Passenger strand of miR-145-3p acts as a tumor-suppressor by targeting MYO1B in head and neck squamous cell carcinoma.

Analysis of the microRNA (miRNA) expression signature of head and neck squamous cell carcinoma (HNSCC) based on RNA sequencing showed that dual strands of pre‑miR‑145 (miR‑145‑5p, guide strand; and miR‑145‑3p, passenger strand) were significantly reduced in cancer tissues. In miRNA biogenesis, passenger strands of miRNAs are degraded and have no biological activities in cells. The aims of this study were to investigate the functional significance of the passenger strand of miR‑145 and to identify miR‑145‑3p‑regulated oncogenic genes in HNSCC cells. Expression levels of miR‑145‑5p and miR‑145‑3p were significantly downregulated in HNSCC tissues and cell lines (SAS and HSC3 cells). Ectopic expression of miR‑145‑3p inhibited cancer cell proliferation, migration and invasion, similar to miR‑145‑5p, in HNSCC cells. Myosin 1B (MYO1B) was directly regulated by miR‑145‑3p, and knockdown of MYO1B by siRNA inhibited cancer cell aggressiveness. Overexpression of MYO1B was confirmed in HNSCC clinical specimens by analysis of protein and mRNA levels. Interestingly, high expression of MYO1B was associated with poor prognosis in patients with HNSCC by analysis of The Cancer Genome Atlas database (p=0.00452). Our data demonstrated that the passenger strand of miR‑145 acted as an antitumor miRNA through targeting MYO1B in HNSCC cells. The involvement of dual strands of pre‑miR‑145 (miR‑145‑5p and miR‑145‑3p) in the regulation of HNSCC pathogenesis is a novel concept in present RNA research.

Introduction

Head and neck squamous cell carcinoma (HNSCC) occurs from the mucosa in the upper aerodigestive tract, including the oral cavity, oropharynx, hypopharynx and larynx, and this disease is the sixth most common cancer worldwide (1). Approximately 550,000 new patients are diagnosed, and 30,000 patients die of this disease annually (2). Due to the local recurrence and distant metastasis of HNSCC, the overall survival of patients with HNSCC has not improved in the last decade (3). Currently developed targeted molecular therapies are not sufficiently efficacious in the management of HNSCC (3). Therefore, improving our understanding of the molecular mechanisms of HNSCC aggressiveness is needed based on current genomic approaches.

MicroRNAs (miRNAs) are small noncoding RNAs (19–22 nucleotides in length) involved in the repression or degradation of target RNA transcripts in a sequence-dependent manner (4). One of the unique features of miRNAs is that a single miRNA regulates a vast number of protein-coding or noncoding RNAs in human cells (5). Thus, aberrant expression of miRNAs disrupts systematically regulated RNA networks in cancer cells. In fact, accumulating evidence has revealed that aberrant expression of miRNAs is deeply involved in the pathogenesis of human cancers (6).

In miRNA biogenesis, precursor miRNA (pre-miRNA) is cleaved in the cytoplasm, generating a miRNA duplex comprised of a guide strand and passenger strand. The guide strand of miRNA is thought to be incorporated into the RNA-induced silencing complex (RISC) to target mRNAs, whereas the passenger strand of miRNA is degraded and is not thought to have regulatory activity in cells (7). However, in contrast to this paradigm, we demonstrated that passenger strands of miRNAs, i.e., miR-144-5p, miR-139-3p, miR-150-3p and miR-145-3p, were downregulated and acted as antitumor miRNAs in several types of cancers (8–13). Moreover, dual strands of pre-miR-145 (miR-145-5p and miR-145-3p) coordinately target oncogenic MTDH and UHRF1 in lung cancer and bladder cancer, respectively (10,11). The involvement of passenger miRNA strands and regulation of cancer networks by passenger miRNAs are novel concepts in cancer research.

Analysis of the miRNA expression signature of HNSCC by RNA sequencing revealed that miR-145-5p and miR-145-3p were significantly downregulated in cancer tissues. The guide strand miR-145-5p has been established as an oncogene in several cancers, including HNSCC (14). However, the functional significance of the passenger strand of miR-145 in HNSCC is still unknown. The aims of this present study were to investigate the antitumor function of miR-145-3p and to identify its target oncogenic genes in HNSCC cells. Elucidation of the antitumor roles of passenger strands of miRNAs and the cancer networks mediated by these miRNAs may provide insights into the molecular pathogenesis of HNSCC.

Materials and methods

Clinical HNSCC specimens, cell lines, and cell culture

A total of 22 clinical tissue specimens were collected from patients with HNSCC who underwent surgical resection at Chiba university Hospital between 2008 and 2014. The clinicopathological features of patients with HNSCC are summarized in Table I. All patients in this study provided informed consent, and the study protocol was approved by the Institutional Review Board of Chiba University. TNM classification and tumor stage were determined by the union for International Cancer Control (UICC) (15).

Table I

Clinical features of 22 patients with HNSCC.

No.	Age	Sex	Location	T	N	M	Stage	Differentiation
1	64	F	Oral floor	4a	2c	0	IVA	Moderate
2	73	M	Tongue	3	2b	0	IVA	Poor
3	77	M	Tongue	2	2b	0	IVA	Poor
4	63	F	Oral floor	2	2b	0	IVA	Basaloid SCC
5	59	M	Tongue	1	2a	0	IVA	Moderate
6	36	F	Tongue	3	1	0	III	Moderate
7	67	M	Tongue	3	0	0	III	Moderate
8	60	F	Tongue	2	1	0	III	Well
9	66	M	Tongue	2	0	0	II	Moderate
10	67	M	Tongue	2	0	0	II	Poor to moderate
11	76	F	Tongue	1	0	0	I	Well
12	69	M	Tongue	1	0	0	I	Well
13	73	F	Tongue	1	0	0	I	Well
14	64	M	Tongue	1	0	0	I	Well
15	70	M	Tongue	1	0	0	I	Well
16	38	M	Tongue	1	0	0	I	Well
17	51	M	Tongue	1	0	0	I	Well
18	34	F	Tongue	1	0	0	I	Poor
19	70	M	Tongue	1	0	0	I	Moderate
20	71	M	Tongue	1	0	0	I	Well
21	82	M	Oral floor	1	0	0	I	Well
22	81	M	Tongue	1	0	0	I	Extremely well

HNSCC, head and neck squamous cell carcinoma; F, female; M, male; TNM classification and tumor stage were determined by the union for International Cancer Control (UICC).

In this study, we used the following human HNSCC cells: SAS (derived from a primary lesion of tongue squamous cell carcinoma) and HSC3 (derived from human lymph node metastasis of tongue squamous cell carcinoma), as described previously.

Mature miRNA and small interfering RNA (siRNA) transfection into HNSCC cells

The following RNA species were used in this study: mature miRNAs, Pre-miR miRNA Precursors (hsa-miR-145-3p, assay ID: PM 13036; hsa-miR-145-5p, assay ID: PM 11480), negative control miRNA (assay ID: AM 17111) (both from Applied Biosystems, Foster City, CA, USA), siRNA (Stealth Select RNAi siRNA; si-MYO1B P/N: HSS106714 and HSS106716; Invitrogen, Carlsbad, CA, USA). The transfection procedures were described previously (16–20).

Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR)

The procedure for PCR quantification was described previously (16–19). TaqMan probes and primers for MYO1B (P/N: Hs00362654_m1; Applied Biosystems) were assay-on-demand gene expression products. Expression for miR-145-3p (P/N: 002149; Applied Biosystems) and miR-145-5p (P/N: 002278) was used to quantify the expression levels of miRNAs according to the manufacturer's protocol. To normalize the data for quantification of mRNA and miRNAs, we used human GUSB (P/N: Hs99999908_m1), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (P/N: Hs02758991_m1) and RNU48 (assay ID: 001006) (all from Applied Biosystems). The relative expression levels were analyzed using the 2−ΔΔCT method.

Cell proliferation, migration, and invasion assays

Cell proliferation, migration and invasion assays were described previously (16–19).

Incorporation of miR-145-3p or miR-145-5p into the RISC by Ago2 immunoprecipitation

SAS cells were transfected with 10 nM miRNA by reverse transfection. After 48 h, immunoprecipitation was performed using a human Ago2 miRNA isolation kit (Wako, Osaka, Japan) according to the manufacturer's protocol. Expression levels of miR-145-3p or miR-145-5p were measured by qRT-PCR. miRNA data were normalized to the expression of miR-150-5p (P/N: PM10070; Applied Biosystems), which was not affected by miR-145-3p and miR-145-5p transfection.

Western blot analysis

Cells were harvested and lysed 48 h after transfection. Each cell lysate (50 µg of protein) was separated using Mini-PROTEAN TGX gels (Bio-Rad, Hercules, CA, USA) and transferred to polyvinylidene difluoride membranes. Immunoblotting was performed with monoclonal anti-MYO1B antibodies (1:250 dilution; HPA013607; Sigma-Aldrich, St. Louis, MO, USA). Anti-glyceraldehyde 3-phosphate dehydrogenase (GAPDH) antibodies (1:1,000 dilution; ab8245; Abcam, Cambridge, UK) were used as an internal control. The procedures were described in our previous studies (16–19).

Identification of putative genes regulated by miR-145-3p in HNSCC cells

Specific genes regulated by miR-145-3p were identified by a combination of in silico and genome-wide gene expression analyses. Genes regulated by miR-145-3p were listed using the TargetScan database. Oligo microarrays (Human GE 60K; Agilent Technologies) were used for gene expression analyses. The microarray data were deposited into GEO (http://www.ncbi.nlm.nih.gov/geo/), with accession number GSE82108. Upregulated genes in HNSCC were obtained from publicly available data sets in GEO (accession no. GSE9638). To identify signaling pathways regulated in silico, gene expression data were analyzed using the KEGG pathway categories with the GeneCodis program.

Regulation of targets downstream of MYO1B in HNSCC

We investigated pathways regulated by MYO1B in HNSCC cells. We analyzed gene expression using si-MYO1B-transfected SAS cells. Microarray data were used for expression profiling of si-MYO1B transfectants. The microarray data were deposited into GEO (accession no. GSE100746). We analyzed common downregulated genes using the GEO dataset.

Plasmid construction and dual-luciferase reporter assay

The partial wild-type sequence of the MYO1B 3′-untranslated region (3′-UTR) was inserted between the XhoI-PmeI restriction sites in the 3′-UTR of the hRluc gene in the psiCHECK-2 vector (C8021; Promega, Madison, WI, USA). Alternatively, we used sequences that were missing the miR-145-3p target sites (position 88–94 or position 1117–1123). The synthesized DNA was cloned into the psiCHECK-2 vector. SAS cells were transfected with 20 ng of the vector, 20 nM microRNAs, and 1 µl Lipofectamine 2000 in 100 µl Opti-MEM (both from Invitrogen). The procedure of dual-luciferase reporter assay was described previously (16–19).

Immunohistochemistry

Formalin-fixed, paraffin-embedded (FFPE) tissues were used. Tissue sections were incubated overnight at 4°C with anti-MYO1B antibodies diluted 1:300 (HPA013607; Sigma-Aldrich). The procedure for immunohistochemistry was described previously (21).

The Cancer Genome Atlas (TCGA)-HNSCC data analysis

To explore the clinical significance of MYO1B in HNSCC, we used the RNA sequencing database in TCGA (https://tcga-data.nci.nih.gov/tcga/). The gene expression and clinical data were retrieved from cBioportal (http://www.cbioportal.org/, the provisional data downloaded July 1, 2017).

Statistical analysis

Relationships between two or three variables and numerical values were analyzed using Mann-Whitney U tests or Bonferroni-adjusted Mann-Whitney U tests. Spearman's rank tests were used to evaluate the correlations between the expression of miR-145-3p or miR-145-5p and target genes. Expert StatView software (version 5.0; SAS Institute Inc., Cary, NC, USA) was used for these analyses. Multivariate Cox proportional hazard regression models were used to determine independent factors for survival with JMP Pro 13.

Results

Expression levels of miR-145-5p and miR-145-3p in HNSCC clinical specimens and cell lines

To confirm our miRNA expression signatures in HNSCC by RNA sequencing, we validated the expression levels of miR-145-5p and miR-145-3p in HNSCC clinical specimens and cell lines. In Fig. 1, the expression levels of miR-145-5p and miR-145-3p were significantly reduced in cancer tissues compared with those in corresponding adjacent noncancerous epithelium (p<0.0001) (Fig. 1A). Additionally, the expression levels of miR-145-5p and miR-145-3p in SAS and HSC3 cells were markedly downregulated (Fig. 1A).

Figure 1

Antitumor function of miR-145-5p and miR-145-3p in head and neck squamous cell carcinoma (HNSCC) cells. (A) Expression levels of miR-145-5p and miR-145-3p in HNSCC clinical specimens and cell lines. RNU48 was used as an internal control. Spearman's rank test showed a positive correlation between the expression of miR-145-5p and miR-145-3p. *p<0.0001. (B) Cell proliferation was determined by XTT assays 72 h after transfection with miR-145-5p and miR-145-3p. *p<0.0001. (C) Cell migration activity was determined using migration assays. *p<0.0001. (D) Cell invasion activity was determined using Matrigel invasion assays. *p<0.0001.

Spearman's rank test showed a positive correlation between the expression levels of miR-145-5p and miR-145-3p in clinical specimens (Fig. 1A).

Effects of ectopic expression of miR-145-5p and miR-145-3p on cell proliferation, migration and invasion in HNSCC cell lines

To validate the functional roles of miR-145-3p and miR-145-5p, we carried out gain-of-function assays using miRNA transfection into two HNSCC cell lines (SAS and HSC3). XTT assays revealed that cell proliferation was significantly inhibited in miR-145-3p and miR-145-5p transfectants in comparison with mock or miR-control transfectants (Fig. 1B). Similarly, migration assays showed that cell migration activity was significantly inhibited in miR-145-3p and miR-145-5p transfectants in comparison with mock and miR-control transfectants (Fig. 1C). Matrigel invasion assays also demonstrated that cell invasion activity was significantly inhibited in miR-145-3p and miR-145-5p transfectants in comparison with mock and miR-control transfectants (Fig. 1D).

Incorporation of miR-145-3p into the RISC in HNSCC cells

We hypothesized that the passenger strand miR-145-3p may be incorporated into the RISC and exert important effects in cancer cells. Accordingly, we performed immunoprecipitation with antibodies targeting Ago2, which plays an important role in the RISC. After transfection with miR-145-3p or miR-145-5p, Ago2-bound miRNAs were isolated, and qRT-PCR was carried out to determine whether miR-145-3p and miR-145-5p bound to Ago2. After transfection with miR-145-3p and immunoprecipitation by anti-Ago2 antibodies, miR-145-3p levels were significantly higher than those of mock- or miR-control-transfected cells and those of miR-145-5p-transfected SAS cells (p<0.0001) (Fig. 2A). Similarly, after miR-145-5p transfection, miR-145-5p was detected by Ago2 immunoprecipitation (p<0.0001) (Fig. 2B).

Figure 2

Both strands of miR-145-5p and miR-145-3p were incorporated into the RISC. (A and B) Expression levels of miR-145-5p and miR-145-3p after transfection with miR-145-5p or miR-145-3p following immunoprecipitation by Ago2 (*p<0.0001).

Identification of putative targets of miR-145-3p regulation in HNSCC cells

We performed in silico and gene expression analyses to identify genes targeted by miR-145-3p for regulation (Fig. 3). First, we selected putative miR-145-3p target genes using the TargetScan database and identified 3,164 genes. Next, we performed comprehensive gene expression analysis using miR-145-3p transfectants of SAS, with negative control miRNA transfectants serving as controls (accession no. GSE 82108). A total of 1,187 genes were commonly downregulated (log2 ratio<0). The gene set was then analyzed with a publicly available gene expression data set in GEO (accession no. GSE9638), and genes upregulated in HNSCC were chosen (fold-change >1.5). A total of 14 genes were identified as candidate targets of miR-145-3p regulation (Table II). Next, these genes were validated with TCGA database, and we investigated the correlations between survival rates and target genes with high or low expression. In this study, 3 genes (MYO1B, C16orf74 and RBP1) were selected as genes that affected the patient's overall survival (Table II and Fig. 4). Among them, MYO1B was found to have the greatest effect on the overall survival rate (p=0.00452). In this study, we focused on MYO1B as a candidate target gene of miR-145-3p regulation and investigated the functional roles of HNSCC cells.

Figure 3

Flow chart illustrating the analysis strategy for miR-145-3p targets in head and neck squamous cell carcinoma (HNSCC) cells. A total of 3,164 genes were putative target genes of miR-145-3p in TargetScan database analysis (release 7.1). Finally, 14 genes were selected as putative targets of miR-145-3p in HNSCC cells.

Table II

Putative targets of miR-145-3p regulation in HNSCC cells.

Gene symbol	Gene name	Conserved site count	SAS miR-145-3p transfection	HNSCC fold-change	Prognosis (high vs. low) p-value
MYO1B	Myosin IB	2	−1.49	1.72	0.00452
C16orf74	Chromosome 16 open reading frame 74	1	−0.88	1.97	0.014
SP9	Sp9 transcription factor	1	−0.97	2.38	0.0277a
RBP1	Retinol binding protein 1, cellular	1	−1.2	2.6	0.0316
LRRC3	Leucine rich repeat containing 3	2	−0.86	1.54	0.0749
PSPH	Phosphoserine phosphatase	1	−0.8	1.95	0.0804
CDCA7L	Cell division cycle associated 7-like	1	−0.88	1.71	0.107
CBS	Cystathionine-β-synthase	2	−1.29	1.54	0.228
SH2D5	SH2 domain containing 5	1	−1.87	2.34	0.301
PXDN	Peroxidasin homolog (Drosophila)	1	−0.94	1.63	0.317
CYP27B1	Cytochrome P450, family 27, subfamily B, polypeptide 1	2	−0.86	2.65	0.531
TNK2	Tyrosine kinase, non-receptor, 2	1	−1.08	2.3	0.789
ALDH1L2	Aldehyde dehydrogenase 1 family, member L2	1	−1.19	2.3	0.855
CCDC103	Coiled-coil domain containing 103	1	−1.77	2.03	0.986

HNSCC, head and neck squamous cell carcinoma;

poor prognosis with low expression.

Figure 4

The Cancer Genome Atlas (TCGA) database analysis of putative targets of miR-145-3p in head and neck squamous cell carcinoma (HNSCC). Kaplan-Meier plots of overall survival with log-rank tests for 14 genes with high and low expression in the HNSCC TCGA database.

Direct regulation of MYO1B by miR-145-3p in HNSCC cells

Next, we investigated whether the expression of MYO1B decreased in miR-145-3p-transfected HNSCC cells. MYO1B mRNA levels were significantly reduced by miR-145-3p transfection compared with the mock or miR-control transfectants (Fig. 5A). Furthermore, MYO1B protein levels were also reduced by miR-145-3p transfection compared with mock or miR-control transfectants (Fig. 5B). In contrast, miR-145-5p transfectants did not show altered expression of MYO1B mRNA or protein (Fig. 5A and B).

Figure 5

Regulation of myosin 1B (MYO1B) expression by miR-145-3p in head and neck squamous cell carcinoma (HNSCC) cells. (A) Expression levels of MYO1B mRNA 48 h after transfection with 10 nM miR-145-5p or miR-145-3p into cell lines. GUSB was used as an internal control. *p<0.0001. (B) Protein expression of MYO1B 72 h after transfection with miR-145-5p or miR-145-3p. GAPDH was used as a loading control. (C) miR-145-3p binding sites in the 3′-untranslated region (3′-UTR) of MYO1B mRNA. (D) Dual luciferase reporter assays using vectors encoding putative miR-145-3p target sites (positions 88–94 or 1117–1123) in the MYO1B 3′-UTR for both wild-type and deleted regions. Normalized data were calculated as the ratio of Renilla/Firefly luciferase activities. *p<0.0001.

We then carried out luciferase reporter assays with a vector that included the 3′-UTR of MYO1B to confirm that miR-145-3p directly regulated MYO1B in a sequence-dependent manner. TargetScan Human database predicted that there were two binding sites for miR-145-3p in the 3′-UTR of MYO1B (positions 88–94 and 1117–1123) (Fig. 5C). Cotransfection with miR-145-3p and vectors significantly reduced luciferase activity in comparison with those in mock and miR-control transfectants in position 1117–1123 of the MYO1B 3′-UTR (Fig. 5D).

Effects of MYO1B knockdown on cell proliferation, migration, and invasion in HNSCC cell lines

A loss-of-function assay using siRNA was performed to examine the function of MYO1B in HNSCC cell lines. The expression levels of MYO1B mRNA and protein were reduced by si-MYO1B in HNSCC cell lines (Fig. 6A and B). Furthermore, we investigated effects of MYO1B knockdown on cell proliferation, migration, and invasion in HNSCC cell lines. Cancer cell proliferation was significantly reduced in si-MYO1B transfectants in comparison with that in mock- or miR control-transfected cell lines (Fig. 6C). Additionally, migration activities were significantly suppressed in si-MYO1B transfectants in comparison with that in mock- or miR control-transfected cell lines (Fig. 6D). Invasion activity was also significantly inhibited in si-MYO1B transfectants in comparison with that in mock- or miR control-transfected cell lines (Fig. 6E).

Figure 6

Effects of myosin 1B (MYO1B) silencing in head and neck squamous cell carcinoma (HNSCC) cell lines. (A) MYO1B mRNA expression 72 h after transfection with 10 nM si-MYO1B into HNSCC cell lines. GUSB was used as an internal control. *p<0.0001. (B) Protein expression 72 h after transfection with si-MYO1B. GAPDH was used as a loading control. (C) Cell proliferation was determined with XTT assays 72 h after transfection with 10 nM si-MYO1B-1 or si-MYO1B-2. *p<0.0001. (D) Cell migration activity was determined by migration assays. *p<0.0001. (E) Cell invasion activity was determined using Matrigel invasion assays. *p<0.0001.

Expression of MYO1B in HNSCC clinical specimens

Next, we investigated the mRNA expression levels of MYO1B in 22 HNSCC clinical specimens by qRT-PCR. MYO1B was significantly upregulated in HNSCC tumor tissues (Fig. 7A). Spearman's rank test showed a negative correlation between the expression of MYO1B and miR-145-3p (p=0.0025, R=−0.461) (Fig. 7B). Furthermore, we also examined the expression levels of MYO1B in HNSCC clinical specimens by immunostaining. MYO1B was strongly expressed in several cancer tissues (Fig. 7C: 1, patient no. 2; 2, no. 3; 3, no. 7 in Table I).

Figure 7

Expression of myosin 1B (MYO1B) in clinical specimens of head and neck squamous cell carcinoma (HNSCC). (A) Expression levels of MYO1B in HNSCC clinical specimens. GUSB was used as an internal control. *p<0.0001. (B) The negative correlation between MYO1B expression and miR-145-3p (r=−0.461 and p=0.0025). Spearman's rank test was used to evaluate the correlation. (C) Immunostaining showed that MYO1B was strongly expressed in cancer lesions (×100 and ×400 magnification field).

Correlation between MYO1B expression and clinicopathological characteristics in prognostic prediction in HNSCC specimens

We collected clinical data from TCGA database and analyzed clinicopathological factors and expression of MYO1B as a prognostic predictive factor. The multivariate cox proportional hazards model was used to validate independent predictors for overall survival, including MYO1B expression, clinical T stage, clinical N stage, age, sex and histologic grade. As a result, high expression of MYO1B was an independent predictive factor for survival [hazard ratio (HR), 1.68; 95% confidence interval (CI), 1.13–2.49; p=0.01] (Fig. 8).

Figure 8

Multivariate Cox proportional hazard regression models for overall survival. Multivariate Cox proportional hazards model for prediction of overall survival showed that high myosin 1B (MYO1B) expression, cT stage, cN stage, and age were significant prognostic factors (p= 0.01, p= 0.01, p<0.0001 and p=0.03, respectively).

Downstream genes affected by silencing of MYO1B in SAS cells

Finally, we performed genome-wide gene expression analysis using si-MYO1B in SAS cells to investigate which genes were mediated by MYO1B signaling. A SurePrint G3 Human GE 60K v3 microarray was used for genome-wide expression analysis. We submitted the raw data to the GEO database (accession no. GSE100746). In this study, we focused on significantly downregulated genes by both si-MYO1B-1 and si-MYO1B-2 transfection (log2 [si-MYO1B/mock] <−1.5). MYO1B was the most significantly downregulated gene, indicating that the array data were worthy of evaluation. Genes significantly downregulated by silencing of MYO1B are listed in Table III. Among MYO1B downstream genes, expression of 5 genes (ANXA10, TRIM9, TCTN3, BTBD16 and CYP19A1) was significantly associated with poor prognosis in patients with HNSCC based on TCGA database (Fig. 9).

Table III

Identification of MYO1B downstream genes in HNSCC cells.

Gene symbol	Gene name	Log2 (si-MYO1B-1/mock)	Log2 (si-MYO1B-2/mock)	Average Log2 (si-MYO1B/mock)
MYO1B	Myosin IB	−4.007414	−4.668526	−4.337970
ANXA10	Annexin A10	−3.842131	−2.8575826	−3.349857
MATN3	Matrilin 3	−4.224010	−2.0824907	−3.153250
SOHLH1	Spermatogenesis and oogenesis specific basic helix-loop-helix 1	−4.337910	−1.8513346	−3.094622
SMAD1-AS1	SMAD1 antisense RNA 1	−3.191749	−2.902154	−3.046952
KRT6B	Keratin 6B, type II	−3.626921	−2.0426638	−2.834793
KLK13	Kallikrein-related peptidase 13	−3.540325	−1.9546604	−2.747493
PAX6	Paired box 6	−2.130839	−3.0853565	−2.608098
C5orf66-AS1	C5orf66 antisense RNA 1	−2.704701	−2.1148643	−2.409783
PDGFRB	Platelet-derived growth factor receptor, β polypeptide	−2.886416	−1.8465691	−2.366492
HSD17B2	Hydroxysteroid (17-β) dehydrogenase 2	−2.325892	−2.3811436	−2.353518
SP140	SP140 nuclear body protein	−2.470807	−2.1072135	−2.289010
OR9G4	Olfactory receptor, family 9, subfamily G, member 4	−2.296291	−2.1278794	−2.212085
FOXD3-AS1	FOXD3 antisense RNA 1 (head to head)	−1.846461	−2.4128325	−2.129647
MAGEB17	Melanoma antigen family B, 17	−2.394958	−1.7456088	−2.070283
AMDHD1	Amidohydrolase domain containing 1	−2.223687	−1.916799	−2.070243
IGFBP1	Insulin-like growth factor binding protein 1	−2.512259	−1.5926342	−2.052446
MMP1	Matrix metallopeptidase 1 (interstitial collagenase)	−1.821691	−2.2728753	−2.047283
EN1	Engrailed homeobox 1	−1.834606	−2.220468	−2.027537
FGF13-AS1	FGF13 antisense RNA 1	−2.349053	−1.6906263	−2.019840
ZC3H12D	Zinc finger CCCH-type containing 12D	−2.232335	−1.8071643	−2.019749
KRT6A	Keratin 6A, type II	−2.307169	−1.6317264	−1.969448
FAM196B	Family with sequence similarity 196, member B	−1.855253	−2.031945	−1.943599
DNMT3B	DNA (cytosine-5-)-methyltransferase 3β	−1.530055	−2.3343146	−1.932185
LIN28A	Lin-28 homolog A (C. elegans)	−2.292716	−1.5482489	−1.920483
ZNF501	Zinc finger protein 501	−1.788270	−2.042201	−1.915235
REC114	REC114 meiotic recombination protein	−2.230243	−1.5574937	−1.893868
TRIM9	Tripartite motif containing 9	−2.078308	−1.691343	−1.884826
ZBED3-AS1	ZBED3 antisense RNA 1	−2.140241	−1.6105609	−1.875401
PHKA2-AS1	PHKA2 antisense RNA 1	−2.028810	−1.7067645	−1.867787
ZDHHC22	Zinc finger, DHHC-type containing 22	−2.044774	−1.6702744	−1.857524
SCAND2P	SCAN domain containing 2 pseudogene	−1.924617	−1.7586662	−1.841642
SPRR1B	Small proline-rich protein 1B	−1.967544	−1.7028618	−1.835203
SLC35D3	Solute carrier family 35, member D3	−1.638228	−2.0054185	−1.821823
ANO1-AS2	ANO1 antisense RNA 2 (head to head)	−1.763001	−1.8544457	−1.808723
C22orf23	Chromosome 22 open reading frame 23	−1.741993	−1.8479792	−1.794986
TCTN3	Tectonic family member 3	−1.880425	−1.6976513	−1.789038
FAM198A	Family with sequence similarity 198, member A	−1.940336	−1.6032256	−1.771781
TG	Thyroglobulin	−1.719962	−1.8222181	−1.771090
RASGEF1A	RasGEF domain family, member 1A	−1.865154	−1.6762245	−1.770689
KATNAL2	Katanin p60 subunit A-like 2	−1.982902	−1.5259477	−1.754425
KLHL14	Kelch-like family member 14	−1.575037	−1.9020982	−1.738568
NANOS1	Nanos homolog 1 (Drosophila)	−1.785024	−1.6778822	−1.731453
BTBD16	BTB (POZ) domain containing 16	−1.769118	−1.6703396	−1.719729
APOL4	Apolipoprotein L, 4	−1.542360	−1.8804932	−1.711427
ZNF385C	Zinc finger protein 385C	−1.792121	−1.6219425	−1.707032
ABO	ABO blood group	−1.624970	−1.7806495	−1.702810
CD200R1	CD200 receptor 1	−1.778945	−1.5290467	−1.653996
VWA3A	Von Willebrand factor A domain containing 3A	−1.527752	−1.7406074	−1.634180
CYP19A1	Cytochrome P450, family 19, subfamily A, polypeptide 1	−1.572258	−1.6706244	−1.621441
ZNF880	Zinc finger protein 880	−1.604488	−1.6321578	−1.618323
NKX6-2	NK6 homeobox 2	−1.597461	−1.6252115	−1.611336
GPR157	G protein-coupled receptor 157	−1.583724	−1.6133837	−1.598554
ST3GAL5-AS1	ST3GAL5 antisense RNA 1 (head to head)	−1.526179	−1.5542628	−1.540221

Figure 9

The Cancer Genome Atlas (TCGA) database analysis of myosin 1B (MYO1B) downstream genes. Kaplan-Meier survival curve for overall survival with log-rank tests for 5 MYO1B downstream genes with high or low expression. TCGA dataset for head and neck squamous cell carcinoma (HNSCC) was analyzed.

Discussion

Accumulating evidence has shown that aberrant expression of miRNAs disrupts the well-ordered RNA networks in cancer cells and is involved in the pathogenesis of human cancers (22). Based on the miRNA expression signatures of human cancers, we have sequentially identified antitumor miRNAs that regulate novel cancer networks (16,23–26). Analyses of our miRNA signature of HNSCC by RNA sequencing showed that several passenger strands of miRNAs were significantly downregulated in cancer tissues (8). Our recent study demonstrated that both strands of pre-miR-150 (miR-150-5p, guide strand; and miR-150-3p, passenger strand) had antitumor functions and that these miRNAs cooperatively regulated oncogenic ITGA3, ITGA6 and TNC in HNSCC cells (8). Our other studies showed that the passenger strand of miR-150 acted as an anti-tumor miRNA in several types of cancers, such as esophageal cancer and prostate cancer (9,27). These findings suggested that miRNA passenger strands also contribute substantially to cancer pathogenesis and that identification of RNA networks mediated by miRNA passenger strands may provide novel insights into the pathogenesis of HNSCC.

Based on our miRNA signature of HNSCC, we focused on the passenger strand miR-145-3p in this study. Similarly, miR-145-5p, the guide strand of miR-145, was significantly reduced in this signature. Downregulation of miR-145-5p is frequently observed in many types of cancer, and prior studies have confirmed the antitumor function of miR-145-5p by demonstration of its effects on several types of oncogenes in cancer cells (10,11). Several studies have shown that downregulation of miR-145-5p is caused by hypermethylation of the promoter region of pre-miR-145 in prostate cancer (28). Importantly, the tumor suppressor p53 has been shown to directly bind p53-response elements in the promoter region of pre-miR-145 and to control the expression of miR-145-5p (29). p53 mutations are found in >50% of patients with HNSCC (30). Thus, downregulation of miR-145-5p and miR-145-3p may be dependent on p53 inactivation in cancer cells.

Expression levels of passenger strand of miR-145-3p was lower than miR-145-5p as a guide strand miRNA in HNSCC clinical specimens and cell lines. Our previous studies of bladder, lung, and prostate cancers showed that expression levels of miR-145-3p was lower than miR-145-5p in each cancer (10,11,31). The results of the present data of HNSCC was similar to our previous data. Explanation is incomplete as to in what kind of molecular mechanisms the expression of the two miRNAs differ. This problem is an important issue in miRNA biosynthesis.

Our functional assays showed that miR-145-3p had antitumor functions similar to miR-145-5p in HNSCC cells. We have also demonstrated miR-145-3p is downregulated in cancer tissues and acts as an antitumor miRNA in bladder, lung, and prostate cancers by targeting several oncogenic genes (10,11,31). Previous studies demonstrated that several oncogenic genes were regulated by miR-145-5p in several types of cancers (32–34). There are few studies for target genes by miR-145-3p regulation in cancer cells, including HNSCC cells. Thus, we evaluated miR-145-3p regulatory oncogenic networks in HNSCC cells; a total of 14 putative targets of miR-145-3p in HNSCC cells were identified in this study. Among these candidates, MYO1B, C16orf74, SP9 and RBP1 were found to be associated with poor prognosis in patients with HNSCC by TCGA data analyses.

In this study, we focused on MYO1B because high expression of MYO1B was strongly associated with poor prognosis in patients with HNSCC. Myosins are actin-associated molecular motor proteins that regulate membrane tension, anchor membrane proteins and organelles, and transport inter-cellular vesicles (35,36). We have demonstrated that antitumor miRNAs inhibited cancer cell migration and invasion through targeting several actin-binding proteins and actin-associate proteins, e.g., FSCN1, LASP1, ARPC5 and ANLN (37–40). Overexpression of these proteins has been detected in cancer tissues and has been shown to contribute to cancer cell aggressiveness.

Our present data of restoration of miR-145-5p or miR-145-3p showed the inhibition of cancer cell proliferation. However, inhibition of cell proliferation was weak by knockdown of MYO1B in HNSCC cells. These data suggest that miR-145-5p or miR-145-3p inhibite cell proliferation genes and pathways which do not rely on MYO1B in HNSCC cells.

MYO1B belongs to a member of the membrane-associated class I myosin family and functions as a linker between membranes and the actin cytoskeleton in several cellular processes (41). Previous studies have demonstrated other functions of MYO1B. For example, MYO1B is localized in the endocytotic compartment and has pivotal roles in endocytosis (42). MYO1B couples with the actin assembly to organelles and controls membrane remodeling at the trans-Golgi network (43). In cancer cells, MYO1B is highly expressed in PC-3 metastatic prostate cancer cells, and knockdown of MYO1B affects the cytoskeleton and cell migration (44). Another study showed that knockdown of MYO1B significantly inhibits migratory and invasive abilities of HNSCC cells in vitro and in vivo (35). Our present data confirmed these findings and suggested that MYO1B may be an effective target for the treatment of HNSCC.

To identify MYO1B-mediated HNSCC pathways, we performed genome-wide gene expression analyses using si-MYO1B transfectants. A total of 54 genes were found to be mediated by MYO1B in HNSCC. Among them, 5 genes (ANXA10, TRIM9, TCTN3, BTBD16 and CYP19A1) were significantly associated with poor prognosis in patients with HNSCC by TCGA database analyses. Annexin family proteins are calcium-dependent phospholipid-binding proteins that regulate cell growth and signal transduction (45). Overexpression of ANXA10 has been reported in oral squamous cell carcinoma, and expression of ANXA10 promotes cancer cell proliferation through regulating mitogen-activated protein kinase signaling pathways (46). Exploration of novel MYO1B-mediated pathways may improve our understanding of the aggressiveness of this disease.

In conclusion, downregulation of miR-145-3p was observed in HNSCC clinical specimens, and this passenger strand acted as an antitumor miRNA through targeting MYO1B in HNSCC cells. MYO1B was highly expressed in HNSCC clinical specimens and was found to promote cancer aggressiveness in functional assays. Elucidation of the pathways mediated by the miR-145-3p/MYO1B axis is expected to contribute to further analyses of oncogenesis mechanisms and treatment strategies in HNSCC.