N6-Methyladenosine (m6A) is the most prevalent modification of RNA in eukaryotes, and is associated with many cellular processes and even the development of cancers. We hypothesized that single-nucleotide polymorphisms (SNPs) in m6A modification genes, including its “writers”, “erasers” and “readers”, might affect the m6A functions and associate with the susceptibility to pancreatic ductal adenocarcinoma (PDAC). We first conducted a two-stage case–control study in Chinese population to interrogate all SNPs in 22 m6A modification genes. In the discovery stage, a total of 2735 SNPs were genotyped in 980 patients and 1991 controls. Then, the promising SNP was replicated in another independent population consisting of 858 cases and 2084 controls. As a result, we found the rs7495 in 3′UTR of hnRNPC was significantly associated with increased risk of PDAC in both stages (combined odds ratio = 1.22, 95% confidence interval = 1.12–1.32, P = 2.39 × 10–6). To further reveal the biological function of rs7495 and hnRNPC, we performed a series of biochemical experiments. Luciferase reporter assays indicated that rs7495G allele promoted hnRNPC expression through disrupting a putative binding site for has-miR-183-3p. Cell viability assay demonstrated that knockdown of hnRNPC suppressed the proliferation of PDAC cells. RNA-seq analysis suggested that as an m6A “reader”, hnRNPC played an important role in RNA biological processes. In conclusion, our findings elucidated that rs7495G could confer higher risk of PDAC via promoting the expression of hnRNPC through a miRNA-mediated manner. These results provided a novel insight into the critical role of m6A modification in tumorigenesis.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Agarwal V, Bell GW, Nam JW, Bartel DP (2015) Predicting effective microRNA target sites in mammalian mRNAs. eLife. https://doi.org/10.7554/eLife.05005
Albert FW, Kruglyak L (2015) The role of regulatory variation in complex traits and disease. Nat Rev Genet 16(4):197–212. https://doi.org/10.1038/nrg3891
Anantha RW, Alcivar AL, Ma J et al (2013) Requirement of heterogeneous nuclear ribonucleoprotein C for BRCA gene expression and homologous recombination. PLoS ONE 8(4):e61368. https://doi.org/10.1371/journal.pone.0061368
Bi Z, Liu Y, Zhao Y et al (2019) A dynamic reversible RNA N(6) -methyladenosine modification: current status and perspectives. J Cell Physiol 234(6):7948–7956. https://doi.org/10.1002/jcp.28014
Boyle AP, Hong EL, Hariharan M et al (2012) Annotation of functional variation in personal genomes using RegulomeDB. Genome Res 22(9):1790–1797. https://doi.org/10.1101/gr.137323.112
Bracken CP, Scott HS, Goodall GJ (2016) A network-biology perspective of microRNA function and dysfunction in cancer. Nat Rev Genet 17(12):719–732. https://doi.org/10.1038/nrg.2016.134
Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Can J Clin 68(6):394–424. https://doi.org/10.3322/caac.21492
Childs EJ, Mocci E, Campa D et al (2015) Common variation at 2p13.3, 3q29, 7p13 and 17q25.1 associated with susceptibility to pancreatic cancer. Nat Genet 47(8):911–916. https://doi.org/10.1038/ng.3341
Christian KJ, Lang MA, Raffalli-Mathieu F (2008) Interaction of heterogeneous nuclear ribonucleoprotein C1/C2 with a novel cis-regulatory element within p53 mRNA as a response to cytostatic drug treatment. Mol Pharmacol 73(5):1558–1567. https://doi.org/10.1124/mol.107.042507
Cieniková Z, Damberger FF, Hall J, Allain FH, Maris C (2014) Structural and mechanistic insights into poly(uridine) tract recognition by the hnRNP C RNA recognition motif. J Am Chem Soc 136(41):14536–14544. https://doi.org/10.1021/ja507690d
Dimitrakopoulos C, Vrugt B, Flury R et al (2019) Identification and validation of a biomarker signature in patients with resectable pancreatic cancer via genome-wide screening for functional genetic variants. JAMA Surg 154(6):e190484. https://doi.org/10.1001/jamasurg.2019.0484
Du K, Zhang L, Lee T, Sun T (2019) m(6)A RNA methylation controls neural development and is involved in human diseases. Mol Neurobiol 56(3):1596–1606. https://doi.org/10.1007/s12035-018-1138-1
Frye M, Harada BT, Behm M, He C (2018) RNA modifications modulate gene expression during development. Science 361(6409):1346–1349. https://doi.org/10.1126/science.aau1646
Fu Y, Dominissini D, Rechavi G, He C (2014) Gene expression regulation mediated through reversible m6A RNA methylation. Nat Rev Genet 15(5):293–306. https://doi.org/10.1038/nrg3724
Guo Y, He J, Zhao S et al (2014) Illumina human exome genotyping array clustering and quality control. Nat Protoc 9(11):2643–2662. https://doi.org/10.1038/nprot.2014.174
He L, Li J, Wang X et al (2018a) The dual role of N6-methyladenosine modification of RNAs is involved in human cancers. J Cell Mol Med 22(10):4630–4639. https://doi.org/10.1111/jcmm.13804
He Y, Hu H, Wang Y et al (2018b) ALKBH5 Inhibits Pancreatic cancer motility by decreasing long non-coding RNA KCNK15-AS1 methylation. Cell Physiol Biochem 48(2):838–846. https://doi.org/10.1159/000491915
Kim JH, Paek KY, Choi K et al (2003) Heterogeneous nuclear ribonucleoprotein C modulates translation of c-myc mRNA in a cell cycle phase-dependent manner. Mol Cell Biol 23(2):708–720. https://doi.org/10.1128/mcb.23.2.708-720.2003
Krol J, Loedige I, Filipowicz W (2010) The widespread regulation of microRNA biogenesis, function and decay. Nat Rev Genet 11(9):597–610. https://doi.org/10.1038/nrg2843
Liu J, Jia G (2014) Methylation modifications in eukaryotic messenger RNA. J Genet Genomics 41(1):21–33. https://doi.org/10.1016/j.jgg.2013.10.002
Liu N, Dai Q, Zheng G, He C, Parisien M, Pan T (2015) N(6)-methyladenosine-dependent RNA structural switches regulate RNA-protein interactions. Nature 518(7540):560–564. https://doi.org/10.1038/nature14234
Mathiyalagan P, Adamiak M, Mayourian J et al (2019) FTO-dependent N(6)-Methyladenosine regulates cardiac function during remodeling and repair. Circulation 139(4):518–532. https://doi.org/10.1161/circulationaha.118.033794
Maurano MT, Humbert R, Rynes E et al (2012) Systematic localization of common disease-associated variation in regulatory DNA. Science 337(6099):1190–1195. https://doi.org/10.1126/science.1222794
McCloskey A, Taniguchi I, Shinmyozu K, Ohno M (2012) hnRNP C tetramer measures RNA length to classify RNA polymerase II transcripts for export. Science 335(6076):1643–1646. https://doi.org/10.1126/science.1218469
Mei S, Qin Q, Wu Q et al (2017) Cistrome data browser: a data portal for ChIP-Seq and chromatin accessibility data in human and mouse. Nucleic Acids Res 45(D1):D658–D662. https://doi.org/10.1093/nar/gkw983
Meyer KD, Jaffrey SR (2017) Rethinking m(6)A readers, writers, and erasers. Annu Rev Cell Dev Biol 33:319–342. https://doi.org/10.1146/annurev-cellbio-100616-060758
Meyers RM, Bryan JG, McFarland JM et al (2017) Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells. Nat Genet 49(12):1779–1784. https://doi.org/10.1038/ng.3984
Panneerdoss S, Eedunuri VK, Yadav P et al (2018) Cross-talk among writers, readers, and erasers of m(6)A regulates cancer growth and progression. Sci Adv 4(10):eaar8263. https://doi.org/10.1126/sciadv.aar8263
Park YM, Hwang SJ, Masuda K et al (2012) Heterogeneous nuclear ribonucleoprotein C1/C2 controls the metastatic potential of glioblastoma by regulating PDCD4. Mol Cell Biol 32(20):4237–4244. https://doi.org/10.1128/mcb.00443-12
Petersen GM, Amundadottir L, Fuchs CS et al (2010) A genome-wide association study identifies pancreatic cancer susceptibility loci on chromosomes 13q22.1, 1q32.1 and 5p15.33. Nat Genet 42(3):224–228. https://doi.org/10.1038/ng.522
Rajagopalan LE, Westmark CJ, Jarzembowski JA, Malter JS (1998) hnRNP C increases amyloid precursor protein (APP) production by stabilizing APP mRNA. Nucleic Acids Res 26(14):3418–3423. https://doi.org/10.1093/nar/26.14.3418
Roost C, Lynch SR, Batista PJ, Qu K, Chang HY, Kool ET (2015) Structure and thermodynamics of N6-methyladenosine in RNA: a spring-loaded base modification. J Am Chem Soc 137(5):2107–2115. https://doi.org/10.1021/ja513080v
Ryan BM (2017) microRNAs in cancer susceptibility. Adv Cancer Res 135:151–171. https://doi.org/10.1016/bs.acr.2017.06.004
Ryan DP, Hong TS, Bardeesy N (2014) Pancreatic adenocarcinoma. N Engl J Med 371(11):1039–1049. https://doi.org/10.1056/NEJMra1404198
Samur MK (2014) RTCGAToolbox: a new tool for exporting TCGA firehose data. PLoS ONE 9(9):e106397. https://doi.org/10.1371/journal.pone.0106397
Teng L, He B, Wang J, Tan K (2016) 4DGenome: a comprehensive database of chromatin interactions. Bioinformatics 32(17):2727. https://doi.org/10.1093/bioinformatics/btw375
Wang X, Lu Z, Gomez A et al (2014a) N6-methyladenosine-dependent regulation of messenger RNA stability. Nature 505(7481):117–120. https://doi.org/10.1038/nature12730
Wang Z, Zhu B, Zhang M et al (2014b) Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33. Hum Mol Genet 23(24):6616–6633. https://doi.org/10.1093/hmg/ddu363
Wang X, Zhao BS, Roundtree IA et al (2015) N(6)-methyladenosine modulates messenger RNA translation efficiency. Cell 161(6):1388–1399. https://doi.org/10.1016/j.cell.2015.05.014
Wang S, Sun C, Li J et al (2017) Roles of RNA methylation by means of N(6)-methyladenosine (m(6)A) in human cancers. Cancer Lett 408:112–120. https://doi.org/10.1016/j.canlet.2017.08.030
Wang Y, Song F, Zhang B et al (2018) The 3D genome browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions. Genome Biol 19(1):151. https://doi.org/10.1186/s13059-018-1519-9
Ward LD, Kellis M (2016) HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease. Nucleic Acids Res 44(D1):D877–D881. https://doi.org/10.1093/nar/gkv1340
Wolfgang CL, Herman JM, Laheru DA et al (2013) Recent progress in pancreatic cancer. Cancer J Clin 63(5):318–348. https://doi.org/10.3322/caac.21190
Wu C, Miao X, Huang L et al (2011) Genome-wide association study identifies five loci associated with susceptibility to pancreatic cancer in Chinese populations. Nat Genet 44(1):62–66. https://doi.org/10.1038/ng.1020
Wu Y, Zhao W, Liu Y et al (2018) Function of HNRNPC in breast cancer cells by controlling the dsRNA-induced interferon response. EMBO J. https://doi.org/10.15252/embj.201899017
Zarnack K, König J, Tajnik M et al (2013) Direct competition between hnRNP C and U2AF65 protects the transcriptome from the exonization of Alu elements. Cell 152(3):453–466. https://doi.org/10.1016/j.cell.2012.12.023
Zhang H, Wheeler W, Hyland PL et al (2016) A powerful procedure for pathway-based meta-analysis using summary statistics identifies 43 pathways associated with type II diabetes in European populations. PLoS Genet 12(6):e1006122. https://doi.org/10.1371/journal.pgen.1006122
Zhang Y, Chen W, Pan T, Wang H, Zhang Y, Li C (2019) LBX2-AS1 is activated by ZEB1 and promotes the development of esophageal squamous cell carcinoma by interacting with HNRNPC to enhance the stability of ZEB1 and ZEB2 mRNAs. Biochem Biophys Res Commun 511(3):566–572. https://doi.org/10.1016/j.bbrc.2019.02.079
Zhao X, Yang Y, Sun BF et al (2014) FTO-dependent demethylation of N6-methyladenosine regulates mRNA splicing and is required for adipogenesis. Cell Res 24(12):1403–1419. https://doi.org/10.1038/cr.2014.151
Zhou KI, Parisien M, Dai Q et al (2016) N(6)-methyladenosine modification in a long noncoding RNA hairpin predisposes its conformation to protein binding. J Mol Biology 428(5):822–833. https://doi.org/10.1016/j.jmb.2015.08.021
We gratefully acknowledge the members of the Miao lab for the suggestions and contributions to this work. This work was supported National Natural Science Foundation of China NSFC-81673256, National High-Tech Research and Development Program of China 2014AA020609, Program for HUST Academic Frontier Youth Team and National Science Fund for Distinguished Young Scholars of China for Xiaoping Miao, National Program for Support of Top-notch Young Professionals and the Young Elite Scientist Sponsorship Program by CAST (2018QNRC001) for Jiang Chang.
Conflict of interest
The authors declare no conflicts of interest.
All the procedures involving human participants were in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.
The datasets during the current study are available from the corresponding author on reasonable request. Informed consent was obtained from each subject, and this study was approved by the Chinese Academy of Medical Sciences Cancer Institute and the Institutional Review Board of Tongji Medical College, HUST. All participants gave written informed consent.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Below is the link to the electronic supplementary material.
About this article
Cite this article
Ying, P., Li, Y., Yang, N. et al. Identification of genetic variants in m6A modification genes associated with pancreatic cancer risk in the Chinese population. Arch Toxicol 95, 1117–1128 (2021). https://doi.org/10.1007/s00204-021-02978-5
- Genetic variant
- Pancreatic ductal adenocarcinoma