RNA methyltransferases were upregulated in gastrointestinal cancer

To investigate whether the methylated RNAs are up- or downregulated in cancer cells, we first examined the expression levels of RNA-methylation enzymes; writer proteins such as methyltransferase-like (METTL)3 and METTL14, which are methylation enzymes for adenine13,14,15 and NOP2/Sun RNA methyltransferase family member (NSUN)2, which is a methylation enzyme for cytosine16. Although the expression levels were similar between gastrointestinal cancer and normal tissues, the data showed different distribution between gastrointestinal cancer and normal tissues. The expression levels tended to be upregulated in gastrointestinal cancer. (Fig. 1a, b and Supplementary Figs. 1 and 2). Moreover, the expression levels of METTL3 and the adenine demethylation enzyme AlkB homolog (ALKBH)5 were negatively correlated (Fig. 1c), suggesting that RNA methylation tended to increase in gastrointestinal cancer. To quantify the methylated miRNA in gastrointestinal cancer cells, we carried out liquid chromatography-mass spectrometry (MS) analysis17 of small RNA fractions of three different cell lines that were size-fractionated from total RNA by ultrafiltration. RNA methyl marks including 5-methylcytosine (5mC), N6-methyladenosine (m6A), 3-methylcytosine, and N1-methyladenine (m1A) were detected in 1–8% of total adenines and cytosines analyzed (See Supplementary Fig. 3). Importantly, the fraction of methylated miRNAs increased upon stimulation with epidermal growth factor in all cell lines examined, suggesting the existence of a systemic regulatory mechanism for RNA modification.

Fig. 1 Methylated miRNAs are tended to upregulated in gastrointestinal cancer. a Analysis of RNA expression levels of the RNA methylases METTL3 using a Gene Expression Omnibus (GEO) dataset (GDS4103) derived from pancreatic cancer and paired normal tissue samples from 36 patients. *p= 7.68 × 10−5 (Wilcoxon’s t test). b Analysis of RNA expression levels of the RNA methylase METTL14 using a Gene Expression Omnibus (GEO) dataset (GDS4103) derived from pancreatic cancer and paired normal tissue samples from 36 patients. *p= 0.007193 (Wilcoxon’s t test). c Analysis of the correlation between METTL3 and ALKBH5 expression levels. Blue and orange points represent normal tissue and Pancreatic cancer tissue, respectively. R value was −0.68 in normal tissue and −0.19 in pancreatic cancer. d Methylated miRNA analysis by RIP-Seq using an anti-m6A antibody. The Venn diagram shows that 63 methylated miRNAs were common to four pancreatic cancer cell lines. The box range means from the first quartile to the third quartile. The second quartile means the median of the data. The lower limit of the bar was estimated by “the first quartile − 1.5 × interquartile range”, and the upper limit of the bar was estimated by “the third quartile + 1.5 × interquartile range” Full size image

Methylated microRNAs have altered target inhibitory effects

To clarify the biological significance of mature miRNA methylation, we synthesized miR-200c oligonucleotides with m6A or m5C modifications at all adenines and cytosines, respectively. These oligonucleotides with or without methylation were transfected into the DICER exon 5-disrupted colorectal cancer cell line HCT116 (HCT116EX5), which has very low expression levels of endogenous miRNAs18. Gene expression profiling revealed that m6A-modified miR-200c-3p did not reduce target mRNA expression level as compared to m5C-modified or non-methylated miR-200c-3p (See Supplementary Fig. 4).

New-method for detect the methylated microRNAs using MALDI-TOF-MS

Based on our observation that RNA methyltransferases were increased in gastrointestinal cancer cells, we speculated that methylated miRNAs could serve as biomarkers for gastrointestinal cancer. To be find the commonly methylated miRNAs in gastrointestinal cancer, we tried to m6A RIP-Seq analysis of four pancreatic cancer cell lines and identified 63 commonly-methylated miRNAs (Fig. 1d and See Supplementary Table 1). Since conventional RNA-Seq with a next-generation sequencer cannot detect methylated bases in miRNAs, we purified target miRNAs using magnetic beads with bound complementary oligonucleotides and analyzed these by matrix-assisted laser desorption/ionization time-of-flight tandem MS19,20,21,22,23 (Fig. 2a, b). Methylated nucleotides were detected as a peak a +14 Da from predicted non-methylated peaks in the mass spectrum; the methylation site was further confirmed by derivatization of nucleotides (see Methods for details). The methylation level of each miRNA was evaluated using synthetic non-methylated (let-7a-5p and miR-17-5p) and methylated (let-7a-5p and miR-17-5p) miRNAs as the ratio between peak intensities of methylated and non-methylated nucleotides. This approach provided a highly sensitive and quantitative measurement of non-methylated and methylated miRNA oligonucleotides (Fig. 2b, See Supplementary Fig. 5 and Supplementary Table 2). We used this method to assess the methylation levels of miRNAs identified by RIP-Seq (Fig. 1d, See Supplementary Table 1) in pancreatic cancer tissue. Let-7a-5p and miR-17-5p had m6A whereas miR-200c-3p and miR-21-3p had 5mC modifications at specific positions in the mature sequence (Fig. 2c, d, See Supplementary Fig. 6). We next measured the methylation levels of these miRNAs in pancreatic and colorectal cancer tissues and paired normal samples and found that methylation was increased in all examined cases whereas no differences in miRNA expression level were detected by quantitative reverse transcription PCR (Fig. 3a, b, See Supplementary Figs 7–10, and Supplementary Tables 3–4). Moreover, the methylation levels of these miRNAs were higher in serum samples from pancreatic and colorectal cancer patients than in those from normal subjects (Fig. 3c, d, See Supplementary Figs. 11–14), and were lower in post- as compared to pre-surgery samples (Fig. 3e, f).

Fig. 2 Detection of methylated bases in mature miRNAs. a Schematic depiction of the procedure for detecting RNA modifications in mature miRNA sequences. Total small RNA extracted from cells was hybridized with oligonucleotides complementary to target miRNAs on magnetic beads. Captured miRNAs were eluted and applied to sample plates and then analyzed by matrix-assisted laser desorption/ionization time-of-flight tandem MS (MALDI-TOF-MS/MS). b Dynamic range of methylated miRNA detection. Synthetic miR-200c-3p oligonucleotides with or without methylation were mixed at the indicated concentrations and analyzed by MALDI-TOF-MS/MS. c Mass spectrum of miR-17-5p and let-7a-5p obtained from pancreatic cancer patient-derived tissue. The spectrum shows monovalent, divalent, and trivalent methylated miR-17-5p RNA peaks and monovalent and divalent let-7a-5p RNA peaks (see Methods for details). d Position of methylated nucleoside in each miRNA Full size image

Fig. 3 Increased miRNA methylation levels in pancreatic cancer tissue and serum. a, b Enhancement of miR-17-5p (a) and let-7a-5p (b) methylation in pancreatic cancer tissue (n = 12) relative to paired healthy tissue (n = 12). *p < 0.01 (t test). c, d Fraction of methylated miRNA at a specific position of miR-17-5p (c) and let-7a-5p (d) in serum derived from pancreatic cancer patients (n = 5) and healthy controls (n = 5). Healthy control serum was obtained from liver transplantation donors who were confirmed as having no cancer by endoscopy, computed tomography, and by detection of several tumor markers.*p < 0.01 (t test). e, f Fraction of methylated miRNA at a specific position of miR-17-5p (e) and let-7a-5p (f) in serum derived from pancreatic cancer patients before (n = 21) and after (n = 21) surgery. Healthy control serum was obtained from liver transplantation donors who were confirmed as having no cancer by endoscopy, computed tomography, and by detection of several tumor markers.*p < 0.01 (t test). The box range means from the first quartile to the third quartile. The second quartile means the median of the data. The lower limit of the bar was estimated by “the first quartile − 1.5 × interquartile range”, and the upper limit of the bar was estimated by “the third quartile + 1.5 × interquartile range Full size image

Predicting structural changes of RISC complex by methylated microRNA

To clarify the biological significance of mature miRNA methylation, we carried out molecular simulations to examine the binding between Argonaute (AGO) protein and miR-17-5p and -200c-3p and let-7a-5p (with or without methylation) as well as structural changes in the complexes. In miR-200c-3p, the 5mC modification at position 9 was close to RNA recognition bases. Although there was no obvious difference between the first six nucleotides of methylated and non-methylated miR-200c-3p in the AGO complex, variations in the binding interaction between AGO and each miRNA were observed around the methyl groups, which enhanced van der Waals interactions with the protein and thereby diminished the surrounding space. At the same time, methyl groups of the cytosine at position 9 disrupted hydrogen bonding with Ser220 of AGO likely through steric hindrance, leading to a positional shift of the guanine at position 8 that was also caused by interaction with Arg761 of AGO (See Supplementary Fig. 15). In miR-17-5p and let-7a-5p, methylated adenines were located away from the RNA-binding site; however, m6A modification causes a large structural change in the whole complex, including around the RNA recognition site, which affects the target RNA recognition efficiency (See Supplementary Figs. 16 and 17). These findings indicate that m6A modification reduces the ability of miRNAs to suppress target mRNA translation.

Methylated microRNAs become biomarkers of gastrointestinal cancer

To evaluate the potential of miRNA methylation as a biomarker for early cancer diagnosis, we examined miRNA methylation levels in serum samples from pancreatic cancer patients and healthy controls. Methylated miR-17-5p was detected in all pancreatic cancer patient samples but was either absent or present only at a low level in controls (Fig. 4a). Moreover, miRNA methylation showed better performance in detecting early-stage pancreatic cancer than established biomarkers such as carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA)24 (Fig. 4b, c, See Supplementary Fig. 18, and Supplementary Table 5). Thus, evaluating miRNA methylation and not simply the expression level is a promising diagnostic strategy. To evaluate the methylation of miRNAs as a biomarker, we agree that a relatively large scale study with cancer patients and healthy controls would be necessary for the clinical use. Although the results of this study provide evidence for the biological significance of RNA methylation status in gastrointestinal cancer. Although high-throughput nucleic acid sequencing is currently the gold standard for transcriptome-level analyses, MS enables high-resolution profiling of these chemical modifications, which can aid in the early diagnosis and treatment of cancer. Moreover, elucidating the mechanisms by which methylation regulates miRNA function in the initiation and progression of cancer can lead to the development targeted therapies that can improve patient outcome.