Contributed equally
It has been >70 years since Waddington first proposed the notion of 'epigenetics' (
Despite increased understanding about m6A, direct or indirect target genes of METTL3 or m6A remain unclear. Additionally, the precise role of METTL3 in cancer cells is unknown. To evaluate the aforementioned issues, we focused on the role of METTL3 in pancreatic cancer cells in patients whose prognosis remains poor despite the recent development of multidisciplinary therapies. We investigated the role of METTL3
Human pancreatic adenocarcinoma cell lines, MIA PaCa-2, were purchased from the the American Type Culture Collection (ATCC; Manassas, VA, USA. The cells were maintained in Dulbecco's modified Eagle's medium (DMEM) low glucose (Nacalai Tesque, Inc., Kyoto, Japan) supplemented with 10% fetal bovine serum (FBS; Thermo Fisher Scientific, Waltham, MA, USA) and 1% penicillin/streptomycin (Life Technologies, Carlsbad, CA, USA) in 5% CO2 at 37°C.
For lentiviral particle production, 293FT cells were seeded 24 h before lentiviral infection and cotransfected with pCMV-VSV-G-RSV-Rev and pCAG-HIVgp (provided by Dr Miyoshi from the RIKEN BioResource, Tokyo, Japan) plasmid using Lipofectamine 3000 and P3000 Reagent (Thermo Fisher Scientific) as described in the standard protocol of Lipofectamine 3000. Target sequences of METTL3 short hairpin RNA (shRNA) were 5′-CCAGTCATAAACCAGATGAAA-3′. The collected viral soup was centrifuged at 12,000 x g for 5 min, and the supernatant was filtered with 0.22-
Total RNA was extracted from cultured cells using TRIzol reagent (Thermo Fisher Scientific) and cDNA was synthesized with ReverTra Ace (Toyobo Co., Ltd., Osaka, Japan). Quantitative RT-PCR was performed with Thunderbird SYBR qPCR Mix (Toyobo) using LightCycler 2.0 (Roche Molecular Systems, Inc., Pleasanton, CA, USA). Furthermore, data were analyzed by the ΔΔCt method, in which target genes were normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH). The following primers were used in the present study: GAPDH-F, 5′-GCCCAATACGACCAAATCC-3′ and GAPDH-R, 5′-AGC CACATCGCTCAGACAC-3′; METLL3-F, 5′-CGTACTACA GGATGATGGCTTTC-3′ and METTL3-R, 5′-TTTCATCTA CCCGTTCATACCC-3′.
Plated cells were carefully washed twice with phosphate-buffered saline (PBS; Thermo Fisher Scientific). Next, total protein was extracted with radioimmunoprecipitation assay buffer (Pierce, Rockford, IL, USA) supplemented with 1% of Halt Protease Inhibitor Cocktail (100X) and Halt Phosphatase Inhibitor Cocktail (100X; Thermo Fisher Scientific). Isolated proteins were electrophoresed on 4-20% Mini-PROTEAN TGX Precast protein gels (Bio-Rad Laboratories, Hercules, CA, USA) and transferred to Blot 2 PVDF Mini Stack membranes (Thermo Fisher Scientific) using iBlot 2 Dry Blotting System (Life Technologies). The membrane was blocked with 5% skim milk (Wako Pure Chemical Industries, Ltd., Osaka, Japan) for 1 h at room temperature and reacted with appropriate dilutions of primary antibody overnight at 4°C. The membrane was washed with Tris-buffered saline-Tween (TBST) 6 times for 5 min each, followed by incubation with HRP-linked, anti-rabbit immunoglobulin G (GE Healthcare Biosciences, Little Chalfont, UK) for 1 h at room temperature. The membrane was washed again with TBST 6 times for 5 min each. Next, the secondary anti-bodies were identified using detection reagent Clarity Western ECL substrate (Bio-Rad Laboratories). Images were acquired with ImageQuant LAS 4000 (GE Healthcare Biosciences). The following primary antibodies were used in this study: METTL3 (Proteintech Group Inc., Chicago, IL, USA; rabbit, #15073-1-AP, 1:1,000) and β-actin (Cell Signaling Technology, Danvers, MA, USA; rabbit, #4967, 1:10,000).
Cells were seeded in 96-well plates with 1,500 cells/well containing 100
We performed sphere formation assay using the limiting dilution method. Cultured cells were collected in serum-free DMEM/F-12 with GlutaMAX, bFGF, EGF, B-27 and N2 supplements (Thermo Fisher Scientific). Cell numbers were diluted to 10 cells/ml, then 100-
Cells were plated in 96-well plates at a density of 900 cells/90
Radiosensitivity assay was performed as previously described (
Cells were seeded into four 96-well plates, respectively, in the same way as the chemosensitivity assay. In 2 of 4 plates, 10
GEM was added (final concentration 16 nM) after 4×104 cells were seeded in 10-cm dishes and incubated for 24 h. PBS was used as a control. After incubation for 48 h, apoptosis assay was performed using the Annexin V-FITC apoptosis detection kit (Nacalai Tesque) in accordance with the instructional protocols. Fluorescence intensity of Annexin V-FITC and PI were measured after gating viable cells on FSC vs. SSC dot plots using the BD FACSCanto II system (BD Biosciences, Franklin Lakes, NJ, USA).
The relative expression levels of 35 human apoptosis-related proteins were detected using the Proteome Profiler Array Human Apoptosis Array kit (R&D Systems, Minneapolis, MN, USA). Cells on a 10-cm dish were rinsed with PBS 3 times and solubilized with lysis buffer supplemented with 1% of Halt Protease Inhibitor Cocktail (Thermo Fisher Scientific). Experiments were performed in accordance with the manufacturer's instructions.
TRIzol reagents were used to extract total RNA from cultured cells, and RNA quality was checked (RNA concentration >0.5
Differentially expressed genes whose fold changes were >2 or <1/2 in METTL3 KD cells underwent Gene Ontology (GO) functional enrichment analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8 (
The functional interactions among differentially expressed genes were conducted with the online Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, available at
All data obtained were analyzed by the JMP Pro 12.2.0 software (SAS Institute, Inc., Cary, NC, USA) and described as mean ± standard error (SE). Unless stated otherwise, Student's t-test was used for statistical analysis for experimental results and the differences were considered significant.
We established METTL3 KD cell lines using shRNA. Stable KD of METTL3 in RNA and protein expression was confirmed with qRT-PCR and western blot analysis, respectively (
We performed crystal violet assay under administration of 5-FU, CDDP and GEM to test whether METTL3 KD alters sensitivity to anticancer agents. METTL3 depletion enhanced the sensitivity to each drug (
The aforementioned data suggested that METTL3 is involved in apoptosis; therefore, Annexin V assay was conducted 48 h after treatment with GEM (
Given that METTL3 functions as m6A writers (
In the present study, we demonstrated that METTL3 was a key protein in pancreatic cancer therapy and addressed potential targets of METTL3. METTL3 KD MIA PaCa2 cells showed lower self-renewal abilities in sphere formation assay (
While investigating whether METTL3 KD affected chemo- or radiotherapy, we found that anticancer agents, 5-FU, CDDP and GEM, as well as radiation treatment significantly suppressed cell proliferation in METTL3 KD cells (
From cDNA microarray data, several processes and cascades emerged as potential targets of METTL3: MAPK cascades, ubiquitin-dependent process, RNA splicing and regulation of the cellular process (
This study also showed that ubiquitin-dependent process is a possible target of METTL3 (
Furthermore, we found that the RNA splicing process was a potent target process of METTL3 (
We note several limitations to this study. First, our
In summary, the present study demonstrates that METTL3 is associated with therapeutic resistance and is a potential therapeutic target of pancreatic cancer. Additionally, our findings suggest several critical pathways, including MAPK cascades, ubiquitin-dependent process, RNA splicing and regulation of cellular process, as possible targets of METTL3. Alteration of these processes triggers various aberrant biological behaviors that could lead to cancer progression and therapeutic resistance. Further studies on the interactions between METTL3 and these processes are critical for understanding the functional mechanisms of METTL3.
The authors thank our laboratory members for fruitful discussions, N. Nishida, K. Otani and K. Tamari for helpful suggestions, and M. Ozaki and Y. Noguchi for excellent technical support. Flow cytometric analysis was performed with equipment in the Center for Medical Research and Education, Graduate School of Medicine, Osaka University, Japan. This study received financial support from grants-in-aid for Scientific Research and P-DIRECT and P-CREATE Grants from the Ministry of Education, Culture, Sports, Science, and Technology, MEXT (MK, YD, MM, HI, and KO); Kobayashi Foundation for Cancer Research (HI); Kobayashi International Scholarship Foundation (MK, HI); and a grant-in-aid from the Ministry of Health, Labor, and Welfare (MK, YD, MM, HI, and KO). Institutional endowments were received from Taiho Pharmaceutical Co., Ltd. (Tokyo, Japan), Evidence Based Medical Research Center INC. (Osaka, Japan), UNITECH Co., Ltd. (Chiba, Japan), IDEA Consultants, Inc. (Tokyo, Japan), and Kinshukai Medical Corporation (Osaka, Japan). These funders had no role in the main experimental equipment, supply expenses, study design, data collection and analysis, decision to publish, or preparation of the present study.
Knockdown (KD) of METTL3 by short hairpin RNA. (A) qRT-PCR (n=3) and (B) western blot analysis of METTL3 showed decreased expression levels of METTL3. (C) Representative sphere images of control (shCTL) and shMETTL3 cells. (D) METTL3 KD cells showed significantly lower ability than control cells to form spheres. PCR and sphere formation assay data were analyzed by the Student's t-test and one-way ANOVA, respectively (**P<0.001, ***P<0.0001).
METTL3 depletion enhances chemosensitivity. METTL3 KD cells showed increased sensitivity to anticancer drugs: (A) 5-FU, (B) CDDP, and (C) GEM. The IC50 value (shCTL/shMETTL3) of each drug were as follows: 5-FU, 28.0/18.4
METTL3 depletion enhances radio- and chemoradiosensitivity. (A) Images of colonies stained by crystal violet. METTL3 KD cells showed significant susceptibility to (B) irradiation (IR) of 4 Gy as well as concurrent use of radiation and (C) CDDP or (D) GEM. Data from clonogenic assay and chemoradiosensitivity assay were analyzed by the Student's t-test (n=6) and multifactor ANOVA, respectively (*P<0.05, **P<0.01, ***P<0.001).
METTL3 depletion enhances late apoptosis in the presence of GEM. Annexin V assay in control and METTL3 KD cells. Diagrams Q1 to Q4 represent necrotic, late apoptotic, early apoptotic and live cells, respectively.
Predicted protein-protein interaction networks of downregulated differentially expressed genes in METTL3 KD cells. STRING database provided 209 nodes (genes) and 362 edges (interactions) in the network.
Three highly interconnected regions were detected as modules in the PPI network of downregulated differentially expressed genes in METTL3 KD cells. Genes in (A) module 1, (B) module 2 and (C) module 3 were associated with ubiquitin-dependent process, RNA splicing and regulation of the cellular process, respectively.
Top five GO terms and Reactome pathways of upregulated DEGs.
Category | Term | Count | P-value | FDR |
---|---|---|---|---|
GOTERM_BP_FAT | GO:0071357~cellular response to type I interferon | 6 | 2.80E-05 | 0.0488 |
GOTERM_BP_FAT | GO:0060337~type I interferon signaling pathway | 6 | 2.80E-05 | 0.0488 |
GOTERM_BP_FAT | GO:0034340~response to type I interferon | 6 | 3.62E-05 | 0.0630 |
GOTERM_BP_FAT | GO:0032020~ISG15-protein conjugation | 3 | 3.38E-04 | 0.5862 |
GOTERM_BP_FAT | GO:0006955~immune response | 18 | 9.54E-04 | 1.647 |
REACTOME_PATHWAY | R-HSA-909733~Interferon α/β signaling | 6 | 3.41E-05 | 0.0417 |
REACTOME_PATHWAY | R-HSA-168928~DDX58/IFIH1-mediated induction of interferon-α/β | 3 | 3.99E-03 | 4.783 |
REACTOME_PATHWAY | R-HSA-936440~Negative regulators of DDX58/IFIH1 signaling | 3 | 1.55E-02 | 17.417 |
REACTOME_PATHWAY | R-HSA-1169408~ISG15 antiviral mechanism | 3 | 6.32E-02 | 55.089 |
REACTOME_PATHWAY | R-HSA-1236977~Endosomal/vacuolar pathway | 2 | 6.54E-02 | 56.377 |
DEGs, differentially expressed genes; FDR, false discovery rate; GO, Gene Ontology.
Top five GO terms and Reactome pathways of downregulated DEGs.
Category | Term | Count | P-value | FDR |
---|---|---|---|---|
GOTERM_BP_FAT | GO:0043408~regulation of MAPK cascade | 36 | 6.94.E-04 | 1.319 |
GOTERM_BP_FAT | GO:0051128~regulation of cellular component organization | 93 | 9.23.E-04 | 1.749 |
GOTERM_BP_FAT | GO:0007010~cytoskeleton organization | 52 | 1.38.E-03 | 2.602 |
GOTERM_BP_FAT | GO:0000226~microtubule cytoskeleton organization | 25 | 1.63.E-03 | 3.065 |
GOTERM_BP_FAT | GO:0002821~positive regulation of adaptive immune response | 9 | 2.01.E-03 | 3.769 |
REACTOME_PATHWAY | R-HSA-2428928~IRS-related events triggered by IGF1R | 3 | 1.21.E-02 | 16.127 |
REACTOME_PATHWAY | R-HSA-112412~SOS-mediated signaling | 3 | 1.67.E-02 | 21.4931 |
REACTOME_PATHWAY | R-HSA-450302~activated TAK1 mediates p38 MAPK activation | 4 | 2.31.E-02 | 28.560 |
REACTOME_PATHWAY | R-HSA-171007~p38MAPK events | 3 | 5.51.E-02 | 55.772 |
REACTOME_PATHWAY | R-HSA-418359~Reduction of cytosolic Ca++ levels | 3 | 6.30.E-02 | 60.840 |
DEGs, differentially expressed genes; FDR, false discovery rate; GO, Gene Ontology.
Top three GO terms of modules in PPI of downregulated DEGs.
Category | Term | Count | P-value | FDR |
---|---|---|---|---|
Hub nodes 1 | ||||
GOTERM_BP_FAT | GO:0016567~protein ubiquitination | 9 | 1.74E-10 | 2.53E-07 |
GOTERM_BP_FAT | GO:0032446~protein modification by small protein conjugation | 9 | 5.40E-10 | 7.84E-07 |
GOTERM_BP_FAT | GO:0070647~protein modification by small protein conjugation or removal | 9 | 1.81E-09 | 2.62E-06 |
Hub nodes 2 | ||||
GOTERM_BP_FAT | GO:0000377~RNA splicing, via transesterification reactions with bulged adenosine as nucleophile | 5 | 1.02E-07 | 1.20E-04 |
GOTERM_BP_FAT | GO:0000398~mRNA splicing, via spliceosome | 5 | 1.02E-07 | 1.20E-04 |
GOTERM_BP_FAT Hub nods 3 | GO:0000375~RNA splicing, via transesterification reactions | 5 | 1.08E-07 | 1.26E-04 |
GOTERM_BP_FAT | GO:0010557~positive regulation of macromolecule biosynthetic process | 10 | 8.61E-07 | 1.38.E-03 |
GOTERM_BP_FAT | GO:0031328~positive regulation of cellular biosynthetic process | 10 | 1.70E-06 | 2.72.E-03 |
GOTERM_BP_FAT | GO:0009891~positive regulation of biosynthetic process | 10 | 1.97E-06 | 3.16.E-03 |
DEGs, differentially expressed genes; FDR, false discovery rate; GO, Gene Ontology.