survival in HPV-negative HNSCC patients (Fig. 2D). To analyze the relationship between DOCK5 variant expression and gene mutation, we selected the significantly mutated genes identified with cBioPortal (MutSig q-value < 0.1) in the TCGA HNSCC data (22, 23). As shown in Supplementary Fig. S3, among these 75 significantly mutated genes, the mutations or copy-number alterations of TP53, NSD1, and OR2M5 gene were more commonly occurred in patients with higher expression of DOCK5 variant (P < 0.05), and DPPA2 gene mutation or copy-number alteration was more commonly occurred in patients with lower expression of DOCK5 variant (P < 0.05). We also found that there was no significant association between the expression of DOCK5 variant and the clinical parameters such as age, sex, alcohol consumption, clinical stage, pathologic stage, and lymph node metastasis. But the patients with higher expression of DOCK5 variant were more commonly occurred in smokers than nonsmokers (P = 0.0358; Supplementary Table S6). These results indicate that DOCK5 variant overexpression may play a significant role in HPV-negative HNSCC initiation and progression.

Figure 2.

DOCK5 variant is highly expressed in HPV-negative HNSCC. A, IGV visualization of DOCK5 variant shows an alternative end site with expression unique to tumors (top), in which 10 representative samples with reads coverage were shown. Schematic diagram of DOCK5 variant shows the alternative end site (middle); amino acid sequence of DOCK5 variant shows the alternative end site, and the amino acid length of DOCK5 variant was much shorter than DOCK5 WT (bottom). B, Unique DOCK5 junction expression and overall DOCK5 gene expression in TCGA HPV–negative HNSCC data is shown. Expression of the DOCK5 splice junction is identified mostly in tumors. The corresponding overall DOCK5 gene expression (RSEM normalized) shows that these differences in DOCK5 splice variant expression are not fully explained by overall gene expression. Each vertical bar represents one sample sorted by expression level of DOCK5 variant (normal samples: blue; tumors: red). C, Biological validation of DOCK5 variant expression in primary tumor tissues. Quantitative PCR for identification of the DOCK5 variant shows significantly increased expression in tumors compared with normal UPPP tissues (P < 0.001), whereas wild-type DOCK5 gene expression is similar between tumors and normal tissues (NS), and the ratio of DOCK5 variant to wild-type is higher in in tumors than UPPP tissues (P < 0.001). D, Log-rank test shows that the patients with higher expression of DOCK5 variant have decreased overall survival (P = 0.0374), but no significant changes of disease-free survival (P = 0.2750). The patients with no expression of DOCK5 variant (n = 127) are defined as lower expression of DOCK5 variant group. ***, P < 0.001 and NS, not significant.

Figure 2.

DOCK5 variant is highly expressed in HPV-negative HNSCC. A, IGV visualization of DOCK5 variant shows an alternative end site with expression unique to tumors (top), in which 10 representative samples with reads coverage were shown. Schematic diagram of DOCK5 variant shows the alternative end site (middle); amino acid sequence of DOCK5 variant shows the alternative end site, and the amino acid length of DOCK5 variant was much shorter than DOCK5 WT (bottom). B, Unique DOCK5 junction expression and overall DOCK5 gene expression in TCGA HPV–negative HNSCC data is shown. Expression of the DOCK5 splice junction is identified mostly in tumors. The corresponding overall DOCK5 gene expression (RSEM normalized) shows that these differences in DOCK5 splice variant expression are not fully explained by overall gene expression. Each vertical bar represents one sample sorted by expression level of DOCK5 variant (normal samples: blue; tumors: red). C, Biological validation of DOCK5 variant expression in primary tumor tissues. Quantitative PCR for identification of the DOCK5 variant shows significantly increased expression in tumors compared with normal UPPP tissues (P < 0.001), whereas wild-type DOCK5 gene expression is similar between tumors and normal tissues (NS), and the ratio of DOCK5 variant to wild-type is higher in in tumors than UPPP tissues (P < 0.001). D, Log-rank test shows that the patients with higher expression of DOCK5 variant have decreased overall survival (P = 0.0374), but no significant changes of disease-free survival (P = 0.2750). The patients with no expression of DOCK5 variant (n = 127) are defined as lower expression of DOCK5 variant group. ***, P < 0.001 and NS, not significant.

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DOCK5 variant promotes proliferation of HPV-negative HNSCC cells

To further clarify the role of DOCK5 variant in cancer, specific siRNAs and pooled siRNAs were designed to silence the expression of the tumor-specific variant of DOCK5 with an alternative end exon and overall DOCK5 gene, respectively. Meanwhile, DOCK5 variant or wild-type cDNA was cloned into an expression vector to generate stable cell lines with overexpression of DOCK5 variant or wild-type. Using sequence-specific primers and probes, expression of DOCK5 variant and wild-type was detected in a panel of 14 HPV-negative HNSCC cell lines (Supplementary Fig. S4). From this data, BHY and JHU011 cell lines with the highest expression of DOCK5 variant were selected for loss-of-function assays, and UM-SCC17B and Detroit562 with the lowest expression of DOCK5 variant were selected for gain-of-function assays. qRT-PCR results demonstrated that three specific siRNAs targeting the DOCK5 variant successfully downregulated the expression of the DOCK5 variant, with only modest inhibition of the DOCK5 wild-type gene expression in both BHY and JHU011 cells (Fig. 3A). More specifically, in BHY cells, compared with the NC group, the expression of DOCK5 variant was decreased (92.7 ± 0.3)%, (96.3 ± 0.5)%, (95.3 ± 0.2)%, and the expression of DOCK5 wild-type was decreased only (27.9 ± 0.3)%, (36.1 ± 3.2)%, (25.3 ± 2.5)% by DOCK5 variants 1, 2, and 3, respectively (all P < 0.01). In JHU011 cells, the expression of DOCK5 variant was decreased (88.4 ± 1.2)%, (90.8 ± 3.1)%, (85.6 ± 0.3)%, and the expression of DOCK5 wild-type was decreased (44.6 ± 5.2)%, (45.3 ± 7.8)%, (32.2 ± 1.3)% by DOCK5 variants 1, 2, and 3, respectively (all P < 0.01). As expected, pooled siRNAs designed to target the whole DOCK5 gene decreased both the wild-type and variant expressions of DOCK5; however, the ratio of DOCK5 variant expression to DOCK5 wild-type expression was significantly inhibited by DOCK5 variant siRNA, not by pooled siRNA (Fig. 3A).

Figure 3.

DOCK5 variant promotes proliferation of HPV-negative HNSCC cells. A, qRT-PCR results show the decreased expression of both DOCK5 wild-type (WT) and DOCK5 variant (Var) when treated with pooled siRNA for DOCK5. Three siRNAs specifically targeting DOCK5 variant show inhibition of the alternatively spliced DOCK5, with minimal inhibition of the wild-type gene. Specifically, the right plot shows the ratio of DOCK5 variant to wild-type expression, demonstrating that this ratio is significantly decreased by these three ASE siRNAs in both BHY and JHU011 cell lines. B, Cell viability is measured after knockdown the expression of overall DOCK5 (si Pool) and DOCK5 variant (Var si1, si2, si3) in BHY and JHU011 cells. Proliferation ratio represented the cell numbers relative to day 0. Significant growth inhibition is seen with specific silencing of DOCK5 in both cell lines compared with silencing of the whole DOCK5 gene and control group (Blank, NC). C, Colony formation assay shows the colonies in DOCK5 variant knockdown group are much fewer and smaller than control groups in BHY and JHU011 cells. D, qRT-PCR results show that following transfection of lentivirus of DOCK5 variant or wild-type in UM-SCC17B and Detroit562 cells, the expression of DOCK5 variant or wild-type was successfully upregulated. E, Cell viability assay shows significant growth increase by overexpression of DOCK5 variant, not DOCK5 wild-type. F, Colony formation assay demonstrates that the colonies in DOCK5 variant overexpression group are more and bigger than EV groups and DOCK5 WT overexpression group in UM-SCC17B and Detroit562 cells. *, P < 0.05; **, P < 0.01; ***, P < 0.001; and NS, not significant.

Figure 3.

DOCK5 variant promotes proliferation of HPV-negative HNSCC cells. A, qRT-PCR results show the decreased expression of both DOCK5 wild-type (WT) and DOCK5 variant (Var) when treated with pooled siRNA for DOCK5. Three siRNAs specifically targeting DOCK5 variant show inhibition of the alternatively spliced DOCK5, with minimal inhibition of the wild-type gene. Specifically, the right plot shows the ratio of DOCK5 variant to wild-type expression, demonstrating that this ratio is significantly decreased by these three ASE siRNAs in both BHY and JHU011 cell lines. B, Cell viability is measured after knockdown the expression of overall DOCK5 (si Pool) and DOCK5 variant (Var si1, si2, si3) in BHY and JHU011 cells. Proliferation ratio represented the cell numbers relative to day 0. Significant growth inhibition is seen with specific silencing of DOCK5 in both cell lines compared with silencing of the whole DOCK5 gene and control group (Blank, NC). C, Colony formation assay shows the colonies in DOCK5 variant knockdown group are much fewer and smaller than control groups in BHY and JHU011 cells. D, qRT-PCR results show that following transfection of lentivirus of DOCK5 variant or wild-type in UM-SCC17B and Detroit562 cells, the expression of DOCK5 variant or wild-type was successfully upregulated. E, Cell viability assay shows significant growth increase by overexpression of DOCK5 variant, not DOCK5 wild-type. F, Colony formation assay demonstrates that the colonies in DOCK5 variant overexpression group are more and bigger than EV groups and DOCK5 WT overexpression group in UM-SCC17B and Detroit562 cells. *, P < 0.05; **, P < 0.01; ***, P < 0.001; and NS, not significant.

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Cell viability showed that over 3 days’ transfection, significant growth inhibition was seen in both BHY and JHU011 cells after treatment with three independent ASE-specific siRNAs (Fig. 3B). Notably, this growth inhibition was significant compared with both controls (Blank and NC group) as well as knockdown of overall DOCK5 gene expression (si Pool group), although cell growth was also inhibited in si Pool group compared with Blank and NC group. Meanwhile, a colony formation assay showed similar results, in which the colonies in DOCK5 variant knockdown group were much fewer and smaller than control groups in both cell lines (Fig. 3C). For the gain-of-function assay, in UM-SCC17B and Detroit562 cells, qRT-PCR results showed that the expressions of DOCK5 variant or wild-type were successfully upregulated with transfection of lentivirus of DOCK5 variant or wild-type (Fig. 3D). In both UM-SCC17B and Detroit562 stably transfected cells, cell viability assay showed that overexpression of DOCK5 variant significantly increased cell growth but overexpression of DOCK5 wild-type showed no differences on cell growth (Fig. 3E). Colony formation assay revealed that the colonies in DOCK5 variant overexpression (Var OE) group were much more and bigger than EV and DOCK5 wild-type overexpression (WT OE) group (Fig. 3F). Taken together, these results demonstrate that the tumor-specific DOCK5 variant can promote proliferation of HPV-negative HNSCC cells.

DOCK5 variant promotes migration and invasion of HPV-negative HNSCC cells

To study whether DOCK5 variant affects the metastatic ability of HPV-negative HNSCC in vitro, cell scratch assay and Transwell migration and invasion assay were used to exam the changes of cell migration and invasion after transfection. Cell scratch assay revealed that although cell migration ability was inhibited by knockdown of overall DOCK5, it is much more significantly in DOCK5 variant knockdown group (Fig. 4A), and overexpression of DOCK5 variant could increase cell migration ability (Fig. 4B). Transwell migration and invasion assay demonstrated that the number of migrating or invading cells was significantly reduced by knockdown of DOCK5 variant (Fig. 4C and D) and increased by overexpression of DOCK5 variant (Fig. 4E and F). These results reveal that DOCK5 variant enhances the migration and invasion ability of HPV-negative HNSCC cells.

Figure 4.

DOCK5 variant promotes migration and invasion of HPV-negative HNSCC cells. A, Cell scratch assay demonstrates that cell migration ability was inhibited by knockdown of DOCK5 variant in BHY and JHU011 cells. B, Cell scratch assay demonstrates that cell migration ability was enhanced by overexpression of DOCK5 variant in UM-SCC17B and Detroit562 cells. C, Transwell migration assay shows that the number of migrating cells is decreased by knockdown of DOCK5 variant. D, Transwell invasion assay shows that the number of invading cells is significantly reduced by knockdown of DOCK5 variant. E, Transwell migration assay shows that the number of migrating cells is increased by overexpression of DOCK5 variant. F, Transwell invasion assay shows that the number of invading cells is significantly increased by overexpression of DOCK5 variant. **, P < 0.01 and ***, P < 0.001.

Figure 4.

DOCK5 variant promotes migration and invasion of HPV-negative HNSCC cells. A, Cell scratch assay demonstrates that cell migration ability was inhibited by knockdown of DOCK5 variant in BHY and JHU011 cells. B, Cell scratch assay demonstrates that cell migration ability was enhanced by overexpression of DOCK5 variant in UM-SCC17B and Detroit562 cells. C, Transwell migration assay shows that the number of migrating cells is decreased by knockdown of DOCK5 variant. D, Transwell invasion assay shows that the number of invading cells is significantly reduced by knockdown of DOCK5 variant. E, Transwell migration assay shows that the number of migrating cells is increased by overexpression of DOCK5 variant. F, Transwell invasion assay shows that the number of invading cells is significantly increased by overexpression of DOCK5 variant. **, P < 0.01 and ***, P < 0.001.

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DOCK5 variant activates p38 and Erk MAPK pathway

Dysregulation within the MAPK pathway plays a critical role in HNSCC progression, so we investigated whether the DOCK5 variant was involved in MAPK pathway in HPV-negative HNSCC. Western blot results showed that following knockdown the expression of DOCK5 variant in BHY and JHU011 cells, the expression levels of p-p38, p-Erk, and p-MEK1/2 all decreased (Fig. 5A). And overexpression of DOCK5 variant in UM-SCC17B and Detroit562 cells increased the expression of p-p38, p-Erk, and p-MEK1/2, whereas there were almost no changes in total p38, Erk, and MEK1/2 (Fig. 5B). These results indicate that the DOCK5 variant can activate p38 and Erk MAPK pathways in HPV-negative HNSCC.

Figure 5.

DOCK5 variant activates p38 and Erk MAPK pathway. A, The expression of p-p38, p-Erk, and p-MEK1/2 is decreased following knockdown of the expression of DOCK5 variant in both BHY and JHU011 cells. B, Overexpression of DOCK5 variant upregulated the expression of p-p38, p-Erk, and p-MEK1/2 in both UM-SCC17B and Detroit562 cells.

Figure 5.

DOCK5 variant activates p38 and Erk MAPK pathway. A, The expression of p-p38, p-Erk, and p-MEK1/2 is decreased following knockdown of the expression of DOCK5 variant in both BHY and JHU011 cells. B, Overexpression of DOCK5 variant upregulated the expression of p-p38, p-Erk, and p-MEK1/2 in both UM-SCC17B and Detroit562 cells.

Close modal

Differentially expressed gene and pathway analysis

To better understand the mechanisms of DOCK5 variant in cancer, TCGA HPV–negative HNSCC samples with the highest expression of DOCK5 variant (1/3 of total samples, n = 136) and lowest expression of DOCK5 variant (1/3 of total samples, n = 136) were selected to conduct a differentially expressed gene set and pathway analysis. Compared with the low expression of DOCK5 variant group, 1,018 upregulated genes and 1,163 downregulated genes were found in high expression of DOCK5 variant group, including the top upregulated genes DGUOK, RANBP1, SNRPG, TPRKB, and HSPB11 and top downregulated genes DOPEY2, FYCO1, PBRM1, CCSER2, and MAST3 (Supplementary Fig. S5A and Supplementary Table S7). Meanwhile, 301 upregulated pathways and 682 downregulated pathways were determined in high expression of DOCK5 variant group, including the top upregulated pathways like “KEGG_PROTEIN_EXPORT,” “CHANG_CORE_SERUM_RESPONSE_UP,” and “REACTOME_MRNA_DECAY_BY_3_TO_5_EXORIBONUCLEASE,” and top downregulated pathways like “SHEDDEN_LUNG_CANCER_GOOD_SURVIVAL_A4,” “REACTOME_NOTCH_HLH_TRANSCRIPTION_PATHWAY,” and “KEGG_GNRH_SIGNALING_PATHWAY” (Supplementary Fig. S5B and Supplementary Table S8).

Recently, with the rapid advancement of genome sequencing technologies and bioinformatics, there is an enormous resource of publicly available genome dataset of tumors of different subtypes. Among these databases, TCGA represents the most comprehensive integrative genomic analysis of cancer, which accelerates the thorough understanding of the molecular mechanisms of cancer (24, 25). For HNSCC, TCGA has also identified various genes and pathways that are frequently mutated including TP53, PIK3CA, NOTCH1, CDKN2A, and others, contributing to the development of new preventive strategies, diagnostic methods, and cancer therapies for HNSCC (22). Independent of genetic mutations, alternative splicing is another mechanism by which a single gene may generate multiple mRNAs and protein variants with different and even opposite functions (8, 12). In our current study, utilizing the RNA sequencing data of TCGA, ASEs unique to HPV-negative HNSCC were systematically characterized, which showed that alternative splicing could represent an important functional mechanism of carcinogenesis in HPV-negative HNSCC.

Although the landscape of alternative splicing variants in several types of tumor has been identified (26–30), it has not been previously reported in HPV-negative HNSCC, which is proposed to be a distinct disease from HPV-positive HNSCC with poorer prognosis. Meanwhile, most of currently existing methods to define differential ASE expression is based on comparing mean expression values between tumor and normal samples, which is insufficient for analysis of heterogeneous cancer sample populations (31–35). Outlier statistics was suggested to better capture significant events of heterogeneous tumors that may have similar mean values (36, 37), and our previous studies also demonstrated that applying outlier analysis to microarray and RNA sequencing data was well suited for identifying ASEs in HNSCC (13, 14, 38). Therefore, in this study, outlier analysis was applied to generate the profile of significant ASEs, and 580 ASEs were confirmed in HPV-negative HNSCC. Although some of these identified ASEs may merely represent passenger alterations in RNA levels, many may be functionally active in HPV-negative HNSCC, such as the DOCK5 variant described.

Alternative splicing is a ubiquitous regulatory mechanism that affects more than 95% of multiexonic genes, and it has long been considered as an important mechanism for expansion of the eukaryotic proteome and play important roles in initiation and progression in both solid and liquid tumors (8, 39, 40). To date, several types of alternative splicing have been described such as exon skipping, alternative start or end splice sites, intron retention, and others (41). Kim and colleagues pointed out that the distribution of the types of ASEs was different between cancerous and normal tissues, in which cancer cells showed less exon skipping, but more alternative start or end sites than normal cells (42). Our results also revealed that of these validated ASEs, the majority were alternative start sites (33.3%) and alternative end sites (20.2%). This is similar to HPV-positive oropharyngeal cancer, in which alternative start site was also the most common type of ASE noted (14). One interesting finding was that patients with higher numbers of ASEs were more commonly occurred in men than women (Supplementary Table S4). Compared with ASEs identified in HPV-positive oropharyngeal cancer (14), we found 10 ASEs were included in our results (Supplementary Table S5), such as FBXO3, CYB561A3, GRHL3, NLRP1 variants, and so on, which may play similar roles in both HPV-negative and -positive HNSCC. The small number of ASEs that overlap between HPV-positive and HPV-negative tumors further confirms that these two are distinct entities of head and neck cancer. In addition, it should be noted that some ASEs, like LAMA3 and DST variants that have been previously proved to be upregulated in HNSCC, were not identified in our results (13). These differences might be attributable to different number and clinical features of samples, including stringent outlier statistic, as well as differences between RNA sequencing–based discovery compared with array-based discovery used previously. To define these alternatives, when we relaxed the stringency of the outlier approach by changing offsets in our outlier statistic approach, these variants were differentially present in tumor samples.

Utilizing described outlier statistics, a functionally relevant splice variant of DOCK5 was confirmed in HPV-negative HNSCC. DOCK5 belonged to the DOCK family of GEFs, which consisted of 11 DOCK proteins in mammals (43). And DOCK1 was the founding member of the DOCK family, which was widely reported to be involved in cancer survival, migration, and invasion (44–46). Though DOCK5 possessed the greatest similarity to DOCK1, it was one of the least studied members in the DOCK family, and DOCK5 was associated with mast cell degranulation (47), neutrophils, and osteoclasts activity (48–51), obesity (52, 53), and epithelial invasion (54, 55). With regard to cancer, the role of DOCK5 has been poorly understood thus far. To our knowledge, this was the first study to reveal the function of DOCK5 and its variant on HNSCC progression. We found that DOCK5 variant was highly expressed in HPV-negative HNSCC, and patients with higher expression of DOCK5 variant showed decreased overall survival in the TCGA cohort. However, there was no significance between the expression of DOCK5 variant and disease-free survival (Fig. 2D). Analysis of the relationship between DOCK5 variant and clinical parameters shows that DOCK5 expression is correlated with the smoking status, implying that smoking-related comorbidity may be responsible for the worse overall survival in DOCK5 variant–expressing tumors (Supplementary Table S6). The DOCK5 variant increased cell proliferation, migration, and invasion in HPV-negative HNSCC cells. Particularly, this effect was dependent on the expression ratio of DOCK5 variant compared with DOCK5 wild-type. Knockdown of the DOCK5 variant alone produced significant growth, migration, and invasion inhibition; however, the effect was weakened when knocking down the expression of whole DOCK5 gene including both variant and wild-type, and overexpression of DOCK5 wild-type almost had no effect on cell growth, migration, and invasion. It should be mentioned that this study is limited by some factors. The DOCK5 variant and wild-type were not knocked down independently as the specific siRNAs targeting DOCK5 variant also had a little inhibition of the DOCK5 wild-type, and pooled siRNA also inhibit the expression of DOCK5 variant. In the stably overexpressed cells, the expression of DOCK5 variant was much higher than the expression of the wild-type construct, which may partly explain that there were no obvious phenotype changes in DOCK5 wild-type overexpressed cells.

The DOCK family GEFs contained DHR-1 and DHR-2 domains, in which DHR-2 were GEF catalytic domain (56). Because of the alternative end exon, the amino acid sequence was much shorter, and there was no canonical DHR-2 domain in DOCK5 variant, which indicated the potential function of DOCK5 variant may be independent of GEF domains. In this study, we found that DOCK5 variant could activate p38 and Erk MAPK pathway in HPV-negative HNSCC. However, more functional studies are needed to define the potential mechanism of DOCK5 variant in regulating HPV-negative HNSCC progression; the identified differentially expressed genes and pathways between higher and lower expression of DOCK5 variant patients in this study may provide some clues toward elucidating the mechanism.

In conclusion, we identified 580 tumor-specific splice variant candidates within HPV-negative HNSCC, including a splice variant of DOCK5, which can promote the proliferation, migration, and invasion of HPV-negative HNSCC cells. These alternative splicing variants will provide a solid foundation for the future exploration of their potential roles in HPV-negative HNSCC, and the functionally relevant DOCK5 variant may be a potential therapeutic target for the treatment of HPV-negative HNSCC.

No potential conflicts of interest were disclosed.

Conception and design: C. Liu, J. Califano

Development of methodology: C. Liu, T. Guo, J. Califano

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): C. Liu, T. Guo, Z. Khan, J. Califano

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): C. Liu, G. Xu, A. Sakai, S. Ren, T. Fukusumi, M. Ando, K.M. Fisch, J. Califano

Writing, review, and/or revision of the manuscript: C. Liu, S. Sadat, K.M. Fisch, J. Califano

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): C. Liu, A. Sakai, S. Ren, S. Sadat, Y. Saito, Z. Khan, J. Califano

Study supervision: C. Liu, T. Guo, G. Xu, A. Sakai, S. Ren, T. Fukusumi, M. Ando, S. Sadat, Y. Saito, Z. Khan, K.M. Fisch, J. Califano

This work has been supported by National Institute of Dental and Craniofacial Research and NIH (R01 DE023347 to J. Califano) and the UC San Diego Clinical and Translational Research Institute Grant (UL1TR001442 to K.M. Fisch).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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