YTHDF3 modulates the progression of breast cancer cells by regulating FGF2 through m6A methylation

doi:10.21203/rs.3.rs-3721424/v1

Download PDF

Research Article

YTHDF3 modulates the progression of breast cancer cells by regulating FGF2 through m6A methylation

https://doi.org/10.21203/rs.3.rs-3721424/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background

Breast cancer (BC) is a prevailing malignancy among women, and its inconspicuous development contributes significantly to mortality. The RNA N6-methyladenosine (m⁶A) modification represents an emerging mechanism for gene expression regulation, with the active involvement of the YTH N6-methyladenosine RNA binding protein 3 (YTHDF3) in tumor progression across multiple cancer types. Nonetheless, its precise function in breast cancer necessitates further investigation.

Methods

The expression of YTHDF3 in both cell lines and patient tissues was examined using Western blotting, reverse transcription quantitative PCR (RT-qPCR), and immunohistochemistry (IHC) techniques. Bioinformatics analysis of methylated RNA immunoprecipitation sequencing (MeRIP-seq) and transcriptome RNA sequencing (RNA-seq) data was employed to screen for the target genes of YTHDF3. The main focus of this study was to investigate the in vitro biological functions of YTHDF3. The specific binding of YTHDF3 to its target genes and its correlation with m⁶A methylation were studied through RNA pull-down, RNA immunoprecipitation, and co-immunoprecipitation experiments. The protein regulatory mechanisms of downstream genes of YTHDF3 were assessed using protein stability analysis. Furthermore, the biological functions of YTHDF3 and its target genes in breast cancer cells were validated through CRISPR-Cas9 technology and rescue experiments.

Results

By constructing a risk model using the TCGA database, YTHDF3 was identified as a high-risk factor among m⁶A methylation factors. Subsequent investigations revealed its elevated expression in various subtypes of breast cancer, accompanied by poor prognosis. MeRIP-seq analysis further revealed fibroblast growth factor 2 (FGF2) as a downstream gene of YTHDF3. Knockdown of YTHDF3 in breast cancer cells led to significant inhibition of cell self-renewal, migration, and invasion abilities in vitro. Mechanistically, YTHDF3 specifically recognized the methylated transcript of FGF2 within its coding sequence (CDS) region, leading to the inhibition of FGF2 protein degradation. Moreover, depletion of FGF2 markedly suppressed the biological functions of breast cancer cells, while reducing FGF2 expression in YTHDF3-overexpressing breast cancer cell lines substantially alleviated the malignant progression.

Conclusions

In summary, our study elucidates the role of YTHDF3 as an oncogene in maintaining FGF2 expression in BC cells through an m⁶A-dependent mechanism. Additionally, we provide a potential biomarker panel for prognostic prediction in BC.

Breast Caner

N6-methyladenosine

YTHDF3

FGF2

N6-Methyladenosine (m⁶A) is the most prevalent and frequent internal post-transcriptional modification discovered in eukaryotic messenger RNAs (mRNAs). This crucial epigenetic component plays a significant role in regulating gene expression through a reversible process. m⁶A is involved in the regulation of various cellular functions, including differentiation, self-renewal, invasion, and apoptosis ^1–3. The methylation of m⁶A is carried out by a methyltransferase complex, which includes METTL3, METTL14, WTAP, VIRMA, RBM15, and ZC3H13, referred to as “writers” of this modification. Conversely, the m6A modification can be removed by demethylases, namely FTO or ALKBH5, referred to as "erasers" ⁴. The m⁶A modification is recognized by “readers” proteins that play a role in regulating RNA metabolism, including translation, splicing, export, and degradation ⁵. Therefore, m⁶A modifications are responsible for regulating the functions of mRNAs, microRNAs, and lncRNAs ^4,6. “Readers” proteins containing the YT521-B homology (YTH) structural domain, such as YTHDF1-3, YTHDC1, and YTHDC2, specifically recognize m⁶A modifications and are responsible for the regulation of m6A-modified mRNAs ⁷.

Numerous studies have provided evidence for a strong association between m⁶A methylation modifications and the progression of human cancers ⁸. For instance, FTO, the m⁶A demethylase, has been identified as a prognostic factor that promotes cell proliferation and invasion in lung squamous cell carcinoma (LUSC)⁹. Moreover, ALKBH5, another m⁶A demethylase, exhibits high expression in Glioblastoma stem-like cells (GSCs), and the decreased expression of a combination of ALKBH5 and FOXM1-AS interferes with GSC tumorigenesis through the FOXM1 axis¹⁰. In vitro and in vivo studies have demonstrated the essential role of METTL3 in epithelial-mesenchymal transition (EMT) and metastasis of gastric cancer¹¹ .

In 2020, breast cancer surpassed lung cancer to become the most prevalent malignancy worldwide¹². he identification of effective targets and the study of molecular mechanisms underlying breast cancer development and progression have become crucial areas of investigation in ongoing research. Breast cancer is a complex and multifactorial disease characterized by somatic gene mutations, copy number aberrations, alterations in exon sequencing, changes in miRNA and protein expression levels, and modifications in DNA methylation¹³. Epigenetic research has gained increasing attention, offering new insights and avenues for studying breast cancer progression. By focusing on the genetic and epigenetic differences, novel directions and innovative ideas for breast cancer research can be discovered¹⁴.

Initially, we noted that YTHDF3 expression was abnormally upregulated in breast cancer and that it played a crucial role in breast cancer cell growth and metastasis. Analysis of multiple biomolecules revealed that fibroblast growth factor 2 (FGF2) is directly targeted by YTHDF3 in breast cancer cells. YTHDF3 controls the translation of FGF2 in an m⁶A-dependent manner, which affects the malignant progression of breast cancer cells. Our data provide evidence that the m⁶A reader YTHDF3 plays a critical oncogenic role in the development of breast cancer.

Sources of the sequencing data

The RIP-seq and m⁶A-seq data for this study can be accessed from NCBI GEO DataSets with the accession numbers GSE130171 and GSE130172. The mRNA sequence data for the shYTHDF3 can be found at NCBI GEO DataSets with the accession number GSE124817¹⁵.

Cell Culture

293T and MCF-10A cells were procured from the National Cell Resource Center (Shanghai, China). MCF-7 and MDA-MB-231 cells were purchased from Zhong Qiao Xin Zhou Biotechnology (Shanghai, China). All cell types were cultured in DMEM (GIBCO, USA) supplemented with 10% FBS (BI, USA) at 37°C with 5% CO₂ in a cell incubator.

Plasmids

To utilize shRNAs for lentivirus-mediated interference, complementary sense and antisense oligonucleotides that encode shRNAs targeting YTHDF3 were synthesized, annealed, and cloned into the pLKO.1 vector. To construct the YTHDF3 overexpression plasmid, the YTHDF3 gene was cloned into the pCDH-CMV-MCS-EF1-copGFP vector. To construct the YTHDF3-wt (YTHDF1-FLAG) and YTHDF3-mut (W438A, W492A) expression plasmids, they were cloned into pCDH vector. To construct a Knockdown FGF2 plasmid, it was synthesized to encode targeting FGF2 sgRNAs that were annealed and cloned into lentiCRISPR v2 (#52961, Addgene). Synthesized shRNAs and sgRNA-related sequences are shown in Supplementary Table S1. pLKO.1 and pCDH-CMV-MCS-EF1-copGFP were obtained from ige biotechnology ltd (Guangzhou, China )

Cell transfection and lentiviral infection

For transient transfection, Lipofectamine 3000 (Invitrogen, USA) was used to transfect cells with external pressure vectors. HEK293T cells were co-transfected with lentiviral vectors, including packaging vectors psPAX2 (#12260, Addgene) and pMD2.G (#12259, Addgene), using lipofectamine LTX (Invitrogen, USA) for lentivirus production. Infectious lentiviral particles were harvested from cells 48 hours post-transfection, filtered through 0.45 µm PVDF filter, and transfected into other cells.

RNA isolation and RT-qPCR

Total RNA was extracted using Trizol (Invitrogen, USA) as per the manufacturer’s instructions from cells and tissues. In RT-qPCR, cDNA was obtained by reverse transcription of RNA using a Reverse Transcription Kit (Takara, Japan). The levels of RNA transcripts were analyzed using the Bio-rad CFX96 real-time PCR system (Bio- rad, USA). GAPDH were used to normalize all samples. Supplementary Table S1 contains the all of the primers used in RT-qPCR.

Western blot and Co-IP

MCF-7 or MDA-MB-231 cells were rinsed twice with cold phosphate-buffered saline (PBS) and then centrifuged. Afterward, the pellet was resuspended in lysis buffer and incubated on ice with frequent vortex for 10 min. Finally, the lysate was obtained by centrifugation at 12,000 g for 10 min. SDS-polyacrylamide gel electrophoresis (PAGE) was used to fractionate the proteins, and were later transferred onto polyvinylidene fluoride (PVDF) membranes. The membranes were then blocked with 5% nonfat milk in TBST and blotted with specific antibodies. Antibodies used were anti-YTHDF3(1:2000, Abcam), anti-GAPDH (1:10000, Abcam), anti-FGF2 (1:2000, Abcam), and anti-FLAG-tag (1:1000, Sigma-Aldrich).

For co-IP, cell lysates containing 1 x 10⁷ cells were immunoprecipitated with IP buffer containing agarose beads coupled to IP antibodies. Protein-protein complexes were detected by Western blot. IgG was used as a negative control.

Cell growth and proliferation assay

Cell viability was assessed by adding 10% CCK8 (DOJINDO, Japan) to infected cells in 96-well plates. The cells were then incubated at 37°C for 2 hours at 0, 24, 48, 72, and 96 hours, respectively. All experiments were replicated three times.

For colony formation assays, each well of a six-well plate was cultured with 1 × 10³ MCF-7 or 1 × 10³ MDA-MB-231 infected cells, and the medium was replaced every three days. After ten days, colonies were fixed with paraformaldehyde, stained with 0.1% crystal violet (Solarbio, China) for 30 minutes, and rinsed with PBS. The number of colonies with more than 50 cells was the count.

Cell migration and invasion assay

The migration assays were carried out by using a 24-well Transwell chamber system (Corning, USA). In a 24-well plate, breast cancer cells were seeded in the top chamber of an insert, which contained 0.4 ml of serum-free medium. The lower chamber was filled with 0.6 ml of medium, which contained 20% FBS. Following a 24-hour incubation period, the cells were fixed with paraformaldehyde for 15 minutes, and subsequently stained with 0.1% crystal violet (Solarbio, China) for 30 minutes. Following rinsing with water, the membranes of the chambers were mounted and then covered on the slides. To perform the invasion assay, we applied Matrigel (BD, USA) on the 24-well Transwell cell chamber system (Corning, USA) and the upper chamber of the inserts before transplanting the cells. We imaged and counted the migrated or invaded cells under a 20 X microscope.

Apoptosis assay

Following the manufacturer’s guidelines, cellular staining was performed using the Cell Apoptosis Assay Kit (Multisciences, China). Subsequently, flow cytometric analysis of the stained cells was carried out using the BD flow cytometer.

RNA Immunoprecipitation (RIP)

The cells were washed twice in PBS, harvested, and resuspended in IP lysis buffer (150mM KCl,25mM Tris (pH 7.4), 5mM EDTA, 0.5mM DTT, 0.5% NP40, 1× protease inhibitor, and 1U RNase inhibitor). Following a 30-minute incubation, centrifugation of the lysate occurred at 12,000 g for 10 minutes. Then, the lysate was incubated with antibodies and 40 µl protein G beads (Thermo Fisher, USA) overnight at 4^◦C. Following three washes with the washing buffer (150 mM KCl, 25 mM Tris (pH 7.4), 5 mM EDTA, 0.5 mM DTT, 0.5% NP40), RNA co-precipitated with the lysate was extracted with Trizol's reagent, while ethanolwas made use of for precipitating glycogen (Invitrogen, USA.). The degree of RNA enrichment was normalized with that of IgG.

Vector and m ⁶ A mutation assays

The potential m⁶A sites were predicted using an online tool, SRAMP (http://www.cuilab.cn/sramp/). the FGF2 CDS region, and the m⁶A motif depleted CDS regions were cloned into pcDNA3.1 for the RNA pull-down assay.

RNA pull-down

The Pierce Magnetic RNA-Protein Pull-down Kit (Thermo Fisher Scientific) was used to perform the RNA pull-down assay. More specifically, we used biotin-labeled FGF2-WT, FGF2-Mut, YTHDF3, and YTHDF3-Mut RNA in the assay. MCF-7 cell lysates were incubated with biotin-labeled RNA on magnetic beads at 4°C overnight. After washing with appropriate buffer, purification was performed. The relevant proteins were detected by Western blot analysis.

Protein stability

Protein stability of breast cancer cells was evaluated by treating them with 100 µg/ml CHX and 10m/ml MG132 for the indicated time intervals. The cells were then harvested. Protein expression of either FGF2 or YTHDF3 was determined by western blot analysis.

Statistics

Linux, the R platform, and GraphPad Prism 8 were used for analysis. Statistical analysis was performed using the R platform. The relevant data were obtained from three replicate experiments. The results are presented as mean ± standard deviation. Differences between the two groups were analyzed using paired two-tailed Student's t-test, one-way ANOVA, and chi-square test.

YTHDF3 is highly expressed in BRCA and associated with poor prognosis

In order to assess the risk factors associated with m⁶A regulators in breast cancer (BRCA), we conducted an analysis of The Cancer Genome Atlas (TCGA) database. Our examination revealed the significance of YTH N6-methyladenosine RNA-binding protein (YTHDF3) in constructing a risk model for breast cancer (Supplementary Figure.1). Notably, YTHDF3 exhibited significant expression and correlation with different subtypes of breast cancer within the TCGA database (Figure.1A). Furthermore, elevated levels of YTHDF3 expression were consistently associated with a poorer prognosis in terms of survival (Figure.1B). These distinct expression patterns of YTHDF3 prompted further investigation into its functional and clinical implications in BRCA. We observed increased protein levels of YTHDF3 in BRCA cell lines compared to normal mammary epithelial cell lines (MCF-10A). Moreover, both YTHDF3 protein and mRNA levels were significantly elevated in the majority of BRCA patient tissues when compared to normal tissues (Figure.1C D F). To evaluate the clinical significance of YTHDF3 in BRCA, we performed immunohistochemical (IHC) staining for YTHDF3 on tissue samples obtained from Guizhou Provincial Tumor Hospital (Figure.1E). Our findings demonstrated an intensified YTHDF3 staining, which indicates an increased malignancy. Collectively, these results suggest that the m⁶A reader YTHDF3 is overexpressed in breast cancer and is associated with a poor prognosis in breast cancer patients.

YTHDF3 plays an oncogenic role in breast cancer cells

In order to elucidate the role of YTHDF3 in breast cancer, our study aimed to investigate the cellular changes occurring in breast cancer cells following YTHDF3 knockdown. Successful knockdown of YTHDF3 was achieved in MCF-7 and MDA-MB-231 breast cancer cells using siRNAs (siY3-1 and siY3-2) (Figure. 2A). Moreover, CCK8 assays demonstrated a significant impairment in cell growth upon YTHDF3 knockdown in both MCF-7 and MDA-MB-231 cells (Figure. 2B). Furthermore, the wound healing assay revealed a notable decrease in the scratch healing ability of breast cancer cells following YTHDF3 knockdown (Figure. 2C). Additionally, the cell colony formation assay exhibited a significant inhibition in the ability of cells to form colonies after YTHDF3 knockdown (Figure. 2E). Furthermore, the cell migration and invasion assays indicated that YTHDF3 knockdown impaired the migration and invasion abilities of both MCF-7 and MDA-MB-231 cells. These findings collectively highlight the pivotal role of YTHDF3 in the proliferation, migration, and invasion of breast cancer cells, suggesting its potential as a pro-oncogenic factor in breast cancer progression.

Identification of FGF2 as a target of YTHDF3 in breast cancer

In order to uncover the underlying mechanisms of YTHDF3 in breast cancer occurrence and development, we initially conducted an analysis of RNA-seq datasets of YTHDF3 knockout cells and control cells available in the literature¹⁵. The knockout of YTHDF3 led to comprehensive alterations in gene expression (Figure S2.A). Gene ontology (GO) analysis revealed enrichment in several pathways, including the MAPK signaling pathway, VEGF signaling pathway, and protein processing in the endoplasmic reticulum (Figure S2.B). Additionally, gene set enrichment analysis (GSEA) demonstrated that the genes affected by YTHDF3 were associated with MicroRNAs in cancer, Lipid and atherosclerosis, MAPK signaling pathway, and protein processing in the endoplasmic reticulum (Figure S2.C-F), providing further support for the regulatory role of YTHDF3 in breast cancer tumorigenesis.

YTHDF3, a widely recognized m⁶A “readers”, exerts its function by interacting with and modulating m⁶A methylated transcripts. By analyzing meRIP-seq data from the literature¹⁵, we observed the existence of an m⁶A binding domain between FGF2 and YTHDF3, as depicted in the IGV plot (Figure S2.G H). This finding indicates that FGF2 could potentially be a downstream target of YTHDF3, subject to regulation through m⁶A methylation. To further investigate the relationship between FGF2 and YTHDF3, RNA immunoprecipitation followed by quantitative PCR (RIP-qPCR) confirmed the interaction between YTHDF3 and FGF2 mRNA in MCF-7 and MDA-MB-231 breast cancer cells (Figure .4F).

YTHDF3 enhances FGF2 protein stability via an m ⁶ A-dependent manner

In previous studies, the YTH family has been implicated in playing specific roles in controlling the fate of mRNA methylation^16,17. To elucidate the specificity of FGF2 as an m⁶A reader and determine the m⁶A-dependent regulatory mechanism of FGF2, we first examined the transcription and translation of FGF2 after YTHDF3 depletion. As expected, silencing YTHDF3 with shRNAs in MCF-7 and MDA-MB-231 breast cancer cells resulted in a reduction in FGF2 protein levels without affecting its RNA levels (Figure.3A B). The decrease in FGF2 protein levels rather than mRNA levels in the absence of YTHDF3 led us to speculate that YTHDF3 may regulate the stability or translation efficiency of FGF2 protein. To validate this, control or YTHDF3-depleted breast cancer cells were treated with the protein translation inhibitor cycloheximide (CHX). Western blot analysis revealed an enhanced stability of FGF2 protein in YTHDF3 knockout MCF-7 and MDA-MB-231 cells, which was significantly reversed by the proteasome inhibitor MG132, indicating the impact of YTHDF3 depletion on FGF2 protein (Figure.3K M). Therefore, we discovered that YTHDF3 functions by enhancing the stability of FGF2 protein. Our next question is whether the regulation of FGF2 expression by YTHDF3 depends on m⁶A methylation. It is known that YTHDF3 can bind to m⁶A sites through its m⁶A-binding domain in the YTH domain, and mutations at W438 and W492 weaken the binding ability of YTHDF3 with mRNA¹⁵. By introducing point mutations W438A and W492A in the YTH domain of YTHDF3 tagged with FLAG (YTHDF3-OE-mut), breast cancer cells were transfected with constructs expressing YTHDF3 wild-type (YTHDF3-OE-wt) and YTHDF3 mutant (YTHDF3-OE-mut) (Figure.3C). Subsequently, RNA immunoprecipitation (RIP) using FLAG antibody followed by qPCR demonstrated that cells transfected with YTHDF3-wt effectively immunoprecipitated FGF2 mRNA, while the interaction between YTHDF3 mutant and FGF2 mRNA was significantly reduced (Figure.3E), indicating the crucial importance of the m⁶A-binding domain for the interaction between YTHDF3 and FGF2 mRNA. Importantly, we observed that YTHDF3-OE-wt, but not YTHDF3-OE-mut, increased the protein expression of FGF2 (Figure.3D). It is noteworthy that RNA pull-down assays revealed that FGF2 primarily binds to the YTHDF3 coding sequence (CDS) region in MCF-7 cells, and the specific binding was significantly weakened when the m⁶A-binding region was deleted (Figure.3G). Reverse pull-down experiments with mutations in the predicted m⁶A-binding domain of FGF2 showed a significant reduction in specific binding when the m⁶A-binding domain of FGF2 was mutated (Figure.3H), further validating the role of YTHDF3 in regulating FGF2 protein expression through m⁶A methylation. Co-immunoprecipitation (Co-IP) and Western blot analysis using Flag-tagged YTHDF3 demonstrated a significant reduction in specific binding between FGF2 and YTHDF3 when the m⁶A-binding domain was mutated (Figure.3I). Furthermore, reverse FGF2 pull-down experiments further confirmed the interaction between YTHDF3 and FGF2 and its regulation through m⁶A methylation (Figure.3J).

In summary, our data demonstrate that the FGF2 transcript is directly recognized by the m⁶A “reader” YTHDF3. FGF2 maintains transcript stability through an m⁶A-YTHDF3-dependent mechanism, preventing degradation and naturally increasing its expression.

The downregulation of FGF2 inhibits the malignant progression of breast cancer cells

Due to the unclear role of FGF2 in breast cancer cells, we first employed CRISPR-Cas9 technology to target and knockout FGF2. Western blot analysis revealed that the expression of YTHDF3 was not significantly affected upon FGF2 knockout (Figure.4A). Notably, both cell growth and colony formation abilities of these two breast cancer cell lines were significantly inhibited after FGF2 knockout (Figure.4B E). Furthermore, the loss of FGF2 re-induced the migration and invasion of breast cancer cells (Figure.4D). Concurrently, scratch assays indicated that the wound healing ability was diminished after FGF2 knockout (Figure.4C). To further investigate the impact of FGF2 on the cell cycle of breast cancer cells, flow cytometry analysis revealed that FGF2 knockout arrested MCF-7 and MDA-MB-231 cells in the S phase and induced early apoptosis in both cell lines (Figure.4F). These findings suggest that the downregulation of FGF2 inhibits tumorigenesis in breast cancer cells.

The protein blotting results demonstrated that siFGF2-1 exhibited the strongest silencing effect. Therefore, siFGF2-1 was selected for subsequent experiments (Figure.5A). We knocked down the expression of FGF2 in MCF-7 and MDA-MB-231 cells overexpressing YTHDF3, and observed alterations in FGF2 levels in both cell lines (Figure.5B). For subsequent cell biology experiments, we designed NC (negative control), 1# (OE-YTHDF3), and 2# (OE-YTHDF3/siFGF2) groups. Overexpression of YTHDF3 promoted cell growth and colony formation, whereas downregulation of FGF2 reversed these effects (Figure.5C D). Similarly, upon FGF2 knockdown, the enhanced cell growth and invasion caused by YTHDF3 overexpression were suppressed (Figure.5E F). These findings indicate that FGF2 is an important downstream target through which YTHDF3 promotes breast cancer progression.

The most prevalent mRNA modification, N6-methyladenosine (m⁶A), surpasses others in terms of abundance. On average, every 1000 nucleotides harbors 1–2 m⁶A residues. This modification predominantly occurs in eukaryotic cells, specifically at the RRACH sequence (with R = A or G, H = A, C, or U) ^18–20. Remarkably, m⁶A methylation has been detected not only in eukaryotic cells but also in viruses, prokaryotic cells, and even viral genomes, highlighting its universal presence²¹. Mechanistically, m⁶A methylation is intricately involved in numerous facets of RNA metabolism, encompassing mRNA translation, degradation, splicing, export, and folding^22,23. Despite its widespread existence throughout eukaryotes, the role of m⁶A methylation in cancer is nuanced and cannot be simply categorized as "beneficial" or "detrimental"²⁴.

YTHDF3, a member of the YTH family characterized by the presence of the YTH domain, exhibits highly conserved genetic features across various animal and plant species, underscoring its undeniable significance^25,26. The YTH family comprises five known members: YTHDF1, YTHDF2, YTHDF3, YTHDC1, and YTHDC2, all of which are involved in m⁶A modification and function as “readers” of this modification. As integral components of the “reading” machinery, they play a crucial role by recognizing and binding to m⁶A-modified sites, thereby modulating the function of target RNAs^{27 8}. For instance, YTHDF1 inhibits the presentation of tumor neoantigens to T cells by recognizing m⁶A modification in dendritic cells, leading to tumor cell evasion from immune surveillance²⁸. YTHDF2 interacts with miRNAs and influences the migration and invasion capabilities of prostate cancer cells²⁹. YTHDF3, in concert with YTHDF2 and YTHDF1, contributes to translational regulation. Furthermore, YTHDF3 recognizes the m⁶A-modified initiation factor eIF4G2 and participates in the translation process of circular RNAs (CircRNAs). In other cancers, YTHDF3 affects the occurrence and progression of colorectal cancer through the regulation of m⁶A modification³⁰. It also plays a role in immune-related microenvironments by promoting FOXO3 translation to suppress interferon-dependent antiviral responses³¹. In conclusion, "Readers" holds immense potential in cancer research and serves as a promising avenue for exploring m⁶A modification, thereby warranting further investigation.

According to reports, YTHDF3 plays a pivotal role as a key component of m⁶a methylation in various tumor types ^32–35. Previous studies have also emphasized the involvement of YTHDF3 in brain metastasis of breast cancer cells¹⁵, as well as its significant role in the progression and metastasis of triple-negative breast cancer through the YTHDF3-ZEB1 axis ³⁴. In our research, we observed upregulation of the YTHDF3 gene in breast cancer, indicating a heightened risk. Additionally, in several intrinsic molecular subtypes of breast cancer, heightened expression of YTHDF3 is accompanied by increased patient mortality rates, suggesting its importance as an oncogene in breast cancer and its selection during the cancer evolution process. Our findings align with a previous study^32,36. Furthermore, our research reveals the pronounced promotion of malignant processes, including proliferation, migration, and invasion, by YTHDF3 in breast cancer cells. These findings provide insightful revelations, pointing towards the potential of YTHDF3 as a promising therapeutic target in the treatment of breast cancer.

To unravel the underlying mechanisms of YTHDF3 in breast cancer, we conducted a comprehensive analysis using bioinformatics tools and examined previously published meRIP-Seq and RIP-Seq data ¹⁵. Our primary objective was to identify potential downstream targets of YTHDF3 that could be modulated through m⁶A methylation. The bioinformatics analysis highlighted FGF2 as a promising candidate downstream target of YTHDF3, with plausible involvement in m⁶A methylation regulation. Nevertheless, the regulatory relationship between YTHDF3 and FGF2 necessitates further deliberation. To investigate this, we performed RIP experiments in breast cancer cell lines, which unveiled an interaction between FGF2 and YTHDF3 mRNA. However, the precise regulatory mechanism involving YTHDF3-induced m⁶A methylation modifications remains to be elucidated. Further research efforts are warranted to shed light on this aspect.

Previous studies have predominantly explored FGF2 as a target within the FGF2/FGFR1 signaling pathway, employing exogenous FGF2 to facilitate breast cancer progression ³⁷. Notably, it has also been observed that the impact of exogenous FGF2 and intracellular overexpression of FGF2 in breast cancer cells differs substantially³⁸.Consequently, FGF2 presents a paradoxical situation in breast cancer cells. In our investigation, we employed CRISPR-Cas9 technology to specifically knock out FGF2. The depletion of FGF2 in breast cancer cell lines notably attenuated their migration, invasion, and clonogenic capacities, while also inducing apoptosis in these cells, echoing findings from a previous study ³⁹. These contradictory observations further provoke our curiosity regarding whether YTHDF3 influences the malignant processes of breast cancer cells by regulating the expression of FGF2.

To gain further insights into the YTHDF3-m⁶A-FGF2 axis, we introduced specific mutations in the YTHDF3 protein, specifically altering the hydrophobic residues W438 and W492 to alanine. These mutations are known to disrupt the YTH domain, thus impairing the m⁶A binding capability. Subsequently, we generated plasmids containing the mutated sequences and conducted RIP-qPCR and RNA pull-down experiments to confirm the direct interaction between FGF2 mRNA and the YTH domain of YTHDF3. Intriguingly, overexpressing the mutated plasmids did not affect the protein levels of FGF2, and silencing YTHDF3 mRNA did not lead to substantial changes in FGF2 mRNA levels. We thus postulated that FGF2 potentially exhibits its effects through the recognition of the YTH domain on YTHDF3. Further exploration of this interaction was undertaken through Co-IP experiments to examine the protein-protein interactions between FGF2 and YTHDF3. As anticipated, the specific protein interaction between FGF2 and the mutated YTH domain in YTHDF3 weakened. Additionally, utilizing the SRAMP tool (http://www.cuilab.cn/sramp/) ⁴⁰, we predicted potential m⁶A binding sites in the coding sequence (CDS) region of FGF2. RNA pull-down experiments confirmed that the binding between YTHDF3 and FGF2 mRNA was abolished when these predicted sites were individually or jointly mutated. These findings provide further support for our hypothesis. Furthermore, considering previous research indicating the role of YTHDF3 in protein stability regulation ⁴¹, we investigated whether YTHDF3 modulates the stability of FGF2 protein. Through cycloheximide (CHX) and MG132 treatments, we demonstrated that YTHDF3 indeed influences the stability of FGF2 protein. Low levels of FGF2 inhibit the malignant progression of breast cancer cells .Nonetheless, it is important to acknowledge that YTHDF3 may regulate the expression of multiple genes in breast cancer, and its effects on breast cancer may be attributed to its broad impact on various targets. Further validation is warranted.

In summary, our research demonstrates the crucial role of YTHDF3 in breast cancer progression and provides an intriguing m⁶A-dependent regulatory mechanism. The combined network of YTHDF3 and the target gene FGF2 highlights an innovative m⁶A-dependent gene regulatory mechanism in the field of epigenetics. Furthermore, the YTHDF3-m⁶A-FGF2 model indicates the potential for a novel therapeutic approach in breast cancer treatment by suppressing YTHDF3 expression.

CDS

Coding sequence

Breast Cancer

m⁶A

N6-methyladenosine

RIP

RNA immunoprecipitation

ROC

Receiver operating characteristic

RT-qPCR

quantitative real-time PCR

TCGA

The Cancer Genome Atlas

YTHDF3

YTH N6-methyladenosine RNA binding protein 3

TCGA

The Cancer Genome Atlas

MeRIP-seq

Methylated RNA immunoprecipitation sequencing

IHC

Immunohistochemical

Hazard ratio

CHX

Cycloheximide

MG132

Carbobenzoxy-Leu-Leu-leucinal

Co-IP

Co-Immunoprecipitation

FGF2

Fibroblast growth factor 2

Knockout

Ethics declarations

Ethics approval and consent to participate

Clinical BC specimens were collected with the permission of the Ethics Committee of Guizhou Medical University.

Consent for publication

The content of this manuscript has not been previously published or considered for publication elsewhere.

Competing interests

The authors declare no conflict of interest.

Availability of data and materials

All data generated or analyzed during this study are included in this published article. The meRIP-seq and RIP-seq sequencing datasets used in this study were obtained from previously published articles, and the corresponding GSE accession numbers are provided in the Materials section.

Authors' contributions

The manuscript’s structure and organization were conceptualized by RF Gong and Wen Fang. The experimental procedures were performed by ZH Zhang, RF Gong, and YX Zhao. RF Gong conducted the data processing and bioinformatics analysis. The study received funding from Wen Fang, and the collection of clinical samples was facilitated by Ting Sun. RF Gong was responsible for drafting the initial version of the manuscript, which was later reviewed and revised by Wen Fang. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

Funding

This study was supported by the Science and Technology Program of Guizhou Province (Grant No. ZK［2022］-419).

Bi, Z. et al. A dynamic reversible RNA N(6) -methyladenosine modification: current status and perspectives. Journal of cellular physiology 234, 7948–7956, doi:10.1002/jcp.28014 (2019).
Linder, B. et al. Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nature methods 12, 767–772, doi:10.1038/nmeth.3453 (2015).
Lin, X. et al. RNA m(6)A methylation regulates the epithelial mesenchymal transition of cancer cells and translation of Snail. Nature communications 10, 2065, doi:10.1038/s41467-019-09865-9 (2019).
Ma, S. et al. The interplay between m6A RNA methylation and noncoding RNA in cancer. J Hematol Oncol 12, 121, doi:10.1186/s13045-019-0805-7 (2019).
He, L. et al. Functions of N6-methyladenosine and its role in cancer. Molecular cancer 18, 176, doi:10.1186/s12943-019-1109-9 (2019).
Erson-Bensan, A. E. & Begik, O. m6A Modification and Implications for microRNAs. MicroRNA 6, 97–101, doi:10.2174/2211536606666170511102219 (2017).
Liao, S., Sun, H. & Xu, C. YTH Domain: A Family of N(6)-methyladenosine (m(6)A) Readers. Genomics Proteomics Bioinformatics 16, 99–107, doi:10.1016/j.gpb.2018.04.002 (2018).
Chen, X. Y., Zhang, J. & Zhu, J. S. The role of m(6)A RNA methylation in human cancer. Mol Cancer 18, 103, doi:10.1186/s12943-019-1033-z (2019).
Liu, J. et al. m(6)A demethylase FTO facilitates tumor progression in lung squamous cell carcinoma by regulating MZF1 expression. Biochem Biophys Res Commun 502, 456–464, doi:10.1016/j.bbrc.2018.05.175 (2018).
Zhang, S. et al. m(6)A Demethylase ALKBH5 Maintains Tumorigenicity of Glioblastoma Stem-like Cells by Sustaining FOXM1 Expression and Cell Proliferation Program. Cancer cell 31, 591–606 e596, doi:10.1016/j.ccell.2017.02.013 (2017).
Shi, H. et al. YTHDF3 facilitates translation and decay of N(6)-methyladenosine-modified RNA. Cell Res 27, 315–328, doi:10.1038/cr.2017.15 (2017).
Sung, H. et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 71, 209–249, doi:10.3322/caac.21660 (2021).
Rahman, M. M., Brane, A. C. & Tollefsbol, T. O. MicroRNAs and Epigenetics Strategies to Reverse Breast Cancer. Cells 8, doi:10.3390/cells8101214 (2019).
Byler, S. et al. Genetic and epigenetic aspects of breast cancer progression and therapy. Anticancer research 34, 1071–1077 (2014).
Chang, G. et al. YTHDF3 Induces the Translation of m(6)A-Enriched Gene Transcripts to Promote Breast Cancer Brain Metastasis. Cancer cell 38, 857–871 e857, doi:10.1016/j.ccell.2020.10.004 (2020).
Wang, X. et al. N(6)-methyladenosine Modulates Messenger RNA Translation Efficiency. Cell 161, 1388–1399, doi:10.1016/j.cell.2015.05.014 (2015).
Wang, X. et al. N6-methyladenosine-dependent regulation of messenger RNA stability. Nature 505, 117–120, doi:10.1038/nature12730 (2014).
Krug, R. M., Morgan, M. A. & Shatkin, A. J. Influenza viral mRNA contains internal N6-methyladenosine and 5'-terminal 7-methylguanosine in cap structures. J Virol 20, 45–53, doi:10.1128/JVI.20.1.45-53.1976 (1976).
Beemon, K. & Keith, J. Localization of N6-methyladenosine in the Rous sarcoma virus genome. J Mol Biol 113, 165–179, doi:10.1016/0022-2836(77)90047-x (1977).
Bokar, J. A., Shambaugh, M. E., Polayes, D., Matera, A. G. & Rottman, F. M. Purification and cDNA cloning of the AdoMet-binding subunit of the human mRNA (N6-adenosine)-methyltransferase. Rna 3, 1233–1247 (1997).
Dai, D., Wang, H., Zhu, L., Jin, H. & Wang, X. N6-methyladenosine links RNA metabolism to cancer progression. Cell death & disease 9, 124, doi:10.1038/s41419-017-0129-x (2018).
Liu, Q. & Gregory, R. I. RNAmod: an integrated system for the annotation of mRNA modifications. Nucleic Acids Res 47, W548-W555, doi:10.1093/nar/gkz479 (2019).
Liu, N. et al. N6-methyladenosine alters RNA structure to regulate binding of a low-complexity protein. Nucleic Acids Res 45, 6051–6063, doi:10.1093/nar/gkx141 (2017).
Melstrom, L. & Chen, J. RNA N(6)-methyladenosine modification in solid tumors: new therapeutic frontiers. Cancer gene therapy 27, 625–633, doi:10.1038/s41417-020-0160-4 (2020).
Zhang, Z. et al. The YTH domain is a novel RNA binding domain. J Biol Chem 285, 14701–14710, doi:10.1074/jbc.M110.104711 (2010).
Wang, C. et al. A novel RNA-binding mode of the YTH domain reveals the mechanism for recognition of determinant of selective removal by Mmi1. Nucleic Acids Res 44, 969–982, doi:10.1093/nar/gkv1382 (2016).
Xu, Y. et al. YTH Domain Proteins: A Family of m(6)A Readers in Cancer Progression. Front Oncol 11, 629560, doi:10.3389/fonc.2021.629560 (2021).
Han, D. et al. Anti-tumour immunity controlled through mRNA m(6)A methylation and YTHDF1 in dendritic cells. Nature 566, 270–274, doi:10.1038/s41586-019-0916-x (2019).
Li, J. et al. Downregulation of N(6)-methyladenosine binding YTHDF2 protein mediated by miR-493-3p suppresses prostate cancer by elevating N(6)-methyladenosine levels. Oncotarget 9, 3752–3764, doi:10.18632/oncotarget.23365 (2018).
Ni, W. et al. Long noncoding RNA GAS5 inhibits progression of colorectal cancer by interacting with and triggering YAP phosphorylation and degradation and is negatively regulated by the m(6)A reader YTHDF3. Molecular cancer 18, 143, doi:10.1186/s12943-019-1079-y (2019).
Zhang, Y. et al. RNA-binding protein YTHDF3 suppresses interferon-dependent antiviral responses by promoting FOXO3 translation. Proceedings of the National Academy of Sciences of the United States of America 116, 976–981, doi:10.1073/pnas.1812536116 (2019).
Anita, R., Paramasivam, A., Priyadharsini, J. V. & Chitra, S. The m6A readers YTHDF1 and YTHDF3 aberrations associated with metastasis and predict poor prognosis in breast cancer patients. Am J Cancer Res 10, 2546–2554 (2020).
Du, H., Zou, N. Y., Zuo, H. L., Zhang, X. Y. & Zhu, S. C. YTHDF3 mediates HNF1alpha regulation of cervical cancer radio-resistance by promoting RAD51D translation in an m6A-dependent manner. FEBS J 290, 1920–1935, doi:10.1111/febs.16681 (2023).
Lin, Y. et al. YTHDF3 facilitates triple-negative breast cancer progression and metastasis by stabilizing ZEB1 mRNA in an m(6)A-dependent manner. Ann Transl Med 10, 83, doi:10.21037/atm-21-6857 (2022).
Xu, Y. et al. The m(6)A reading protein YTHDF3 potentiates tumorigenicity of cancer stem-like cells in ocular melanoma through facilitating CTNNB1 translation. Oncogene 41, 1281–1297, doi:10.1038/s41388-021-02146-0 (2022).
Liu, J. et al. A Novel YTHDF3-Based Model to Predict Prognosis and Therapeutic Response in Breast Cancer. Front Mol Biosci 9, 874532, doi:10.3389/fmolb.2022.874532 (2022).
Santolla, M. F. et al. GPER Mediates a Feedforward FGF2/FGFR1 Paracrine Activation Coupling CAFs to Cancer Cells toward Breast Tumor Progression. Cells 8, doi:10.3390/cells8030223 (2019).
Korah, R. M., Sysounthone, V., Scheff, E. & Wieder, R. Intracellular FGF-2 promotes differentiation in T-47D breast cancer cells. Biochemical and biophysical research communications 277, 255–260, doi:10.1006/bbrc.2000.3655 (2000).
Maloof, P. et al. Overexpression of basic fibroblast growth factor (FGF-2) downregulates Bcl-2 and promotes apoptosis in MCF-7 human breast cancer cells. Breast Cancer Res Treat 56, 153–167, doi:10.1023/a:1006258510381 (1999).
Zhou, Y., Zeng, P., Li, Y. H., Zhang, Z. & Cui, Q. SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features. Nucleic acids research 44, e91, doi:10.1093/nar/gkw104 (2016).
Li, A. et al. Cytoplasmic m(6)A reader YTHDF3 promotes mRNA translation. Cell research 27, 444–447, doi:10.1038/cr.2017.10 (2017).

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

YTHDF3 modulates the progression of breast cancer cells by regulating FGF2 through m6A methylation

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

1. Introduction

2. Methods

3. Results

4. Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1