METTL2B m3C RNA Transferase: Oncogenic Role in Ovarian Cancer Progression and its Link to the Tumor Immune Microenvironment

doi:10.21203/rs.3.rs-4935270/v1

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Research Article

METTL2B m3C RNA Transferase: Oncogenic Role in Ovarian Cancer Progression and its Link to the Tumor Immune Microenvironment

https://doi.org/10.21203/rs.3.rs-4935270/v1

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Background

Aberrant expression of N3-methylcytidine methyltransferase 2B (METTL2B) has been observed in various human malignancies, including those of the prostate, liver, breasts, and bladder. However, its role in ovarian cancer (OC) remains largely unexplored. This research preliminarily investigated METTL2B expression in OC and elucidated the associated molecular mechanisms.

Methods

We utilized three publicly available cancer-related databases (Genotype-Tissue Expression, Gene Expression Omnibus, and The Cancer Genome Atlas) to identify gene signatures in patients with OC and normal individuals with a specific focus on METTL2B. The role of METTL2B in OC was evaluated using patient survival data, and its impact on oncogenic behaviors in both cell and animal models, including growth potential, migration, invasion, and the tumor microenvironment, was examined. This assessment was conducted using bioinformatics tools such as Gene Set Cancer Analysis, GeneMANIA, and Tumor Immune Single-cell Hub 2. Additionally, the association between drug sensitivity and METTL2B expression was analyzed using CellMiner.

Results

METTL2B expression was significantly elevated in OC, highlighting its potential clinical value in the diagnosis and prognosis of OC. Patients with lower METTL2B expression exhibited favorable survival. Furthermore, METTL2B knockdown significantly disrupted oncogenic behaviors in OC cell lines by suppressing the mTOR/AKT signaling pathway. Additionally, bioinformatics-based Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses suggested a close correlation between METTL2B and immune responses.

Conclusions

Our research confirmed the upregulation of METTL2B in OC, suggesting its oncogenic function and association with immune infiltration. These findings highlight the significant clinical value of METTL2B in the diagnosis and prognosis of OC.

Ovarian cancer

N3-methylcytidine

METTL2B

Immune infiltration

Ovarian cancer is one of the most life-threatening diseases globally among women older than 40, and it is the second most prevalent type of malignancy in the female population [1]. Global Cancer Statistics 2020 recorded an estimated 313,959 new cases of ovarian cancer, accounting for 1.6% of all new cancer cases. With 207,252 recorded deaths, ovarian cancer ranks as the eighth most life-threatening malignancy worldwide [2]. To date, there are numerous therapeutic treatments for OC including surgery, platinum–taxane chemotherapy [3], targeted therapy [4–8], immunotherapy, and combination strategies [9]. The AKT/mTOR pathway is crucial in OC because of its involvement in tumor invasion and metastasis. Remarkably, the AKT/mTOR pathway was found to be abnormally activated in 70% of patients with OC [10]. This finding provided a basis for combination therapy with first-line anti-cancer therapeutic agents alongside mTOR pathway inhibitors, such as everolimus and temsirolimus [11]. Despite continuous advances in the treatment of OC, overall response rates remain limited. Consequently, the development of reliable indicators for predicting outcomes is urgently needed to better guide treatment strategies for OC.

Epigenetic modifications have garnered increased attention, particularly in the area of RNA modification, because of the emergence of several high-tech and advanced methods such as high-throughput sequencing. Among these, methylation is the most abundant RNA modification. Growing evidence has linked RNA methylation to various human diseases, including cancers [12].

Several eukaryotic RNA modifications are commonly found in the human body, including m6A, m5C, m3C, m1A, and 7G. Recent studies revealed vital roles of m6A [13–16], m5C [17, 18], and m1A [19] in tumor growth, metastasis, recurrence, and drug resistance in OC. However, it remains unclear whether the m3C modification plays a crucial role in tumorigenesis and cancer development.

The methyltransferase-like protein (METTL) family, comprising four members, namely METTL2A, METTL2B, METTL6, and METTL8, is involved in the m3C modification [20]. Among these proteins, METTL6 has been linked to prognosis in several malignancies across various body systems, including the lungs, breasts, and liver [21–23]. Additionally, the methyltransferase activity of METTL8 is enhanced by SUMOylation, leading to R-loop formation and m3C methylation. This process promotes colorectal malignancies [24].

To explore the clinical value of METTL2B in predicting the prognosis of OC, we investigated the role of METTL2B in OC using a bioinformatics strategy. We also evaluated the impact of METTL2B on oncogenic behavior using both in vitro and in vivo OC models with a focus on the AKT/mTOR pathway. Our research found aberrantly elevated METTL2B expression in patients with OC, and its expression was correlated with unfavorable survival outcomes and local immune cell infiltration. This suggests that METTL2B could represent a promising treatment target in OC.

Data acquisition

In this study, clinical data were sourced from OC datasets within TCGA. Gene expression profiles for healthy individuals were obtained from GTEx Portal, a comprehensive public repository of normal tissue and cell-specific gene expression information. The count data contain 60,499 identifiers and 19,109 samples, including 88 normal ovarian samples from GTEx and 427 OC samples from TCGA. In addition to the two aforementioned databases, further information, including data within GSE54388, was obtained from GEO. The raw data extracted from the online databases were subjected to batch processing and normalization with the R package “limma.”

The expression pattern of METTL2B in OC

The differences in ovarian METTL2B expression patterns between patients with OC and healthy individuals, as sourced from the aforementioned publicly available databases, were identified through statistical analyses, including the signed-rank test and Wilcoxon’s rank-sum test.

Survival analysis

The survival of patients with OC was assessed using Kaplan–Meier survival curves and statistical analysis such as the log-rank test.

Correlation between METTL2B expression and its CNV

In this study, the correlation between METTL2B expression in OC and CNV was evaluated using GSCA database, which integrates multiple genomic data across various cancer types from TCGA (http://bioinfo.life.hust.edu.cn/GSCA/) [25].

Functional enrichment analysis

A common computational method, namely GSEA, has been used to analyze large biological datasets. By utilizing gene sets from GO and KEGG, GSEA helps to interpret the biological significance of observed changes in gene expression, linking them to known biological processes and pathways. This analysis began by obtaining the “c2 KEGG gene set” and “c2 REACTOME gene set” GMT files from the MSigDB database. Subsequently, GSEA was conducted by focusing on three gene sets using the R package “clusterProfiler” with threshold criteria set at P < 0.05 and FDR < 0.1. This approach will help us gain a more comprehensive understanding of the functional regulatory mechanisms of METTL2B in OC development.

Stromal and immune scores in tumor samples

The gene signatures of patients with OC, including the METTL2B expression profile in each tumor sample, were identified. Based on these gene expression data, the stromal and immune scores were calculated using ESTIMATE algorithm with the ssGSEA method included in the R package “GSVA”[26]. These scores reflect tumor purity, the presence of stromal cells, and the infiltration level of immune cells in tumor tissues.

Top 20 hub genes associated with METTL2B

GeneMANIA is a bioinformatics tool that can identify other genes associated with a set of input genes based on tumor functional association data such as protein and genetic interactions, pathways, co-expression, co-localization, and protein domain similarity. Using this tool, top 20 hub genes associated with METTL2B were identified. The network of those hub genes was visualized using Cytoscape, an open source software platform for visualizing complex networks.

TISCH2 database

Analysis of the tumor microenvironment (TME) was conducted using TISCH2, an scRNA-seq database focusing on the TME [27]. We explored the expression of METTL2B in each subpopulation after identifying detailed cellular subpopulations by clustering six OC tissues in the GSE147082 dataset through the TISCH2 database.

Prediction of drug sensitivity in patients with OC

The correlation between drug sensitivity (FDA-approved chemotherapeutic agents) and METTL2B expression in patients with OC was investigated using the CellMiner database [28]. Our study found a significant correlation between METTL2B expression and drug sensitivity in patients with OC, suggesting that patients with high METTL2B expression exhibit increased sensitivity to chemotherapy.

Cell culture and human tissue samples

The OC cell lines SK-OV-3 and A2780 and the normal ovarian epithelial cell line IOSE-80 were purchased from Shanghai Zhongqiao Xinzhou Biotechnology Co. Ltd. (Shanghai, China). These cells were maintained in RPMI-1640 culture medium (Gibco, Baltimore, MD, USA) supplemented with 1% penicillin/streptomycin (Beyotime, Shanghai, China) and 10% fetal bovine serum (Procell, Wuhan, China). ES-2, another human OC cell line, was provided by Procell and cultured in a specialized complete medium from the same supplier. All cell lines were cultured at 37°C with 5% CO₂. The purity of these cell lines was confirmed using STR analysis.

Tissue samples from normal ovarian tissues and OC tumors were collected from inpatients at the Second Affiliated Hospital of Harbin Medical University (Harbin, China). The experimental protocol was approved by the Medical Ethics Committee of the Second Affiliated Hospital of Harbin Medical University (approval number: Ky2020-060), and all participants provided informed written consent.

Measurement of METTL2B mRNA expression

METTL2B mRNA expression was measured by qRT-PCR. Total RNA was extracted from samples using Trizol reagent (Invitrogen, Carlsbad, CA, USA), and cDNA was synthesized from 2 µg of total RNA. PCR was performed using the ChamQ SYBR qPCR Master Mix kit (Vazyme, Nanjing, China) on a QuantStudio Real-Time PCR system (Applied Biosystems, Foster City, CA, USA).

The primer pair sequences were as follows:

METTL2B forward primer, 5′-CACCTGCAATCCTCGCCGATAAG-3′; METTL2B reverse primer, 5′-GCTCTTCCGACCACTCCACATTG-3′; 18s rRNA (used as a reference gene) forward primer, 5′-ATCCTCAGTGAGTTCTCCCG-3′; and 18s rRNA reverse primer, 5′-CTTTGCCATCACTGCCATTA-3′.

All primers were obtained from Sangon Biotech (Shanghai, China). METTL2B mRNA expression was normalized to 18s rRNA and analyzed using the 2^−ΔΔCT method.

Silencing of endogenous METTL2B expression using siRNA

To inhibit endogenous METTL2B expression, two siRNAs targeting METTL2B were designed and synthesized by RiboBio (Guangzhou, China): siRNA-1 (sequence: GATGGTACTTCTGCGAGAT) and siRNA-2 (sequence: CGAAGAGCCTTGAACATAA). When the cells reached 50–60% confluency, they were transfected with METTL2B siRNAs using CALNPTM RNAi transfection reagent (D-nano Therapeutics, Beijing, China). The siRNA-transfected cells were harvested at 24 or 48 h post-transfection for functional studies.

Stable silencing of METTL2B expression in OC cells

To stably knockout METTL2B in A2780 cells, METTL2B lentiviral shRNA (shMETTL2B; sequence: AACAAGAGTGAAGTATGT) and its reference shNC (blank lentivirus) were designed and synthesized by GenePharma (Shanghai, China). After transducing shMETTL2B and shNC into cells (24 h), stably transduced cells were selected using 2 µg/mL puromycin for 2 weeks. The surviving cells were harvested, and their lysates were used for western blotting.

Western blotting

To determine the protein levels of METTL2B in human tissue samples and ovarian cell lines, lysates were prepared using RIPA buffer, and protein concentrations were quantified using the BCA protein assay (Beyotime). Proteins were separated by electrophoresis on a 12% SDS-PAGE gel, followed by transfer to a nitrocellulose membrane (Pall, Port Washington, NY, USA). After blocking the membrane at room temperature for 1 h, the blot was incubated overnight at 4°C with primary antibodies against METTL2B and GAPDH (Proteintech, Rosemont, IL, USA), as well as p-mTOR (Ser2448), mTOR, AKT, and p-AKT (Ser473) from Cell Signaling Technology (Danvers, MA, USA). The target protein bands were visualized by incubating the membrane with an HRP-conjugated secondary antibody (ZSGB-BIO, Beijing, China) for 1 h and then briefly exposing the membrane to an ECL kit (Beyotime).

Proliferation potential assessment

The proliferation potential of human OC cell lines was assessed using the 5-ethynyl-2′-deoxyuridine (EdU) incorporation assay (Beyotime). Briefly, 10,000 OC cells were seeded into each well of a 24-well plate. The cells were cultured in medium containing 10 µM EdU for 2 h in an incubator. After incubation, the cells were fixed with 4% paraformaldehyde, permeabilized using 0.3% Triton X-100, and labeled with an anti-EdU working solution. Nuclei were also counterstained with Hoechst 33342. The signals from the EdU-labeled cells were visualized and recorded using an inverted microscope (Olympus IX51).

Colony formation assay

After 24 h of siRNA transfection in A2780 and SK-OV-3 cells, the cells were trypsinized and seeded at a density of 500 cells per well in triplicate in six-well plates. The cells were cultured in a 37°C incubator for 14 days until colonies formed. The colonies were then fixed with methanol and visualized by staining with crystal violet. Colonies containing more than 50 cells were counted to determine the efficiency of colony formation.

Hematoxylin–eosin (HE) staining

To examine histological changes in mouse tumor tissue samples, samples were fixed in 3.7% formalin, embedded in paraffin, and sliced into 5-µm-thick sections. The histological examination utilized various staining methods, including HE staining (Boster Biotech, Wuhan, China). Staining results were observed and recorded using a Zeiss Mirax Slide Scanner.

Immunohistochemistry (IHC)

The 5-µm-thick paraffin sections of tumor tissue were deparaffinized and hydrated using a xylene and graded ethanol series and subjected to antigen retrieval in boiled citrate buffer. Endogenous peroxidase activity was inhibited with 3% H₂O₂ (in methanol), and the samples were blocked with goat serum for 1 h.

Following these steps, the sections were incubated overnight at 4°C with primary antibodies against METTL2B (Proteintech) or Ki67 (ZSGB-BIO). The next day, the sections were washed with PBS and incubated with a secondary antibody (goat anti-rabbit IgG-HRP from ZSGB-BIO) for 1 h at room temperature.

The IHC results were visualized using DAB reagent (ZSGB-BIO) and observed using a Zeiss Mirax Slide Scanner. The positive areas in the sections were quantified using ImageJ software.

Transwell migration and invasion assays

After 24 h of siRNA transfection, cells were trypsinized and seeded into the upper chambers of Transwell plates (Corning, NY, USA) or Matrigel-coated Transwell plates (BD Bioscience, San Jose, CA, USA). Each chamber contained 10,000 cells in 200 µL of serum-free medium. The upper chambers were equipped with an 8-µm pore membrane to permit cell migration or invasion.

After incubation (during which the bottom chamber contained medium supplemented with 10% FBS), cells on the undersurface of the membrane were detected, and the number of migrating or invading cells was counted. Subsequently, the cells were stained with 0.1% crystal violet for visualization and quantification.

OC xenograft animal model

In our study, we developed an OC xenograft animal model by inoculating A2780-shNC or A2780-shMETTL2B cells subcutaneously into female BALB/c nude mice (4–6 weeks old) obtained from Changsheng Biotechnology (Shenyang, China). Each mouse received an injection of 5 × 10⁶ cells into the dorsal skin (seven mice per group).

Tumor volumes were measured every 3 days, and mice were euthanized 4 weeks later after cell inoculation. Then, tumors were dissected and photographed, and their weights were recorded. The experimental animals (SPF-grade) were bred and housed in the Animal Experiment Center of Harbin Medical University.

Statistical analyses

Data analysis in this study was performed using GraphPad Prism 9 (San Diego, CA, USA) and SPSS version 26.0. Statistical differences in continuous data between the groups were assessed using Student’s t-test or one-way ANOVA, whereas nonparametric data were analyzed using Spearman’s test.

Furthermore, the diagnostic value of METTL2B in OC was evaluated using receiver operating characteristic (ROC) curve analysis. Statistical significance between groups was indicated by P < 0.05.

Association of elevated METTL2B expression with poor prognosis in OC

To investigate METTL2B expression in OC, RNA sequencing data were sourced from 427 OC samples within TGCA. Gene expression profiles for 88 normal ovarian samples were obtained from the GTEx Portal. Additionally, we utilized gene microarray profiling data (GSE54388) from GEO, which included 6 normal and 16 OC specimens. Our findings demonstrated that METTL2B expression was significantly elevated in OC samples compared with that in normal tissues (Fig. 1A–B). According to AUC value of 0.801, METTL2B expression can effectively distinguish between OC and normal ovarian tissues (Fig. 1C). Although the difference in PPS between the high and low METTL2B expression groups was not significant, high METTL2B expression tended to be correlated with shorter PFS and worse OS in patients with OC (Fig. 1D).

Consistent with TCGA and GTEx results, METTL2B expression was notably elevated in surgically resected OC tissue samples and normal ovarian tissues (Fig. 1E, Supplementary Fig. S1). Similar trends were also evident when comparing the qRT-PCR and western blotting data between OC cells (A2780 and SK-OV-3) and normal ovarian cells (IOSE-80), as presented in Fig. 1F.

The CNV characteristics of METTL2B in OC

Genomic changes affect tumor development and immune tolerance. To explore the possible causes of METTL2B upregulation in OC, we analyzed CNV related to the METTL2B gene in OC. CNV analysis indicated that METTL2B amplification mutations were present in a majority of patients with OC, and whereas deletion of the METTL2B gene was rare (Fig. 2A). A strong correlation between METTL2B mRNA expression and its gene copy number was revealed through correlation analysis (Fig. 2B). These results suggested that METTL2B gene amplification is a prominent mechanism underlying high METTL2B expression in OC.

Enrichment of METTL2B-associated pathways in OC based on GO and KEGG analysis

To investigate METTL2B-associated biological functions and pathways in OC, our research found 1605 genes positively correlated (r > 0.3, P < 0.05) with elevated METTL2B expression in TCGA database (Supplementary Table S1).

GO analysis of METTL2B-associated 1605 genes highlighted their enrichment in various biological functions, including cytoplasmic ribonucleoprotein granule complexes, methyltransferase activity, chromosome condensation, ATP hydrolysis, DNA replication, RNA splicing, and RNA processing (Fig. 3A–C). A protein–protein interaction (PPI) network constructed using the GeneMANIA database identified the top 20 proteins that interact with METTL2B, including CENPU, MAPK3, METTL2A, NAT16, TPM3, AGK, TRUB2, CMC2, C5orf22, C1D, CSNK2A1, HSPA8, METTL8, METTL6, NSUN2, CCT7, SMG8, GATAD2B, SORCS3, and SLC35B4 (Fig. 3D).

To identify potential pathways associated with METTL2B expression in OC, we used GSEA with KEGG and Reactome as pathway repositories. Through KEGG analysis, we identified several pathways significantly enriched in the high METTL2B expression group, including cell cycle, generation of basal transcription factors, nucleotide excision repair, and RNA degradation (Fig. 4A, Supplementary Table 2). Conversely, low METTL2B expression was significantly correlated with the following pathways: cytotoxicity by natural killer cells and antigen processing and presentation (Fig. 4B, Supplementary Table 2). The analysis based on Reactome indicated that the following pathways were enriched in the high METTL2B expression group: RNA metabolism, cell cycle, FGFR2, TGF-β receptor complex, and mTOR signaling (Fig. 4C and Supplementary Table 3). Conversely, the following pathways were enriched in the low METTL2B expression group: chemokine–chemokine receptor binding, endosomal vacuolar pathway, initial triggering of complement, and regulation of CD22-mediated BCR (Fig. 4D and Supplementary Table 3).

Impact of METTL2B knockdown on oncogenic behaviors in OC: In vitro and in vivo models

Because of the aberrant overexpression of METTL2B observed in OC cell lines and surgical specimens from patients with OC, understanding the underlying mechanisms is crucial. Thus, our study investigated the impact of METTL2B knockdown on oncogenic behaviors in OC. METTL2B expression was silenced using two specific siRNAs in A2780 and SK-OV-3 cells. Following METTL2B knockdown, both the mRNA and protein levels of METTL2B were significantly reduced compared with those in siNC-transfected control cells (Fig. 5A–B). Following METTL2B knockdown, we observed significant reductions in the proliferation, migration, and invasion capabilities of OC cells. This was evidenced by decreased colony formation potential (Fig. 5C), reduced EdU incorporation (Fig. 5D), and impaired migration and invasion (Fig. 5E).

In addition to the observed positive results in the OC cell model, we further investigated the impact of METTL2B knockdown on oncogenic behaviors using an in vivo OC model. To achieve this, we established an OC xenograft animal model by subcutaneously inoculating A2780-shNC or A2780-shMETTL2B cells into female BALB/c nude mice (seven mice per group). Tumor volumes were measured every 3 days, and the mice were euthanized 4 weeks later. Tumors were dissected, photographed, and weighed. Our findings revealed significant reductions in tumor size and weight in the METTL2B-silenced groups compared with those in the control mice (Fig. 6A–B). Furthermore, IHC highlighted a decrease in Ki67 expression in the tumor areas of nude mice injected with A2780-shMETTL2B cells compared with the findings in mice injected with A2780-shNC cells (Fig. 6C). To verify the METTL2B shRNA efficiency, METTL2B protein expression was examined by western blotting in A2780-shMETTL2B cells (Fig. S2). Overall, our results underscore the oncogenic role of METTL2B in OC tumorigenesis.

METTL2B silencing suppressed the AKT/mTOR pathway in OC

Based on prior bioinformatics analysis, elevated METTL2B expression was found to be correlated with activation of the mTOR signaling pathway. It has been demonstrated that dysregulation of the PI3K/AKT signaling pathway, in which mTOR acts as a crucial kinase downstream, is correlated with progression and drug resistance in ovarian cancer [29, 30].

To explore the relationship of METTL2B with the AKT/mTOR pathway, we conducted western blotting. Following METTL2B silencing in both A2780 and SK-OV-3 cells, we assessed the expression of p-AKT (Ser473), p-mTOR (Ser2448), total AKT. and total mTOR. Western blotting demonstrated that p-AKT (Ser473) expression, but not total AKT expression, was significantly decreased in both cell lines following METTL2B knockdown. We also observed a significant decrease in p-mTOR (Ser2448) expression, but not total mTOR expression, in both cell lines upon METTL2B silencing (Fig. 7A). In addition, the ratios of p-AKT/AKT and p-mTOR/mTOR in mouse tumor tissue samples were examined using western blotting, revealing similar results to those observed in the cell model (Fig. 7B).

Immune characteristics of METTL2B in OC

To explore the interplay between METTL2B and the TME, we utilized the ESTIMATE algorithm to calculate ESTIMATE scores across TCGA-OC samples, for which the levels of infiltrating stromal and immune cells were predicted according to gene signatures. Our analysis revealed that METTL2B expression was negatively correlated with the stromal (r = − 0.143), immune (r = − 0.301), and ESTIMATE scores (r = − 0.246, Fig. 8A–C).

Further investigation using ssGSEA highlighted a complex relationship between METTL2B expression and immune cell infiltration. Specifically, METTL2B expression was positively correlated with infiltrating immune cells, such as Tcm and helper T cells, but negatively correlated with the infiltration scores of multiple immune cells, including cytotoxic cells, T cells, CD56^dim NK cells, activated dendritic cells (aDCs), helper follicular T cells (Tfh), Th1 cells, immature dendritic cells (iDCs), CD8⁺ T cells, CD56^bright NK cells, dendritic cells, regulatory T cells, mast cells, macrophages, B cells, neutrophils, Th17 cells, eosinophils, and γδ T cells (Fig. 8D).

Exploring single-cell gene expression in the TME

To analysis the relationship between METTL2B and the TME, a single-cell gene expression dataset (TISCH2) was used in our research. We leveraged TISCH2 and selected GSE17048, focusing on six patients with OC and omental metastasis (Supplementary Table 4). Through clustering analysis, we categorized the single-cell samples into 25 distinct clusters (Fig. 9A). Subsequently, these clusters were annotated into 10 cell types, encompassing proliferating T cells, plasma cells, myofibroblasts, monocytes or macrophages, malignant cells, endothelial cells, CD8 T cells, conventional CD4 T cells, and B cells (Fig. 9B). Each patient with OC exhibited a unique distribution of these 10 cell types (Fig. 9C). Notably, METTL2B expression was prominently elevated in malignant cells compared with the findings in the other identified cell types (Fig. 9D).

Impact of METTL2B expression on anticancer drug sensitivity

To explore the relationship between METTL2B expression and the susceptibility to anticancer therapeutic agents, we utilized the CellMiner database to identify seven drugs significantly correlated with METTL2B expression. As depicted in Fig. 10, METTL2B was positively correlated with the susceptibility to calusterone, XL-147, vismodegib, vorinostat, fenretinide, nelarabine, and testolactone.

OC is the most fatal gynecological malignancy [31, 32]. Early detection continues to be a major hurdle, as nearly half of all patients with OC are diagnosed at advanced stages, frequently presenting with metastases dispersed throughout the peritoneal cavity. Consequently, the prognosis and OS rates for these patients are typically dismal [33, 34]. In response, there has been a shift toward molecular targeted epigenetic therapies, which consider the varied epidemiological and genomic characteristics of different OC tissue types [35]. Among epigenetic modifications, the m6A modification is particularly notable for its regulatory role in gene transcription, influencing OC progression and resistance to treatment. Furthermore, therapies targeting m6A regulatory factors have displayed promise in enhancing the tumor-suppressive effects of chemotherapy [36, 37].

The m3C modification is frequently found in the anticodon loop at position 32 of certain eukaryotic cytoplasmic and mammalian mitochondrial tRNAs, including tRNA^Thr, tRNA^Ser, and some tRNA^Arg species. To date, research has only identified the specific methyltransferases that catalyze the m3C modification at this position in eukaryotic cytoplasmic tRNA^Thr, tRNA^Ser, and tRNA^Arg [20, 38–40]. Among mammals, enzymes such as METTL2, METTL6, and METTL8 are recognized for their m3C activity. METTL2A and METTL2B, which are closely related variants of METTL2 differing by only six amino acids, have been extensively studied [20]. However, investigations revealed that the m3C32 modification activity of METTL2B is significantly weaker than that of METTL2A in vitro [41].

Previous research revealed a uniform expression pattern for the four m3C-associated genes (METTL2A, METTL2B, METTL6, METTL8) across various cancer types, including hepatocellular carcinoma, esophageal carcinoma, colon adenocarcinoma, endocervical adenocarcinoma, and cervical squamous cell carcinoma [21, 23, 42]. These findings suggest that these genes function as oncogenes in these malignancies. In our research, we specifically examined METTL2B and its oncogenic roles in OC, offering new insights into its potential mechanisms in promoting OC development. Our analyses, utilizing data from TCGA, GTEx, and GEO databases, demonstrated for the first time that METTL2B expression is significantly higher in OC tumor samples than in normal ovarian tissue. Furthermore, the AUC of METTL2B in OC reached 0.801, underscoring its substantial diagnostic potential for distinguishing between tumor and normal tissues. It is important to note that patients with OC and high METTL2B expression exhibited shorter PFS.

The results of qRT-PCR and western blotting confirmed the remarkable overexpression of the METTL2B gene in both OC surgical specimens and two human OC cell lines, consistent with our bioinformatics results. Further studies indicated that the increased expression of METTL2B in OC might result from amplification mutations, as detailed in the GSCA database.

The molecular and biological properties of METTL2B in OC were deliberately investigated through GO and KEGG enrichment analyses, highlighting METTL2B-associated critical biological functions and pathways, such as RNA metabolism, cell cycle regulation, FGFR2 signaling, TGF-β receptor complex signaling, and the mTOR signaling pathway. In particular, the AKT/mTOR signaling pathway is known to play a pivotal role in OC progression, contributing to tumor growth, cancer cell migration and invasion, and heightened resistance to chemoradiotherapy [10]. Further exploration of METTL2B’s oncogenic effects was conducted using in vitro and in vivo models. The results demonstrated that METTL2B knockdown could significantly curtail oncogenic behaviors in OC cells, including aspects such as proliferation, migration, and invasion. Additionally, this intervention led to a marked reduction in the activity of p-AKT (Ser473) and p-mTOR (Ser2448).

These results suggest that METTL2B, acting as an oncogene, could be a valuable indicator for OC diagnosis and prognosis prediction. Nevertheless, the specific molecular mechanisms by which METTL2B influences the m3C modification in cancer development and progression are yet to be fully determined.

A growing body of research has linked tumor immune infiltration to patient prognosis across various cancers. However, the role of METTL2B within the TME of OC was not previously documented. Our investigation delved into the immune properties of METTL2B in OC, assessing factors such as immune cell infiltration and single-cell type annotation within the TME. Our findings revealed inverse relationships of METTL2B expression with stromal, immune, and ESTIMATE scores. We observed a positive association between METTL2B expression and the infiltration of Tcm and helper T cells. However, METTL2B expression was negatively associated with the infiltration of various immune cells, including Tfh cells, Tfh cells, Th1 cells, iDCs, CD8⁺ T cells, CD56^bright NK cells, regulatory T cells, macrophages, and B cells.

It has been reported that tumor-infiltrating lymphocytes (TILs) in the TME are associated with better outcomes in OC [43]. Recent studies indicated that in high-grade serous carcinoma (HGSC), a high proportion of CD56^brightCD16⁻ NK cells in the ascites is associated with extended PFS and OS, whereas a high macrophage count was correlated only with improved OS. This suggests that METTL2B overexpression suppresses the immune activity of tumor-infiltrating cells, potentially accelerating the progression and severity of OC. On the contrary, elevated METTL2B expression could suppress the cytotoxic effects of TILs on tumors and reduce OC [44].

Additionally, a close relationship between METTL2B expression and susceptibility to chemotherapeutic agents was validated in this research based on drug sensitivity analysis, underscoring the potential of METTL2B as a therapeutic target for OC. These findings collectively underscore the significant link between METTL2B expression and tumor immunity in OC.

In conclusion, our study demonstrated that METTL2B expression is significantly elevated in OC, and this elevation is associated with decreased PFS. Silencing METTL2B was found to inhibit the malignant progression of OC by reducing AKT/mTOR signaling activity. Additionally, METTL2B appears to influence immune cell infiltration within the TME. Collectively, these results indicate that METTL2B might function as an oncogene, playing a crucial role in the malignant progression and interacting with the TME in OC.

Ovarian cancer (OC), N3-methylcytidine methyltransferase 2B (METTL2B), The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Genotype-Tissue Expression (GTEx), gene set enrichment analysis (GSEA), Tumor Immune Single-cell Hub 2 (TISCH2), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), N6-methyladenosine (m6A), 5-methylcytidine (m5C), N3-methylcytosine (m3C), N1-methyladenine (m1A), and 7-methylguanosine (m7G), methyltransferase-like protein (METTL), tumor microenvironment (TME), copy number variation (CNV), Gene Set Cancer Analysis (GSCA), Estimation of Stromal and Immune Cells in Tumor Tissue (ESTIMATE), protein–protein interaction (PPI), immunohistochemistry (IHC), post-progression survival (PPS), overall survival (OS), progression-free survival (PFS), tumor-infiltrating lymphocytes (TILs), high-grade serous carcinoma (HGSC), short tandem repeat (STR) analysis，quantitative real-time PCR (qRT-PCR), the area under the curve (AUC), and small interfering RNA (siRNA)

Ethics approval and consent to participate

The use of human tissues for our experiments received approval from the Ethics Committee of the Second Affiliated Hospital of Harbin Medical University (Harbin, China), with informed consent obtained from all participants. Furthermore, the Animal Ethics Committee of the Second Affiliated Hospital of Harbin Medical University (Harbin, China) approved all procedures involving animals.

Consent for publication

Not applicable.

Availability of data and materials

Data supporting the results of this study are available in the paper and its supplementary information file. All original data are available from the corresponding author upon reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This research was supported by the National Natural Science Foundation of China (NO. 82072864).

Authors’ contributions

Y.Z.M. and J.H. contributed to the conception. Y.Z.M. and Y.M.M. devised the research. H.Z. and J.R.H. collected the clinical samples. Y.Z.M. and Y.M.M. performed the experiments. Y.Z.M. and Y.M.M. analyzed and interpretated the data. Y.Z.M., Y.M.M., and Y.H.S. drafted the paper. P.L.L., Y.H.S., and J.H. submitted the published version for final approval. All authors read and approved the final manuscript.

Acknowledgements

The authors extend their sincere gratitude to the core facility staff at the First Hospital of Jilin University and Harbin Medical University for their invaluable training and guidance. We thank Medjaden Inc. for their scientific editing and proofreading of this manuscript.

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No competing interests reported.

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METTL2B m3C RNA Transferase: Oncogenic Role in Ovarian Cancer Progression and its Link to the Tumor Immune Microenvironment

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Materials and methods

Data acquisition

The expression pattern of METTL2B in OC

Survival analysis

Correlation between METTL2B expression and its CNV

Functional enrichment analysis

Stromal and immune scores in tumor samples

Top 20 hub genes associated with METTL2B

TISCH2 database

Prediction of drug sensitivity in patients with OC

Cell culture and human tissue samples

Measurement of METTL2B mRNA expression

Silencing of endogenous METTL2B expression using siRNA

Stable silencing of METTL2B expression in OC cells

Western blotting

Proliferation potential assessment

Colony formation assay

Hematoxylin–eosin (HE) staining

Immunohistochemistry (IHC)

Transwell migration and invasion assays

OC xenograft animal model

Statistical analyses

Results

Association of elevated METTL2B expression with poor prognosis in OC

The CNV characteristics of METTL2B in OC

Enrichment of METTL2B-associated pathways in OC based on GO and KEGG analysis

Impact of METTL2B knockdown on oncogenic behaviors in OC: In vitro and in vivo models

METTL2B silencing suppressed the AKT/mTOR pathway in OC

Immune characteristics of METTL2B in OC

Exploring single-cell gene expression in the TME

Impact of METTL2B expression on anticancer drug sensitivity

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1