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m6A modification suppresses ocular melanoma through modulating HINT2 mRNA translation

Molecular Cancer volume 18, Article number: 161 (2019) Cite this article

Abstract

Background

Dynamic N6-methyladenosine (m6A) RNA modification generated and erased by N6-methyltransferases and demethylases regulates gene expression, alternative splicing and cell fate. Ocular melanoma, comprising uveal melanoma (UM) and conjunctival melanoma (CM), is the most common primary eye tumor in adults and the 2nd most common melanoma. However, the functional role of m6A modification in ocular melanoma remains unclear.

Methods

m6A assays and survival analysis were used to explore decreased global m6A levels, indicating a late stage of ocular melanoma and a poor prognosis. Multiomic analysis of miCLIP-seq, RNA-seq and Label-free MS data revealed that m6A RNA modification posttranscriptionally promoted HINT2 expression. RNA immunoprecipitation (RIP)-qPCR and dual luciferase assays revealed that HINT2 mRNA specifically interacted with YTHDF1. Furthermore, polysome profiling analysis indicated a greater amount of HINT2 mRNA in the translation pool in ocular melanoma cells with higher m6A methylation.

Results

Here, we show that RNA methylation significantly inhibits the progression of UM and CM. Ocular melanoma samples showed decreased m6A levels, indicating a poor prognosis. Changes in global m6A modification were highly associated with tumor progression in vitro and in vivo. Mechanistically, YTHDF1 promoted the translation of methylated HINT2 mRNA, a tumor suppressor in ocular melanoma.

Conclusions

Our work uncovers a critical function for m6A methylation in ocular melanoma and provides additional insight into the understanding of m6A modification.

Background

N6-Methyladenosine (m6A), the most prevalent modification in mRNA [1, 2], is a dynamic RNA modification installed by “writer” methyltransferase-like 3 (METTL3), methyltransferase-like 14 (METTL14) and Wilms tumor associated protein (WTAP) [3,4,5]; erased by “eraser” fat-mass and obesity-associated protein (FTO) and α-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5) [6, 7]; and recognized by “readers”. Dynamic m6A modification affects a variety of cellular processes, such as RNA stability, export, splicing or translation [2]. For instance, m6A modification promotes the degradation of Notch1a mRNA in the earliest hematopoietic progenitor cells [3] while promoting the translation of immediate-early genes in long-term memory [8]. Therefore, m6A RNA modifications have attracted increasing attention in the pathogenesis of human disease.

As m6A modifications play a key role in the maintenance of homeostasis, aberrant m6A modifications may be an important inducer of tumorigenesis [2]. Disturbance of m6A modifications was reported to contribute to the tumorigenesis of glioblastoma, breast cancer and hepatocellular carcinoma [9]. For example, decreased METTL3 expression or METTL14 mutation in endometrial cancer reduces the m6A modification of AKT pathway-related genes, resulting in the activation of the AKT signaling pathway and contributing to tumorigenesis [10]. In addition, FTO erases m6A modification of tumor suppressor genes MYC/CEBPA, which contributes to the tumor formation of leukemia. Therapeutically, R-2-hydroxyglutarate inhibits the activity of FTO, thereby suppressing leukemia progression. Thus, exploration of the novel m6A RNA methylation drivers of tumorigenesis is potentially interesting.

Ocular melanoma, including uveal melanoma (UM) and conjunctival melanoma (CM), is the most common primary eye tumor in adults and the 2nd most common melanoma, with a high rate of recurrence and poor prognosis [11,12,13]. The loss of one copy of chromosome 3 has been frequently identified in ocular melanoma. Previous studies have revealed that mutations in G protein subunit alpha Q (GNAQ) or G protein subunit alpha 11 (GNA11) result in the promotion of cell proliferation and sensitize cells to mitogen-activated protein kinase (MAPK) inhibitors. Furthermore, epigenetic drivers, such as DNA methylation, histone modifications, microRNAs and lncRNAs, also participate in tumorigenesis of ocular melanoma [14,15,16]. For instance, lncRNA ROR serves as a decoy oncoRNA that blocks G9a (a key enzyme of histone methylation) binding to the surfaces of target DNA, thereby promoting UM tumorigenesis, while lncRNA CASC15-New-Transcript 1 (CANT1) inhibits UM progression by simultaneously activating other lncRNAs, JPX and FTX. However, the functional role of dynamic tuning of m6A in ocular melanoma tumorigenesis remains unclear.

We thus aimed to identify the functional role of m6A methylation in malignant ocular melanoma and reveal its potential mechanism in tumorigenesis. We show that m6A methylation significantly inhibits the progression of ocular melanoma cells. Mechanistically, m6A methylation recognized by YTH N6-methyladenosine RNA binding protein 1 (YTHDF1) promotes translation of histidine triad nucleotide-binding protein 2 (HINT2), a tumor suppressor in ocular melanoma. Our study reveals the functional importance of RNA m6A methylation and thereby presents a novel dynamic mechanism of m6A RNA modifications.

Methods

Patient samples

A total of 88 human ocular melanoma tissues and 28 human normal melanocyte tissues were collected for immunofluorescence (IF) from patients of Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine from 2007 to 2017. The histological features of all specimens were evaluated by pathologists according to the standard criteria, and the clinic pathological characteristics of ocular melanoma patients are listed in Additional file 2: Table S2 and Additional file 3: Table S3.

m6A RNA methylation assay

Total RNA was extracted from samples using an EZ-press RNA Purification Kit (B0004). The change in m6A level relative to total mRNA was measured using the m6A RNA Methylation Quantification Kit (Colorimetric) (ab185912) following the manufacturer’s protocol. Each sample was analyzed using 200 ng of RNA isolated from different cells.

Cell lines

The PIG1 human normal melanocyte cell line was kindly provided by the Department of Ophthalmology, Peking University Third Hospital. The human ocular melanoma cell lines, OCM1, OCM1a and OM431, were kindly supplied by Professor John F. Marshall (Tumor Biology Laboratory, Cancer Research UK Clinical Center, John Vane Science Centre, London, UK). The human conjunctival melanoma cell lines, CRMM1 and CM2005.1, were kindly supplied by Prof. Martine J. Jager (Leiden University Medical Center, Leiden, The Netherlands). The HEK293T human embryonic kidney cell line was purchased from the American Type Culture Collection (Manassas, VA, USA). The cell lines used in this study were authenticated by STR profiling.

Cell culture

Human OCM1, OCM1a, OM431 and HEK293T cells were cultured in DMEM (GIBCO). PIG1 and CM2005.1 cells were cultured in RPMI 1640 medium (GIBCO). CRMM1 cells were cultured in Ham’s F-12 K (Kaighn’s) Medium (GIBCO). All mediums are supplemented with 10% certified heat-inactivated fetal bovine serum (FBS; GIBCO), penicillin (100 U/mL), and streptomycin (100 mg/mL) and cells are all cultured at 37 °C in a humidified 5% CO2 atmosphere.

RNA isolation and quantitative real-time PCR

Total RNA was extracted from samples using the EZ-press RNA Purification Kit (B0004), and cDNA was generated using the PrimeScript RT Reagent Kit (Takara). Quantitative real-time PCR using Powerup SYBR Green PCR Master Mix (Life Technologies) was performed using a real-time PCR system (Applied Biosystems).

Western blot analysis

Cells were harvested at the indicated times and rinsed three times with PBS. Cell extracts were prepared with lysis buffer and centrifuged at 13,000 xg for 30 min at 4 °C. Protein samples were separated by 7.5% (wt/vol) sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene fluoride membranes. After blocking with 5% milk for 1 h at room temperature, the membrane was incubated with 2.5 μg/mL of antibody in 5% BSA overnight at 4 °C. The membrane was then incubated with a secondary antibody conjugated to a fluorescent tag (Invitrogen). The band signals were visualized and quantified using the Odyssey Infrared Imaging System (LI-COR, USA).

Plasmid construction

pLKO.1, pCDH and pCMV were used in our study. ShRNA sequences were generated by PCR and then cloned into the pLKO.1 vector. The HINT2 overexpression cassette was generated by PCR and cloned into the pCDH vector and verified by DNA sequencing. The YTHDF1 overexpression cassette was generated by PCR and cloned into the pCMV vector and verified by DNA sequencing.

Lentivirus packaging and generation of stable cell lines

Lipofectamine 3000 reagent (Invitrogen) was incubated with Opti-MEM I Reduced Serum Medium (GIBCO), and HEK239T cells were transfected with 3 mg of plasmid or 6.0 mg of the PsPax plasmid. Eight hours after transfection, the medium was replaced with 10 mL of fresh medium. The supernatant containing the viruses was collected at 48 and 72 h, filtered through a 0.45-mm cellulose acetate filter and used immediately. Viruses carrying a given plasmid were premixed 1:1, and 50 μL of virus was added to 1 mL of serum. Twenty-four hours prior to transfection, tumor cells were seeded at 2.0 × 105 cells per well in a 6-cm dish, and the medium was replaced with virus-containing supernatant supplemented with 10 ng/mL polybrene (Sigma-Aldrich). After 48 h, the medium was replaced with fresh medium. Cells were selected by incubation with 4 mg/mL puromycin (InvivoGen) for 2 weeks and maintained in 1 mg/mL puromycin (InvivoGen).

Cell proliferation/growth assays

Cell proliferation/growth was assessed by CCK8 assays (HY-K0301, MCE) following the manufacturer’s instructions. Briefly, cells were seeded in triplicate in 96-well plates at a density of 2000–10,000 cells/100 mL. Dye solution was added at the indicated time points, and the plates were incubated at 37 °C for 3–4 h before the absorbance was detected at 570 nm.

Apoptosis assays

FITC-Annexin V Apoptosis Detection Kit 1 (BD Biosciences, San Diego, CA) was used following the manufacturer’s instructions. Briefly, cells were washed twice with cold PBS, stained with FITC-Annexin V and PI on ice for 5 min, and subjected to flow cytometric analysis using a BD LSRFortessa analyzer (BD Biosciences).

Colony formation assay

A volume of 1 mL of complete medium containing 1000 cells was placed in each well of a six-well plate. The plate was stained with 0.25% crystal violet after 1–2 weeks.

Transwell assay

A 24-well transwell system (Corning) with polycarbonate filters (8-μm pores, Corning) was used. The upper compartment contained 10,000 cells suspended in the appropriate medium with 2% FBS; the lower chamber contained 10% FBS. After 1 day of incubation at 37 °C, the cells in the transwell system were stained with 0.25% crystal violet. The cells remaining in the upper transwell chamber were removed, and those that migrated to the lower chamber were photographed and counted.

Cell cycle analysis

A sample of approximately 106 cells was centrifuged at 800 xg for 4 min, washed twice with PBS, resuspended in 1 mL of PBS and fixed in 75% ethanol overnight at − 20 °C. The fixed cells were washed three times with 10 mL of ice-cold PBS, resuspended in 200–400 mL of PBS containing 10 mL of RNase (Qiagen) and incubated at 37 °C for 30 min in the dark. The cells were then subjected to FACS at the Flow Cytometry Facility.

RNA extraction, library construction, Illumina sequencing (RNA-seq) and data analysis

Total RNA was extracted from samples using the EZ-press RNA Purification Kit (B0004). We confirmed the integrity of the RNA using the 2100 Bioanalyzer (Agilent Technologies, USA) and measured the RNA concentration using a Qubit 2.0 fluorometer with a Qubit RNA Assay Kit (Life Technologies, Carlsbad, CA, USA). We then prepared libraries from 100 ng of total RNA using the Illumina TruSeq RNA Sample Prep Kit (San Diego, CA, USA) following the manufacturer’s protocol.

Methylated RNA immunoprecipitation sequencing (MeRIP-seq)

MeRIP was performed as previously described [17]. Briefly, purified mRNA was randomly fragmented to approximately 100 nucleotides using Ambion RNA fragmentation reagents and then subjected to IP with an anti-m6A antibody (202,003, Synaptic Systems) and protein A magnetic beads (88,845, Pierce) in MeRIP buffer (150 mM NaCl, 10 mM Tris-HCl, pH 7.4, 0.1% NP-40) supplemented with RNase inhibitor. m6A-containing mRNA fragments were eluted with m6A in MeRIP buffer and purified using TRIzol reagent. For MeRIP-seq, two sets of samples were collected for duplicate biological repeats. For MeRIP-qRT-PCR, the same procedures were followed, except that the purified mRNA was fragmented to approximately 200 nucleotides; three biological repeats were conducted. The samples were sequenced with an Illumina HiSeq 4000 platform.

Cross-linking and methylated RNA immunoprecipitation (miCLIP) -SMARTer-m6A-seq

Small-scale, single base-resolution m6A methylome detection was carried out following procedures modified from a previous report. Briefly, 100 ng of mRNA was isolated from the tumor (OCM1, OCM1a, OM431, CRMM1 and CM2005.1) and normal (PIG1) cell lines using the Dynabeads mRNA Purification Kit (Life Technologies, 61,006), fragmented to ~ 100 nucleotides using fragmentation reagent (Life Technologies, AM8740), and incubated with 5 μg of an anti-m6A antibody (Abcam, ab151230) in 450 μL of IP buffer (50 mM Tris, 100 mM NaCl, 0.05% NP-40, adjusted to pH 7.4) under gentle rotation at 4 °C for 2 h. The mixture was transferred to a clear flat-bottom 96-well plate (Corning) on ice and irradiated three times with 0.15 J/cm2 at 254 nm using a CL-1000 Ultraviolet Crosslinker (UVP). After irradiation, the mixture was collected and incubated with 50 μL of prewashed Dynabeads Protein A (Life Technologies, 1001D) at 4 °C for 2 h. After extensive washing twice with high-salt buffer (50 mM Tris, 1 M NaCl, 1 mM EDTA, 1% NP-40, 0.1% SDS, adjusted to pH 7.4) and twice with IP buffer, the samples on the beads were subjected to dephosphorylation with T4 PNK (NEB, M0201 L) at 37 °C for 20 min. The RNA was then eluted from the beads by proteinase K (Sigma, P2308) treatment at 55 °C for 1 h, followed by phenol-chloroform extraction and ethanol precipitation. The purified RNA was subjected to library construction using the SMARTer smRNA-Seq Kit for Illumina (Clontech Laboratories, 635,030) according to the manufacturer’s instructions and sequenced using the Illumina HiSeq X Ten platform.

RNA-binding protein immunoprecipitation (RIP)-qPCR

To examine m6A modification or RNA-binding proteins on individual genes, the Magna RIP™ Quad RNA-Binding Protein Immunoprecipitation Kit (17–704, Millipore, Billerica, MA) was used according to the manufacturer’s instructions. Briefly, 200 mg of total RNA was enriched with antibody- or rabbit IgG-conjugated Protein A/G Magnetic Beads in 500 mL of 1x IP buffer supplemented with RNase inhibitors at 4 °C overnight. RNA of interest was immunoprecipitated with the beads. One-tenth of each fragmented RNA sample was saved as the input control and further analyzed by qPCR.

Sequencing data analysis

For all untreated tumor and normal cell lines, RNA-seq generated paired-end reads with a length of 151 bp, and MeRIP-seq generated single-end reads with a length of 151 bp. Cutadapt software (version 1.18) [18] was used to trim off the adapter sequences for all raw reads. Reads that contained an ambiguous nucleotide or with lengths less than 18 nt were discarded by Trimmomatic (version 0.36) [19].

The remaining reads were aligned to the human genome (version hg19) using Hisat2 (version 2.1.0) [20]. Only uniquely mapped reads with a mapping quality score ≥ 20 were kept for the subsequent analysis for each sample.

For MeRIP-seq, MACS2 software (version 2.0.10) [21] was used for m6A peak calling in each MeRIP sample with the corresponding input sample serving as a control. The default options expected for ‘-nomodel, -keep-dul all’ to turn off fragment size estimation and to keep all uniquely mapped reads in MACS2 were set. Software BEDTools’ intersectBed (version 2.27.1) [22] was used to annotate each peak on the Ensembl (release 72) gene annotation information.

For RNA-seq, the number of reads mapped to each Ensembl (release 72) gene was counted using the software featureCounts (version 1.6.3) [23] from Subread package. FeatureCounts was applied with default options expect for ‘-s 2, -p’ to inform strand-specific library construction and fragment counting for paired-end reads.

Statistical analysis of differentially expressed genes and genes with differential protein levels

Differentially expressed genes between normal (PIG1) and tumor (OCM1, OCM1a, OM431, CRMM1 and CM2005.1) cell lines were determined using the R-package DEseq2 [24]. Transcripts with a fold change cutoff > 1.5 or < − 1.5 and a p-value cutoff < 0.05 were considered significantly differentially expressed genes. Genes with differential protein levels were also determined with the same cutoffs as above.

Gene ontology analysis

Gene Ontology (GO) analysis of specific genes was performed using DAVID (http://david.abcc. ncifcrf.gov/). GO terms with P < 0.05 were statistically significant. Enrichment maps (Fig. 3e, Fig. 4b) were constructed using Cytoscape 3.7.0 installed with the Enrichment Map plugin. Within the enrichment maps, each node represents a GO pathway, and the node size is proportional to the total number of genes in each pathway. The edge thickness represents the number of overlapping genes between nodes. GO pathways of similar functions are sorted into one group, marked with labels and cycles. The number of genes in each cluster is labeled [3].

Analysis of miCLIP sequencing data

As previously reported [25], raw read preprocessing was performed. Fastx_clipper from fastx_toolkit (http://hannonlab.cshl.edu/fastx_toolkit) was used to trim off the adapter sequence of the raw reads. Fastq_filter.pl, a Perl script from the CLIP Tool Kit (CTK) [26] was used to filter out the low-quality bases, and reads with lengths shorter than 18 nt were discarded. We processed the paired-end data according to the previously reported approach [25] with the same criteria. For individual replicates, we demultiplexed the forward reads based on 5′ barcodes by performing fastq2 collapse to remove PCR-amplified reads, and we reverse complemented the reverse reads and processed them in the same way as the forward counterparts. Finally, stripBarcode.pl was performed to strip the random barcodes of the remaining reads and move to read headers for subsequent analysis processed by the CIMS pipeline.

BWA software (version 0.7.10) [27] was used to map the remaining reads to the human genome (version hg19), and an error rate (substitutions, insertions, or deletions) of ≤0.06 per read was allowed by setting parameter ‘bwa aln –n 0.06 –q20’, following the CTK Online Documentation (https://zhanglab.c2b2.columbia.edu/index.php/CTK_Documentation). The mode of mutation calling was performed as previously reported with minor modifications [28] to identify the m6A locus. Program CIMS.pl [29] was used to determine the coverage of the tag number (k) and mutations (m) for each mutation position. The mutation position with m > 1, m/k ≥ 0.01 and m/k ≤ 0.5 were kept, and only mutation positions within the RRACH motif were determined as m6A for the subsequent analysis to remove the potential m6Am modification [28, 30].

Motif identification within m6A peaks

m6A peaks were identified by extending 25 nt both downstream and upstream of the m6A sites. The motifs enriched in m6A peaks were analyzed by HOMER (version 4.10.3) [31]. Motif length was restricted to 5 nucleotides. The nearby peaks were merged to one peak by performing BEDTools’ merge (version 2.27.1) [22]. These peaks were used as target sequences, and background sequences were constructed by randomly shuffling peaks onto total mRNAs in the genome using BEDTools’ shuffleBed (version 2.27.1) [22].

Immunofluorescence (IF)

Cells adhering to a glass slide were fixed with 4% formaldehyde (Fisher) for 15 min and then blocked with 5% normal goat serum (Vector) with or without 0.1% Triton X-100 in PBS for 60 min at room temperature. Immunostaining was performed using the appropriate primary and secondary antibodies. Nuclei and the cytoskeleton were counterstained with DAPI and phalloidin, respectively. IF staining was performed with the appropriate Alexa Fluor 488 or Alexa Fluor 546 secondary antibody (Invitrogen, 1:1000 dilution). Images were taken with a ZEISS Axio Scope A1 Upright Microscope.

RNA pull-down

Biotin-labeled ssRNA probes were synthesized in vitro by Sangon Biotin (Shanghai) Co., Ltd. In vitro RNA-protein pull-down assay were performed using Pierce™ Magnetic RNA-Protein Pull-Down Kit (Thermo Scientific, 20,164) according to the manufacturer’s instructions. The cell lysate was prepared using standard lysis buffers (Thermo Scientific Pierce IP Lysis Buffer) as suggested. 100 pmol of RNA and 50 μL of magnetic beads were used per sample. Input RNA of each sample was mixed with 1 μl 50% glycerol, separated on the 8% native 1x TBE gel, and visualized by phosphorimaging using the Personal Molecular Imager (Bio-Rad) [32,33,34,35,36,37].

Luciferase reporter assay

Cells seeded in 6-well plates were transfected with the psiCHECK.2-based luciferase vector fused or not fused to the wild-type or mutated HINT2–3’UTR. Transfection efficiency was quantified by cotransfection with an actin promoter-driven Renilla luciferase reporter. The activities of firefly and Renilla luciferase in each well were calculated using a dual luciferase reporter assay system (Promega). The relative luciferase activity of the HINT2–3’UTR plasmid was further normalized to the signal in cells transfected with the firefly luciferase vector control under the same treatment conditions.

Polysome profiling

We followed previously reported protocols (https://www.jove.com/pdf/51455/jove-protocol-51455-polysome-fractionation-analysis-mammalian-translatomes-on-genome-wide) with the following modifications. Before collection, 0.1 mg/mL cycloheximide (CHX) was added to the culture medium for 5 min. A sample of 150 million cells from each group was harvested, rinsed in cold PBS with 0.1 mg/mL CHX and quickly frozen in liquid nitrogen before lysis. The lysis buffer was formulated as 10 mM Tris-HCl (pH 7.5), 100 mM NaCl, 30 mM MgCl2, and 0.1 mg/mL CHX with freshly added 1:100 protease inhibitor (Roche) and 40 U/mL SUPERase in RNase Inhibitor (Ambion). The sample was homogenized using a liquid nitrogen grinder. We chose a linear 10 to 40% sucrose gradient according to cell type, and the sample was fractionated into 23 fractions (0.5 mL per fraction) and analyzed using a Gradient Station (BioCamp) equipped with an ECONOUV monitor (BioRad, Hercules, CA) and a Gilson FC203B fraction collector (Mandel Scientific, Guelph, Canada). RNA was purified from fractions 5–22 and subjected to qPCR analysis.

Mice and animal housing

The animal experiments were approved by the Shanghai Jiao Tong University Animal Care and Use Committee and conducted in accordance with the animal policies of Shanghai JiaoTong University and the guidelines established by the National Health and Family Planning Commission of China. Cells were harvested by trypsinization and washed twice with PBS (GIBCO). BALB/c nude mice (male, 6 weeks old) were used for the study.

Tumorigenesis assay in vivo

Approximately 1 × 106 melanoma cells from each group were injected subcutaneously into the right side of the abdomen of BALB/c nude mice (male, 6 weeks old). At 30 days after cell injection, the mice were humanely killed, and the tumors were harvested. Each tumor was fixed in 4% formaldehyde, embedded in paraffin, and examined for tumor formation by histologic analysis of hematoxylin and eosin (H&E)-stained sections. Tumor volume was calculated by the formula V = ab2/2, where a and b are tumor length and width, respectively.

Immunohistochemistry (IHC)

Tissue slides were deparaffinized and rehydrated through an alcohol series, followed by antigen retrieval with sodium citrate buffer. Tumor sections were blocked with 5% normal goat serum (Vector) with 0.1% Triton X-100 and 3% H2O2 in PBS for 60 min at room temperature and then incubated with appropriate primary antibodies at 4 °C overnight. IHC was performed with horseradish peroxidase (HRP) conjugates using DAB detection.

Results

Decreased m6A in ocular melanoma

To study the functional role of m6A methylation in malignant ocular melanoma, we first examined the global m6A level in ocular melanoma relative to normal control samples. A significant decrease in m6A modification in cellular mRNAs was observed in tumor samples (p < 0.001) (Fig. 1a; Additional file 1: Table S1). Notably, the expression of the known m6A “writer” METTL3 was also decreased in ocular melanoma tissue compared to normal melanocyte tissue (p < 0.05) (Fig. 1b; Additional file 2: Table S2; Additional file 3: Table S3), while the opposite trend was observed for m6A “eraser” ALKBH5 (p < 0.01) (Fig. 1c; Additional file 2: Table S2; Additional file 3: Table S3). Thus, the decreased m6A level in ocular melanoma cells (Fig. 1a) is likely due to the downregulation of METTL3 and upregulation of ALKBH5. Furthermore, lower expression of METTL3 predicted earlier recurrence and enhanced aggressiveness (log rank test, p < 0.05) (Fig. 1d, e, Additional file 2: Table S2; Additional file 3: Table S3). Similarly, elevated ALKBH5 expression indicated a poor prognosis (log rank test, p < 0.05) (Fig. 1f, g, Additional file 2: Table S2; Additional file 3: Table S3), suggesting that a reduced global m6A level predicts higher malignancy. Consistently, we also observed decreased m6A modification in ocular melanoma cells (Fig. 1h). Accordingly, decreased METTL3 and upregulated ALKBH5 were observed in ocular melanoma cells (Fig. 1i). These data indicate that a large portion of ocular melanoma is characterized by decreased m6A modification, either through decreased METTL3 expression or increased ALKBH5 expression.

Fig. 1
figure 1

Ocular melanoma exhibited decreased m6A levels, which was associated with poor prognosis. a An m6A RNA methylation assay revealed the m6A content in tumor and adjacent normal tissues. For ocular melanoma, n = 10, for normal melanocyte, n = 4, ***p < 0.001. b, c METTL3 and ALKBH5 expression in normal and tumor tissues. B: METTL3 and ALKBH5 expression according to IF analysis. Scale bar: left panel, 100 μm; right panel, 20 μm. C: Statistical results of METTL3 and ALKBH5 expression in normal and tumor tissues. *p < 0.05, ***p < 0.001. d Kaplan-Meier curves of tumor recurrence showing the difference between ocular melanoma patients with low and high METTL3 levels. n = 54, log rank test, p < 0.05. e The expression of METTL3 in patients at AJCC stages T1 to T4. f Kaplan-Meier curves of tumor recurrence showing the difference between ocular melanoma patients with low and high ALKBH5 levels. n = 55, log rank test, p < 0.05. g The expression of ALKBH5 in patients at AJCC stages T1 to T4. h The m6A RNA methylation assay revealed the m6A content in PIG1 cells and ocular melanoma cells. Error bars indicate the mean ± SEM, n = 3, *p < 0.05. i Western blot showing METTL3 and ALKBH5 expression in normal melanocytes and orbital melanoma cells. The METTL3 signal was quantified and normalized to that of β-actin

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m6A methylation inhibits ocular melanoma

To evaluate whether the global m6A level is related to tumorigenesis in ocular melanoma, we first inhibited the expression of methyltransferase METTL3 in normal pigmented cells and ocular melanoma cells. The METTL3 expression level decreased to ~ 30% of the original level in normal control cells, PIG1 (Additional file 4: Figure S1A-B), and the global m6A level decreased when METTL3 was knocked down (Additional file 4: Figure S1C), as expected. After silencing METTL3, normal melanocyte cells formed an enlarged colony (Fig. 2a, b) with increased growth (Additional file 4: Figure S1D), reduced apoptosis (Additional file 4: Figure S1E), and an increased population in S phase, indicating faster cell division (Additional file 4: Figure S1F). Furthermore, genome-wide gene set enrichment analysis (GSEA) indicated that lower global m6A methylation promotes tumorigenesis and identified major regulations of METTL3 (Fig. 2c). Similarly, we silenced the expression of methyltransferase METTL3 in ocular melanoma. OCM1 and CRMM1 cells were transfected with the same METTL3 shRNA, and METTL3 expression levels were successfully knocked down to ~ 20% of the original levels (Additional file 5: Figure S2A-B). Next, we evaluated changes in proliferation and tumorigenesis and found that the colony formation rate increased to almost 200% in melanoma cells with lower m6A methylation (Additional file 5: Figure S2C-D). Melanoma cells with METTL3 knockdown also displayed significantly greater migratory ability (Additional file 5: Figure S2E-F) and slightly accelerated cell growth (Additional file 5: Figure S2G-H).

Fig. 2
figure 2

m6A methylation inhibited ocular melanoma tumorigenesis. a A colony formation assay was performed to assess the tumor growth of PIG1 cells with or without METTL3 knockdown. b Statistics of visible colonies in colony formation assays performed using PIG1 cells with or without METTL3 knockdown. The colony number of the control group was set to 1. All of the experiments were performed in triplicate, and relative colony formation rates are shown as the mean ± SEM. n = 3, ***p < 0.001. c GSEA plots evaluating the changes in apoptosis, cell differentiation and cell death in normal melanocyte cells with or without METTL3 knockdown. NES, normalized enrichment score. d A colony formation assay was performed to assess the tumor growth of ocular melanoma cells with or without ALKBH5 knockdown. e Statistics of visible colonies in colony formation assays performed using ocular melanoma cells with or without ALKBH5 knockdown. The colony number of the control group was set to 1. All of the experiments were performed in triplicate, and relative colony formation rates are shown as the mean ± SEM. n = 3, **p < 0.01. f A transwell assay was performed to evaluate the migratory ability of ocular melanoma cells with or without ALKBH5 knockdown. g Statistics of cells in the transwell assay performed using ocular melanoma cells with or without ALKBH5 knockdown. The value obtained for the control group was set to 1. All of the experiments were performed in triplicate, and relative metastasis rates are shown as the mean ± SEM. n = 3, *p < 0.05, **p < 0.01. h GSEA plots evaluating the changes in apoptosis, cell differentiation and cell death in ocular melanoma cells with or without ALKBH5 knockdown. NES, normalized enrichment score

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Because tumor cells present decreased m6A modifications, we next inhibited the expression of the demethylase ALKBH5. CRISPR/Cas9 is utilized to delete ALKBH5 in OCM1 and CRMM1 cells (Additional file 6: Figure S3A), and m6A methylation increases significantly when ALKBH5 is knocked down (Additional file 6: Figure S3B). Moreover, the rate of colony formation decreased to 20% in melanoma cells with higher m6A methylation (Fig. 2d, e), and these cells showed a significantly weaker migratory ability (Fig. 2f, g). Compared with control cells, ocular melanoma cells with higher m6A methylation exhibited significantly decreased tumor growth (Additional file 6: Figure S3C) as more cells underwent apoptosis (Additional file 6: Figure S3D) and fewer cells underwent cell division (Additional file 6: Figure S3E). Genome-wide RNA-seq and GSEA of ocular melanoma cells further demonstrated these antitumor effects of higher m6A modification levels and identified major target gene clusters of ALKBH5 (Fig. 2h).

Transcriptome-wide m6A-Seq and RNA-seq assays to identify potential m6A-mediated targets

To understand the regulatory role of m6A modification in gene expression, we mapped the m6A sites of normal and ocular melanoma cells by MeRIP-seq and m6A individual-nucleotide-resolution cross-linking and immunoprecipitation with sequencing (miCLIP-seq), with two independent biological replicates (Additional file 7: Figure S4A). An average of 13,083 and 11,750 m6A peaks were identified from miCLIP-seq libraries generated from normal and tumor cells (Additional file 7: Figure S4B). Consistent with previous m6A-seq results [3, 4], the m6A peaks we identified were characterized by the canonical RRACH motif (Fig. 3a; Additional file 7: Figure S4C) and were enriched in the 3′ UTR, especially near the stop codons (Fig. 3b, c; Additional file 7: Figure S4D-F). Although the motif and the pattern of m6A distribution were observed similarly in all cells, we found that the m6A modifications were reduced globally in tumor cells compared to normal control cells (Additional file 7: Figure S4G) and that there were more genes with only one m6A site in normal cells among the detected m6A peaks (Fig. 3d). In total, we identified 5828 genes with significant m6A modifications (Additional file 7: Figure S4E). In these genes, terms of cell proliferation and cell death were significantly enriched (Fig. 3e). Moreover, HIF-1 and p53 signaling pathway were significantly enriched to be regulated (Fig. 3f), suggesting a regulation role of m6A modification in tumorigenesis.

Fig. 3
figure 3

Dynamic m6A modifications were highly associated with ocular melanoma tumorigenesis. a Top enriched motifs within m6A peaks identified in ocular melanoma and normal cells. b Distribution of m6A sites along the length of mRNA transcripts. c Pie charts showing the m6A peak distribution in different RNA regions (CDS, 5′ UTR, 3′ UTR and stop codon) in ocular melanoma and normal cells. d The percentage of methylated genes with 1, 2, 3, 4 or more than 5 peaks per gene in each cell line. e GO enrichment map of m6A-containing genes in ocular melanoma and normal cells. f KEGG pathway analysis of m6A-modified genes in ocular melanoma and normal cells

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In detail, the number of transcripts with greater enriched m6A modifications in normal cells was more than 5 times higher than that in tumor cells (Fig. 4a). These transcripts participate in several signaling pathways related to cell proliferation and tumorigenesis (Fig. 4b, Additional file 8: Figure S5A).

Fig. 4
figure 4

Transcriptome-wide identification of m6A targets that regulate tumorigenesis. a Volcano plots showing m6A enrichment of genes in normal and tumor cells. b GO enrichment map of genes with specific enriched m6A peaks in control normal cells. c Schematic of m6A modification downstream analysis. In normal cells, RNA-seq detected 5714 genes with differential expression in which 3506 genes were upregulated and 2208 genes were downregulated. m6A-miCLIP-seq showed that 2826 genes were differentially methylated. In normal cells, 2357 genes were up-methylated, and 469 genes were down-methylated. Protein quantification analysis revealed 1003 genes with differential protein levels in normal cells: 478 genes had upregulated protein levels, and 525 genes had downregulated protein levels. In the group of genes with higher m6A levels, 254 genes were upregulated, and 159 genes were downregulated. However, 2241 genes with m6A methylation levels showed no expression change in normal cells. Finally, we found that 237 genes also had differential m6A levels with differential protein levels. The cutoffs used for differentially expressed genes, differential methylation levels and genes with differential protein levels were FC < − 1.5 or FC > 1.5 and p < 0.05. FC: fold change, p: p-value. d Representative GO biological process categories enriched in genes with significant differences in m6A enrichment and protein content but not gene expression. e Volcano plots showing the m6A enrichment and protein content of genes in normal cells compared to tumor cells. f IGV tracks displaying the miCLIP-seq reads coverage of HINT2 in normal and tumor cells

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To systematically illuminate gene expression changes resulting from the decreased m6A modification in ocular melanoma, we used RNA sequencing to compare the transcriptome between normal and tumor cells. Since m6A modifications play a key role in the modulation of translation [2], we associatively analyzed the protein expression of genes and, as expected, many genes with m6A modifications were inconsistent between mRNA expression and protein expression (Fig. 4c, third panel; Additional file 12: Table S4), suggesting a potential posttranscriptional modulation of translation of m6A modifications. Consistently, these genes are involved in the cell cycle, cell adhesion and protein processes (Fig. 4d). HINT2, one of the genes with most significant evaluated protein expression and m6A enrichment in normal cells, was chosen as a typical example for analyzing the mechanism of m6A modifications acting as translation modulators in tumorigenesis (Fig. 4e, Additional file 8: Figure S5C). From our miCLIP-seq data, we identified a statistically significant m6A peak in HINT2 mRNA on the 3’UTR, which was especially enriched in normal cells (Fig. 4f). To confirm our results, we verified decreased m6A modifications of HINT2 mRNA, downregulated expression of HINT2 protein, and unnoticeably altered mRNA levels by RNA-binding protein immunoprecipitation (RIP)-qPCR, Western blotting and qPCR (Additional file 10: Figure S6A-C).

HINT2 suppresses ocular melanoma in an m6A-dependent manner

HINT2 has been reported to act as a tumor suppressor in hepatocellular carcinoma and pancreatic cancer [38, 39], and we confirmed its function in ocular melanoma. We overexpressed HINT2 in ocular melanoma cells at both the mRNA (Additional file 10: Figure S6D) and protein (Additional file 10: Figure S6E) levels. Notably, cell proliferation (Additional file 10: Figure S6F), cell migration (Additional file 10: Figure S6G-H) and colony formation (Additional file 10: Figure S6I-J) were significantly inhibited and apoptosis was increased (Additional file 10: Figure S6K) in ocular melanoma cells upon HINT2 overexpression. In addition, GSEA showed that HINT2 promoted apoptosis and cell death in tumor cells (Fig. 5a). To determine the role of HINT2 in tumor characteristics in vivo, we performed subcutaneous transplantation of ocular melanoma cells with different treatments. We thus tested the tumor suppression role of HINT2 by overexpressing HINT2. In the HINT2-overexpressing group (Fig. 5b, Group B) compared with the empty vector group (Fig. 5b, Group A), we found that tumor volume was persistently reduced (p < 0.01), meeting the changes created by increased global m6A modification (Fig. 5b, Group C). To investigate whether these variations in protein expression occur in samples, we performed IF staining in ocular melanoma and normal tissue and found that HINT2 was indeed downregulated in tumor samples (p < 0.001) (Fig. 5c, d). Notably, lower HINT2 expression in ocular melanoma tissue samples was highly correlated with a poor prognosis (log rank test, p < 0.05) (Fig. 5e, f; Additional file 2: Table S2; Additional file 3: Table S3).

Fig. 5
figure 5

HINT2 acted as a tumor suppressor gene in ocular melanoma cells. a GSEA plots evaluating the changes in autophagy, mitochondrial function, apoptosis and cell death in ocular melanoma cells with or without HINT2 overexpression. NES, normalized enrichment score. b The animal experiment shows tumor suppressor roles of ALKBH5 and HINT2 in vivo. Top: The line graph shows the volume of subcutaneous tumors formed by the indicated OCM1 cells. Bottom: representative images of H&E staining to evaluate tumor formation. n = 5, **p < 0.01; scale bar: 5 mm. c, d HINT2 expression in normal and tumor tissues. C: HINT2 expression according to IF analysis. Scale bar: top panel, 100 μm; bottom panel, 20 μm. D: Statistical results of HINT2 expression in normal and tumor tissues. n = 105, ***p < 0.001. e Kaplan-Meier curves of tumor recurrence showing the difference between ocular melanoma patients with low and high HINT2 levels. n = 54, log rank test, p < 0.05. f The expression of HINT2 in patients at AJCC stages T1 to T4

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Because HINT2 restrains cell growth and migration in ocular melanoma and shows reduced m6A methylation in tumors compared to normal cells, we hypothesized that decreased m6A modification might restrain tumor growth partially through upregulating HINT2 expression. The m6A status of HINT2 mRNA was further measured by MeRIP of fragmented RNA, and the m6A peak on the 3’UTR was specifically methylated by METTL3 and demethylated by ALKBH5, suggesting functional relevance (Fig. 6a, b). In addition, HINT2 protein expression (Fig. 6c, d, Left), rather than mRNA expression (Fig. 6c, d, Right; Additional file 11 Figure S7A), was decreased when METTL3 was knocked down, while it was upregulated when ALKBH5 was knocked down, indicating that HINT2 translation is positively regulated by its m6A modifications. To determine if reduced HINT2 expression underlies the decreased proliferation observed upon enhancing m6A modification in ocular melanoma, we attempted to rescue this phenotype by inhibiting HINT2 expression in upregulated m6A cells (Fig. 6e, lanes 3,4). HINT2 knockdown in ALKBH5 knockdown cells promoted cell proliferation (Fig. 6f, lanes 3, 4, 6G-H). Importantly, the cell proliferation rates of ALKBH5 knockdown cells after HINT2 knockdown were only partially comparable to those of the control cells with normal ALKBH5 expression (Fig. 6f, lanes 1,4, 6G-H), suggesting that there are more tumor-related genes regulated by their m6A modifications. Collectively, m6A-guided tumor inhibition partially results from the posttranscriptional regulation of HINT2.

Fig. 6
figure 6

HINT2 protein expression was regulated by m6A modification. a Reduction in m6A modification in specific regions of HINT2 transcripts upon METTL3 knockdown, as assessed by gene-specific m6A-RIP-qPCR assays, in PIG1, OCM1 and CRMM1 cells. The value obtained for the control group was set to 1. Error bars indicate the mean ± SEM, n = 3, *p < 0.05, **p < 0.01. b Reduction in m6A modification in specific regions of HINT2 transcripts upon ALKBH5 knockdown, as assessed by gene-specific m6A-RIP-qPCR assays, in OCM1 and CRMM1 cells. The value obtained for the control group was set to 1. Error bars indicate the mean ± SEM, n = 3, *p < 0.05, **p < 0.01. c, d Western blot (Left) and real-time PCR (Right) showing HINT2 expression in PIG1 cells with or without METTL3 knockdown (c) and in OCM1 and CRMM1 cells with or without ALKBH5 knockdown (d). The HINT2 signal was quantified and normalized to that of β-actin. Error bars indicate the mean ± SEM, n = 3. e HINT2 expression in OCM1 and CRMM1 cells with or without ALKBH5 knockdown and with or without HINT2 knockdown. f A colony formation assay was performed to assess the tumor growth of OCM1 and CRMM1 cells with or without ALKBH5 knockdown and with or without HINT2 knockdown. g Statistical analysis of the colony formation assay performed using OCM1 and CRMM1 cells with or without ALKBH5 knockdown and with or without HINT2 knockdown. The colony number in the control group was set to 1. All of the experiments were performed in triplicate, and relative colony formation rates are shown as the mean ± SEM. n = 3, **p < 0.01, ***p < 0.001. h Proliferation of OCM1 and CRMM1 cells with or without ALKBH5 knockdown and with or without HINT2 knockdown, as determined by CCK8 assays. n = 3, ∗∗p < 0.01

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m6A modification promotes HINT2 translation

Because m6A methylation appears to promote the translation of HINT2, we hypothesized that HINT2 transcripts are targets of the YTH family, the m6A reader that regulates translation of m6A modified transcripts [40]. RIP-qPCR analysis revealed that HINT2 mRNAs interacted with YTHDF1 more strongly than the others (Fig. 7a). In addition, RNA pull-down assays further confirmed that YTHDF1 interacted with HINT2 mRNA and that the m6A modification of HINT2 greatly facilitated its binding to YTHDF1 (Fig. 7b, c, Additional file 15: Table S5). Consistently, YTHDF1 knockdown (Fig. 7d line 1, Additional file 11: Figure S7B) decreased HINT2 protein expression (Fig. 7d line 2), while YTHDF1 overexpression (Fig. 7e, f line 1, Additional file 11: Figure S7C-D) increased HINT2 protein expression (Fig. 7e-F line2). These changes in HINT2 expression are not due to changes in the abundance of the HINT2 transcript (Fig. 7d-f, Bottom); rather, the regulation of mRNA translation relies on the methylation of transcripts. We created reporter constructs with HINT2 3′ UTR (WT) or m6A locus mutated (MT) sequences (Additional file 15: Table S5), and dual luciferase assays showed that ALKBH5 significantly decreased the luciferase activity of reporters carrying the wild-type fragment instead of the corresponding mutant fragment (Fig. 7g). In detail, the association of the HINT2 transcript with actively transcribing ribosomes was improved by its m6A modifications (Fig. 7h, Additional file 11: Figure S7E). Altogether, these experiments reveal that m6A modification has an impact on the translation of HINT2 when recognized by YTHDF1.

Fig. 7
figure 7

YTHDF1 promoted HINT2 translation. a Reduction in m6A modification at specific regions of HINT2 transcripts, as assessed by gene-specific YTHDF1, YTHDF2 and YTHDF3 RIP-qPCR assays, in PIG1 cells. The value obtained for the IgG was set to 1. Error bars indicate the mean ± SEM, n = 3, **p < 0.01. b Model showing RNA probes used in RNA pull-down assays. c RNA pulldown of endogenous YTHDF1 proteins from HEK293T nuclear extract using synthetic HINT2 RNA fragments with or without m6A modifications. Images are representative of 3 independent experiments. d Western blotting (Top) and real-time PCR (Bottom) were performed to elucidate HINT2 expression in PIG1 cells with or without YTHDF1 knockdown. The HINT2 and YTHDF1 signals were quantified and normalized to that of GAPDH. Error bars indicate the mean ± SEM, n = 3. e, f Western blotting (Top) and real-time PCR (Bottom) were performed to elucidate HINT2 expression in PIG1 cells with or without YTHDF1 overexpression. The HINT2 and YTHDF1 signals were quantified and normalized to that of GAPDH. Error bars indicate the mean ± SEM, n = 3. g Dual luciferase reporter assays showing the effect of ALKBH5 on HINT2 mRNA reporters with either wild-type or mutated m6A sites. Error bars indicate the mean ± SEM, n = 3, ***p < 0.001. h Polysome profiling assays. The fractionation of lysates from PIG1 cells with or without METTL3 knockdown is shown on the top. RNAs in different ribosome fractions were extracted and subjected to qPCR analysis; data are shown on the bottom as the mean ± SD. n = 3, *p < 0.05; **p < 0.01; ***p < 0.001. i Model showing how reduced m6A methylation alters HINT2 translation to contribute to tumor progression

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Discussion

Here, we discovered that m6A mRNA methylation regulates the translation of the tumor suppressor gene HINT2 and thereby regulates ocular melanoma tumorigenesis (Fig. 7i). One-third of mRNAs are m6A modified, which may regulate mRNA stability and translation [2]. A previous study discovered that the “writers” of m6A methylation, METTL3 and METTL14, could play both oncogenic and tumor suppressor roles in numerous cancers [40, 41], while oncogenic roles have been reported for “erasers” such as FTO and ALKBH5 [7, 42, 43]. Here, we found that the decreased global m6A modification in ocular melanoma promoted tumorigenesis, which resulted from decreased “writers” and upregulated “erasers”. Our study indicates that the disturbance of global m6A homeostasis is a key driver in the regulation of tumor formation, which depends on the balance of “writers” and “erasers” of m6A modification.

Notably, the balance of “writers” and “erasers” regulates clusters of gene function, and the AKT pathway is one of the most important targets regulated by m6A modifications. The expression of some key genes of the AKT pathway, such as PHLPP2, PTEN, Bcl2 and c-Myc, has been reported to be regulated by their m6A modifications. These modifications can be written by METTL3 or METTL14 and can be erased by ALKBH5 and regulate the tumorigenesis of leukemia, pancreatic cancer, endometrial cancer and gastric cancer [10, 30, 44,45,46]. Although we did not find a significant regulation of the AKT pathway by m6A modifications in ocular melanoma, genes in other biological processes, such as mRNA processing, translation, Hippo-YAP signaling and MAPK signaling, were differentially expressed (Fig. 4b, Additional file 8: Figure S5A-C). These signaling pathways have been reported to be involved in m6A targets in colorectal cancer and lung cancer and in the inflammatory response [47,48,49]. Other tumor-related genes, such as ACAT2, PIR and CTBP1, were potentially regulated by m6A modifications in ocular melanoma. Further studies should be performed to understand m6A modification systematically.

Notably, the regulation mechanisms of m6A modifications are complicated, reflected not only in multitudinous targets but also in different regulations in various cells. It should be noted that the key enzyme of m6A modification may have opposite effects on tumorigenesis in different systems, even within one specific type of tumor. For example, Somasundaram et al. found that METTL3 acts as an oncogene that promotes tumorigenesis, glioblastoma stem cell maintenance, and radio resistance by regulating SRY-Box 2 (SOX2) [50], whereas Shi et al. reported opposite effects, including inhibition of tumorigenesis and glioblastoma stem cell self-renewal/ proliferation via regulation of ADAM metallopeptidase domain 19 (ADAM19) [43]. METTL14 inhibits tumor invasion and metastasis by regulating miR-126 [51] while promoting tumor cell proliferation and migration by regulating suppressor of cytokine signaling 2 (SOCS2) [41]. In addition, the key enzyme of m6A modification could also be involved in other non-m6A modification activities. For example, METTL3 and YTH N6-methyladenosine RNA binding protein 3 (YTHDF3) directly regulate translation by cooperating with eukaryotic translation initiation factor 3 (eIF3), independent of m6A [52, 53]. Future systematic studies could focus on the detailed mechanism of m6A-related proteins regulating tumor fate.

m6A-modified RNA recognized by different readers could present with different functions. For instance, YTHDF1 mediates nuclear export and translation [10, 54], YTH N6-methyladenosine RNA binding protein 2 (YTHDF2) regulates mRNA stability with m6A [10, 55] and RNA structural remodeling [33], and YT521-B regulates sex-specific alternative splicing and subcellular localization of mRNAs with m6A [56, 57]. Here, we revealed for the first time that the m6A modification of HINT2 is recognized by YTHDF1. Further study could concentrate on the oncogenic role of other readers, such as YTHDF2/3, in regulating tumor formation of ocular melanoma.

HINT2 is a member of the superfamily of histidine triad AMP-lysine hydrolase proteins, which are closely associated with mitochondrial metabolism and tumor suppression [58]. HINT2 has been reported to expedite Ca2+ influx into mitochondria from the cytoplasm, which is a hallmark of the mitochondrial apoptosis pathway and an essential condition for early apoptosis [58]. Loss of HINT2 disturbs mitochondrial lipid metabolism, glucose homeostasis and mitochondrial deformity [59]. As a tumor suppressor gene, HINT2 is downregulated in pancreatic cancer and hepatocellular cancer, endometrial cancer and colorectal cancer, preventing the mitochondrial apoptosis pathway and leading to poor survival [38, 39, 60, 61]. Here, we revealed for the first time that HINT2 is regulated by m6A modification, indicating that disturbances in RNA methylation homeostasis result in dysregulation of proliferation and mitochondrial apoptosis, which contributes to the progression of ocular melanoma. Notably, we found that knockdown of HINT2 only partially rescued the effect of knockdown of ALKBH5 on ocular melanoma cells, which indicates that there are other cofactors involved in tumorigenesis that are regulated by m6A modifications.

Uveal melanoma is the most common adult intraocular tumor, with a 5-year survival rate ranging from 71 to 76% [11]. Additionally, more than half of patients develop metastasis after 5 years [11], and the median survival time for metastatic UM is only 12 months [62]. Conjunctival melanoma is also a rare but lethal cancer; nearly 30% of patients die within 10 years [63]. Although B-raf mutations are rare in UM, activation changes in other MAPK pathway components, such as GNAQ or GNA11, are found in 85–95% of patients and are partly responsible for tumorigenesis [64, 65]. In CM, the B-raf mutation is present in up to 50% of patients [66]. Ocular melanoma cells with the activated MAPK pathway have been reported to be modestly sensitive to MAPK/ERK kinase (MEK) inhibitors with or without combination treatment with the protein kinase C (PKC) inhibitor [67]. Unfortunately, PKC targeting is limited by toxicity, and a completed phase 3 trial showed no clinical benefit [68]. To date, structure-based selective inhibitors of the m6A key enzyme have been discovered [69, 70]. These drugs provide a novel pathway for targeted therapy of ocular melanoma.

Conclusion

In general, we revealed the critical role of m6A modification in ocular melanoma tumorigenesis. Decreased m6A levels are identified in ocular melanoma samples, indicating poor prognosis, and changes in global m6A modification are highly associated with tumor progression. Mechanistically, YTHDF1 promotes the translation of methylated mRNA of HINT2, a tumor suppressor in ocular melanoma. Our work uncovers a critical function of m6A methylation in ocular melanoma and provides insight into the understanding of m6A modification.

Availability of data and materials

The raw sequence data reported in this paper, including RNA-seq, miCLIP-seq and MeRIP-seq data, have been deposited in the Gene Expression Omnibus database under accession number GSE137675, and also the Genome Sequence Archive [71] in the BIG Data Center [72], Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession number CRA001675 (http://bigd.big.ac.cn/gsa/s/n110138p) and are publicly accessible at http://bigd.big.ac.cn/gsa.

Abbreviations

ADAM19:

ADAM metallopeptidase domain 19

ALKBH5:

α-ketoglutarate-dependent dioxygenase alkB homolog 5

CANT1:

LncRNA CASC15-New-Transcript 1

CM:

Conjunctival melanoma

eIF3:

Eukaryotic translation initiation factor 3

FTO:

Fat-mass and obesity-associated protein

GNA11:

G protein subunit alpha 11

GNAQ:

G protein subunit alpha Q

GSEA:

Genome-wide gene set enrichment analysis

HINT2:

Histidine triad nucleotide-binding protein 2

m1A:

N1-methyladenosine

m5C:

N5-methylcytosine

m6A:

N6-methyladenosine

m6Am:

N6,2′-O-dimethyladenosine

MAPK:

Mitogen-activated protein kinase

MEK:

MAPK/ERK kinase

MeRIP-seq:

methylated RNA immunoprecipitation sequencing

METTL14:

Methyltransferase-like 14

METTL3:

Methyltransferase-like 3

miCLIP-seq:

m6A individual-nucleotide-resolution cross-linking and immunoprecipitation with sequencing

PKC:

Protein kinase C

RIP:

RNA-binding protein immunoprecipitation

SOCS2:

Suppressor of cytokine signaling 2

SOX2:

SRY-box 2

UM:

Uveal melanoma

UTR:

Untranslated region

WTAP:

Wilms tumor associated protein

YTHDF1:

YTH N6-methyladenosine RNA binding protein 1

YTHDF2:

YTH N6-methyladenosine RNA binding protein 2

YTHDF3:

YTH N6-methyladenosine RNA binding protein 3

References

  1. Roundtree IA, Evans ME, Pan T, He C. Dynamic RNA modifications in gene expression regulation. Cell. 2017;169:1187–200.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Yang Y, Hsu PJ, Chen YS, Yang YG. Dynamic transcriptomic m6A decoration: writers, erasers, readers and functions in RNA metabolism. Cell Res. 2018;28:616–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Zhang C, Chen Y, Sun B, Wang L, Yang Y, Ma D, Lv J, Heng J, Ding Y, Xue Y, et al. m6A modulates haematopoietic stem and progenitor cell specification. Nature. 2017;549:273–6.

    Article  CAS  PubMed  Google Scholar 

  4. Weng H, Huang H, Wu H, Qin X, Zhao BS, Dong L, Shi H, Skibbe J, Shen C, Hu C, et al. METTL14 inhibits hematopoietic stem/progenitor differentiation and promotes Leukemogenesis via mRNA m6A modification. Cell Stem Cell. 2018;22:191–205 e199.

    Article  CAS  PubMed  Google Scholar 

  5. Agarwala SD, Blitzblau HG, Hochwagen A, Fink GR. RNA methylation by the MIS complex regulates a cell fate decision in yeast. PLoS Genet. 2012;8:e1002732.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Jia G, Fu Y, Zhao X, Dai Q, Zheng G, Yang Y, Yi C, Lindahl T, Pan T, Yang YG, He C. N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat Chem Biol. 2011;7:885–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Zhang S, Zhao BS, Zhou A, Lin K, Zheng S, Lu Z, Chen Y, Sulman EP, Xie K, Bogler O, et al. m6A Demethylase ALKBH5 maintains Tumorigenicity of Glioblastoma stem-like cells by sustaining FOXM1 expression and cell proliferation program. Cancer Cell. 2017;31:591–606 e596.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Zhang Z, Wang M, Xie D, Huang Z, Zhang L, Yang Y, Ma D, Li W, Zhou Q, Yang YG, Wang XJ. METTL3-mediated N6-methyladenosine mRNA modification enhances long-term memory consolidation. Cell Res. 2018;28:1050–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wang S, Chai P, Jia R, Jia R. Novel insights on m6A RNA methylation in tumorigenesis: a double-edged sword. Mol Cancer. 2018;17:101.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Liu J, Eckert MA, Harada BT, Liu SM, Lu Z, Yu K, Tienda SM, Chryplewicz A, Zhu AC, Yang Y, et al. m6A mRNA methylation regulates AKT activity to promote the proliferation and tumorigenicity of endometrial cancer. Nat Cell Biol. 2018;20:1074–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kujala E, Makitie T, Kivela T. Very long-term prognosis of patients with malignant uveal melanoma. Invest Ophthalmol Vis Sci. 2003;44:4651–9.

    Article  PubMed  Google Scholar 

  12. Shields CL, Markowitz JS, Belinsky I, Schwartzstein H, George NS, Lally SE, Mashayekhi A, Shields JA. Conjunctival melanoma: outcomes based on tumor origin in 382 consecutive cases. Ophthalmology. 2011;118:389–95 e381–382.

    Article  PubMed  Google Scholar 

  13. Shields CL. Conjunctival melanoma: risk factors for recurrence, exenteration, metastasis, and death in 150 consecutive patients. Trans Am Ophthalmol Soc. 2000;98:471–92.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Larsen AC. Conjunctival malignant melanoma in Denmark. Epidemiology, treatment and prognosis with special emphasis on tumorigenesis and genetic profile. Acta Ophthalmol. 2016;94:842.

    Article  PubMed  Google Scholar 

  15. Xing Y, Wen X, Ding X, Fan J, Chai P, Jia R, Ge S, Qian G, Zhang H, Fan X. CANT1 lncRNA triggers efficient therapeutic efficacy by correcting aberrant lncing Cascade in malignant Uveal melanoma. Mol Ther. 2017;25:1209–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sharma A, Stei MM, Frohlich H, Holz FG, Loeffler KU, Herwig-Carl MC. Genetic and epigenetic insights into uveal melanoma. Clin Genet. 2018;93:952–61.

    Article  CAS  PubMed  Google Scholar 

  17. Dominissini D, Moshitch-Moshkovitz S, Salmon-Divon M, Amariglio N, Rechavi G. Transcriptome-wide mapping of N6-methyladenosine by m6A-seq based on immunocapturing and massively parallel sequencing. Nat Protoc. 2013;8:176–89.

    Article  CAS  PubMed  Google Scholar 

  18. Martin M. Cutadapt removes adapter sequences from high-thoughout sequencing reads. EMBnet J. 2011;17:10.

    Article  Google Scholar 

  19. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015;12:357–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9:R137.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26:841–2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Liao Y, Smyth GK, Shi W. Feature counts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30:923–30.

    Article  CAS  PubMed  Google Scholar 

  24. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Moore MJ, Zhang C, Gantman EC, Mele A, Darnell JC, Darnell RB. Mapping Argonaute and conventional RNA-binding protein interactions with RNA at single-nucleotide resolution using HITS-CLIP and CIMS analysis. Nat Protoc. 2014;9:263–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Shah A, Qian Y, Weyn-Vanhentenryck SM, Zhang C. CLIP tool kit (CTK): a flexible and robust pipeline to analyze CLIP sequencing data. Bioinformatics. 2017;33:566–7.

    CAS  PubMed  Google Scholar 

  27. Li H, Durbin R. Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics. 2009;25:1754–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Linder B, Grozhik AV, Olarerin-George AO, Meydan C, Mason CE, Jaffrey SR. Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nat Methods. 2015;12:767–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Weyn-Vanhentenryck SM, Mele A, Yan Q, Sun S, Farny N, Zhang Z, Xue C, Herre M, Silver PA, Zhang MQ, et al. HITS-CLIP and integrative modeling define the Rbfox splicing-regulatory network linked to brain development and autism. Cell Rep. 2014;6:1139–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Vu LP, Pickering BF, Cheng Y, Zaccara S, Nguyen D, Minuesa G, Chou T, Chow A, Saletore Y, MacKay M, et al. The N6-methyladenosine (m6A)-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells. Nat Med. 2017;23:1369–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38:576–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Wang Z, Yang B, Zhang M, Guo W, Wu Z, Wang Y, Jia L, Li S, Cancer genome atlas research N, Xie W, Yang D: LncRNA epigenetic landscape analysis identifies EPIC1 as an oncogenic lncRNA that interacts with MYC and promotes cell-cycle progression in Cancer. Cancer Cell 2018, 33:706–720 e709.

  33. Liu N, Dai Q, Zheng G, He C, Parisien M, Pan T. N6-methyladenosine-dependent RNA structural switches regulate RNA-protein interactions. Nature. 2015;518:560–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Hsu PJ, Zhu Y, Ma H, Guo Y, Shi X, Liu Y, Qi M, Lu Z, Shi H, Wang J, et al. Ythdc2 is an N6-methyladenosine binding protein that regulates mammalian spermatogenesis. Cell Res. 2017;27:1115–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Yang X, Yang Y, Sun BF, Chen YS, Xu JW, Lai WY, Li A, Wang X, Bhattarai DP, Xiao W, et al. 5-methylcytosine promotes mRNA export - NSUN2 as the methyltransferase and ALYREF as an m5C reader. Cell Res. 2017;27:606–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Huang H, Weng H, Sun W, Qin X, Shi H, Wu H, Zhao BS, Mesquita A, Liu C, Yuan CL, et al. Recognition of RNA N6-methyladenosine by IGF2BP proteins enhances mRNA stability and translation. Nat Cell Biol. 2018;20:285–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Lence T, Akhtar J, Bayer M, Schmid K, Spindler L, Ho CH, Kreim N, Andrade-Navarro MA, Poeck B, Helm M, Roignant JY. m6A modulates neuronal functions and sex determination in Drosophila. Nature. 2016;540:242–7.

    Article  CAS  PubMed  Google Scholar 

  38. Chen L, Sun Q, Zhou D, Song W, Yang Q, Ju B, Zhang L, Xie H, Zhou L, Hu Z, et al. HINT2 triggers mitochondrial Ca2+ influx by regulating the mitochondrial Ca2+ uniporter (MCU) complex and enhances gemcitabine apoptotic effect in pancreatic cancer. Cancer Lett. 2017;411:106–16.

    Article  CAS  PubMed  Google Scholar 

  39. Martin J, Magnino F, Schmidt K, Piguet AC, Lee JS, Semela D, St-Pierre MV, Ziemiecki A, Cassio D, Brenner C, et al. HINT2, a mitochondrial apoptotic sensitizer down-regulated in hepatocellular carcinoma. Gastroenterology. 2006;130:2179–88.

    Article  CAS  PubMed  Google Scholar 

  40. Barbieri I, Tzelepis K, Pandolfini L, Shi J, Millan-Zambrano G, Robson SC, Aspris D, Migliori V, Bannister AJ, Han N, et al. Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control. Nature. 2017;552:126–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Chen M, Wei L, Law CT, Tsang FH, Shen J, Cheng CL, Tsang LH, Ho DW, Chiu DK, Lee JM, et al. RNA N6-methyladenosine methyltransferase-like 3 promotes liver cancer progression through YTHDF2-dependent posttranscriptional silencing of SOCS2. Hepatology. 2018;67:2254–70.

    Article  CAS  PubMed  Google Scholar 

  42. Li Z, Weng H, Su R, Weng X, Zuo Z, Li C, Huang H, Nachtergaele S, Dong L, Hu C, et al. FTO plays an oncogenic role in acute myeloid leukemia as a N6-Methyladenosine RNA Demethylase. Cancer Cell. 2017;31:127–41.

    Article  PubMed  CAS  Google Scholar 

  43. Cui Q, Shi H, Ye P, Li L, Qu Q, Sun G, Sun G, Lu Z, Huang Y, Yang CG, et al. m6A RNA methylation regulates the self-renewal and tumorigenesis of Glioblastoma stem cells. Cell Rep. 2017;18:2622–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zhang J, Bai R, Li M, Ye H, Wu C, Wang C, Li S, Tan L, Mai D, Li G, et al. Excessive miR-25-3p maturation via N6-methyladenosine stimulated by cigarette smoke promotes pancreatic cancer progression. Nat Commun. 2019;10:1858.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Zhang C, Zhang M, Ge S, Huang W, Lin X, Gao J, Gong J, Shen L. Reduced m6A modification predicts malignant phenotypes and augmented Wnt/PI3K-Akt signaling in gastric cancer. Cancer Med. 2019;8:4766–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Zhu H, Gan X, Jiang X, Diao S, Wu H, Hu J. ALKBH5 inhibited autophagy of epithelial ovarian cancer through miR-7 and BCL-2. J Exp Clin Cancer Res. 2019;38:163.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Peng W, Li J, Chen R, Gu Q, Yang P, Qian W, Ji D, Wang Q, Zhang Z, Tang J, Sun Y. Upregulated METTL3 promotes metastasis of colorectal Cancer via miR-1246/SPRED2/MAPK signaling pathway. J Exp Clin Cancer Res. 2019;38:393.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Feng Z, Li Q, Meng R, Yi B, Xu Q. METTL3 regulates alternative splicing of MyD88 upon the lipopolysaccharide-induced inflammatory response in human dental pulp cells. J Cell Mol Med. 2018;22:2558–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Lin S, Choe J, Du P, Triboulet R, Gregory RI. The m6A methyltransferase METTL3 promotes translation in human Cancer cells. Mol Cell. 2016;62:335–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Visvanathan A, Patil V, Arora A, Hegde AS, Arivazhagan A, Santosh V, Somasundaram K. Essential role of METTL3-mediated m6A modification in glioma stem-like cells maintenance and radioresistance. Oncogene. 2018;37:522–33.

    Article  CAS  PubMed  Google Scholar 

  51. Ma JZ, Yang F, Zhou CC, Liu F, Yuan JH, Wang F, Wang TT, Xu QG, Zhou WP, Sun SH. METTL14 suppresses the metastatic potential of hepatocellular carcinoma by modulating N6 -methyladenosine-dependent primary MicroRNA processing. Hepatology. 2017;65:529–43.

    Article  CAS  PubMed  Google Scholar 

  52. Choe J, Lin S, Zhang W, Liu Q, Wang L, Ramirez-Moya J, Du P, Kim W, Tang S, Sliz P, et al. mRNA circularization by METTL3-eIF3h enhances translation and promotes oncogenesis. Nature. 2018;561:556–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Shi H, Wang X, Lu Z, Zhao BS, Ma H, Hsu PJ, Liu C, He C. YTHDF3 facilitates translation and decay of N6-methyladenosine-modified RNA. Cell Res. 2017;27:315–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Roundtree IA, Luo GZ, Zhang Z, Wang X, Zhou T, Cui Y, Sha J, Huang X, Guerrero L, Xie P, et al. YTHDC1 mediates nuclear export of N6-methyladenosine methylated mRNAs. Elife. 2017;6.

  55. Wang X, Lu Z, Gomez A, Hon GC, Yue Y, Han D, Fu Y, Parisien M, Dai Q, Jia G, et al. N6-methyladenosine-dependent regulation of messenger RNA stability. Nature. 2014;505:117–20.

    Article  PubMed  CAS  Google Scholar 

  56. Haussmann IU, Bodi Z, Sanchez-Moran E, Mongan NP, Archer N, Fray RG, Soller M. m6A potentiates Sxl alternative pre-mRNA splicing for robust Drosophila sex determination. Nature. 2016;540:301–4.

    Article  CAS  PubMed  Google Scholar 

  57. Fustin JM, Doi M, Yamaguchi Y, Hida H, Nishimura S, Yoshida M, Isagawa T, Morioka MS, Kakeya H, Manabe I, Okamura H. RNA-methylation-dependent RNA processing controls the speed of the circadian clock. Cell. 2013;155:793–806.

    Article  CAS  PubMed  Google Scholar 

  58. Ndiaye D, Collado-Hilly M, Martin J, Prigent S, Dufour JF, Combettes L, Dupont G. Characterization of the effect of the mitochondrial protein Hint2 on intracellular Ca2+ dynamics. Biophys J. 2013;105:1268–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Martin J, Maurhofer O, Bellance N, Benard G, Graber F, Hahn D, Galinier A, Hora C, Gupta A, Ferrand G, et al. Disruption of the histidine triad nucleotide-binding hint2 gene in mice affects glycemic control and mitochondrial function. Hepatology. 2013;57:2037–48.

    Article  CAS  PubMed  Google Scholar 

  60. Lee LR, Teng PN, Nguyen H, Hood BL, Kavandi L, Wang G, Turbov JM, Thaete LG, Hamilton CA, Maxwell GL, et al. Progesterone enhances calcitriol antitumor activity by upregulating vitamin D receptor expression and promoting apoptosis in endometrial cancer cells. Cancer Prev Res (Phila). 2013;6:731–43.

    Article  CAS  Google Scholar 

  61. Li W, Cai S, Wang L, Yang C, Zhou B, Wang H. HINT2 downregulation promotes colorectal carcinoma migration and metastasis. Oncotarget. 2017;8:13521–31.

    PubMed  PubMed Central  Google Scholar 

  62. Rietschel P, Panageas KS, Hanlon C, Patel A, Abramson DH, Chapman PB. Variates of survival in metastatic uveal melanoma. J Clin Oncol. 2005;23:8076–80.

    Article  PubMed  Google Scholar 

  63. Satchi K, McKelvie P, McNab AA. Malignant melanoma of the lacrimal drainage apparatus complicating conjunctival melanoma. Ophthalmic Plast Reconstr Surg. 2015;31:207–10.

    Article  PubMed  Google Scholar 

  64. Yang J, Manson DK, Marr BP, Carvajal RD. Treatment of uveal melanoma: where are we now? Ther Adv Med Oncol. 2018;10:1758834018757175.

    PubMed  PubMed Central  Google Scholar 

  65. Field MG, Harbour JW. Recent developments in prognostic and predictive testing in uveal melanoma. Curr Opin Ophthalmol. 2014;25:234–9.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Larsen AC, Dahmcke CM, Dahl C, Siersma VD, Toft PB, Coupland SE, Prause JU, Guldberg P, Heegaard S. A retrospective review of Conjunctival melanoma presentation, treatment, and outcome and an investigation of features associated with BRAF mutations. JAMA Ophthalmol. 2015;133:1295–303.

    Article  PubMed  Google Scholar 

  67. Chen X, Wu Q, Tan L, Porter D, Jager MJ, Emery C, Bastian BC. Combined PKC and MEK inhibition in uveal melanoma with GNAQ and GNA11 mutations. Oncogene. 2014;33:4724–34.

    Article  CAS  PubMed  Google Scholar 

  68. Komatsubara KM, Manson DK, Carvajal RD. Selumetinib for the treatment of metastatic uveal melanoma: past and future perspectives. Future Oncol. 2016;12:1331–44.

    Article  CAS  PubMed  Google Scholar 

  69. Su R, Dong L, Li C, Nachtergaele S, Wunderlich M, Qing Y, Deng X, Wang Y, Weng X, Hu C, et al. R-2HG exhibits anti-tumor activity by targeting FTO/m6A/MYC/CEBPA signaling. Cell. 2018;172:90–105 e123.

    Article  CAS  PubMed  Google Scholar 

  70. Niu Y, Wan A, Lin Z, Lu X, Wan G. N6-Methyladenosine modification: a novel pharmacological target for anti-cancer drug development. Acta Pharm Sin B. 2018;8:833–43.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Zhang SS, Chen TT, Zhu JW, Zhou Q, Chen X, Wang YQ, Zhao WM. GSA: genome sequence archive. Yi Chuan. 2018;40:1044–7.

    PubMed  Google Scholar 

  72. Members BIGDC. The BIG data center: from deposition to integration to translation. Nucleic Acids Res. 2017;45:D18–24.

    Article  CAS  Google Scholar 

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Acknowledgments

We thank all the uveal melanoma and conjunctival melanoma patients enrolled in our study and wish them good health.

Funding

This work was supported by the National Key R&D Program of China (2018YFC1106100, 2018YFC1106101), the National Natural Science Foundation of China (Grant No. 81772875, 81570884, 81770961, 91753000, U1932135), the Research Grant of the Shanghai Science and Technology Committee (17DZ2260100), Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) and the CAS Key Research Projects of Frontier Science (QYZDY-SSW-SMC027).

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Author notes

  1. Ruobing Jia, Peiwei Chai and Shanzheng Wang contributed equally to this work.

Authors and Affiliations

  1. Department of Ophthalmology, Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 20025, People’s Republic of China

    Ruobing Jia, Peiwei Chai, Yangfan Xu, Shengfang Ge, Renbing Jia & Xianqun Fan

  2. Key Laboratory of Genomic and Precision Medicine, Collaborative Innovation Center of Genetics and Development, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China

    Shanzheng Wang, Baofa Sun, Ying Yang & Yun-Gui Yang

  3. Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, 20025, People’s Republic of China

    Ruobing Jia, Peiwei Chai, Yangfan Xu, Shengfang Ge, Renbing Jia & Xianqun Fan

  4. Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100049, China

    Shanzheng Wang, Baofa Sun, Ying Yang & Yun-Gui Yang

  5. Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China

    Baofa Sun, Ying Yang & Yun-Gui Yang

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  1. Ruobing Jia
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Contributions

XQF and YGY conceived this project and supervised all the experiments. RBJ and PWC designed and performed the molecular biology, protein chemistry, and cell culture experiments. RBJ and PWC analyzed the data and drafted the manuscript. RBJ, YFX and SFG were responsible for sample collection. YY, SZW and BFS performed the m6A-seq and bioinformatic analyses with prediction and experimental candidate selection with assistance from RBJ and PWC. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Renbing Jia, Yun-Gui Yang or Xianqun Fan.

Ethics declarations

Ethics approval and consent to participate

This research was performed in accordance with the World Medical Association Declaration of Helsinki. Written informed consent was obtained from all patients. The study was approved by the Ethics Committee of Shanghai JiaoTong University.

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Not applicable.

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The authors declare no competing financial interests.

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Supplementary information

Additional file 1: Table S1.

The clinical characteristics of ocular melanoma patient cohorts in the m6A assay.

Additional file 2: Table S2.

The clinical characteristics of ocular melanoma patient cohorts in tissue chip.

Additional file 3: Table S3.

The detail information of clinical characteristics and gene expression of ocular melanoma patient cohorts in tissue chip.

Additional file 4: Figure S1.

m6A methylation promoted PIG1 cell proliferation.

Additional file 5: Figure S2.

Lower m6A methylation promoted ocular melanoma tumorigenesis.

Additional file 6: Figure S3.

Higher m6A methylation inhibited ocular melanoma tumorigenesis.

Additional file 7: Figure S4.

m6A-seq of ocular melanoma and normal control cells.

Additional file 8: Figure S5.

Characterization and modulation of m6A in ocular melanoma cells.

Additional file 9: Table S4.

List of protein expression of genes in ocular melanoma cells and normal cells according to the Label-free MS.

Additional file 10: Figure S6.

Overexpression of HINT2 inhibited ocular melanoma tumorigenesis.

Additional file 11: Figure S7

. HINT2 translation was promoted by m6A modification.

Additional file 12: Table S5.

Oligonucleotides used in this study.

Additional file 13: Table S6.

Antibodies used in this study.

Additional file 14: Table S7.

Primers used in this study.

Additional file 15.

Unprocessed original scans of blots.

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Jia, R., Chai, P., Wang, S. et al. m6A modification suppresses ocular melanoma through modulating HINT2 mRNA translation. Mol Cancer 18, 161 (2019). https://doi.org/10.1186/s12943-019-1088-x

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Keywords

Molecular Cancer

ISSN: 1476-4598