Genetic identification of the m6A-related gene YTHDF3 as a putative biomarker for breast cancer

Genetic identification of the m6A-related gene YTHDF3 as a putative biomarker for breast cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Help Center Sign In Submit a Preprint Cite Share Download PDF Research Genetic identification of the m6A-related gene YTHDF3 as a putative biomarker for breast cancer Yu Wang, Yan Shi, Xiaohong Li, Yu Fan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1728752/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Ectopic expression of m6A-related genes is a common feature in a variety of human tumors, but the expression pattern and prognostic value of these genes are poorly understood in breast cancer. This study comprehensively analyzed the expression profile of m6A-related genes and their clinical significance in breast cancer. Methods The mRNA expression of m6A-related genes was evaluated from TCGA and GTEx databases. Differences in gene amplification and DNA methylation were analyzed using cBioPortal and MethHC, respectively. Univariate and multivariate Cox survival analyses were performed based on the gene expression and clinical parameters. STRING and Metascape were used to analyze the potential molecular pathways involving these genes. Results The majority of m6A-related genes showed significantly differential expression in breast cancer tissue samples, but the correlation with molecular characteristics such as gene promoter methylation and gene amplification was weak. Univariate overall survival analysis suggested that the ectopic expression of RBM15B (p = 0.008), METTL16 (p = 0.013), HNRNPC (p = 0.01), YTHDF1 (p = 0.002), YTHDF3 (p = 0.014), and IGF2BP1 (p < 0.001) were significantly associated with prognosis. Further multivariate Cox regression survival analysis revealed that upregulation of YTHDF3 expression was an independent prognostic factor for the survival of breast cancer patients (HR: 1.024, 90%CI: 1.003–1.046, p = 0.024). This study also found that YTHDF3 was probably not only involved in the processing and metabolism of RNA, but also related to DNA repair, pri-miRNA processing, telomere stability and other important molecular pathways. Conclusions m6A-related genes are abnormally expressed in breast cancer and are associated with the prognosis of patients, indicating the potential of these genes as biomarkers for breast cancer, among which YTHDF3 requires further study. RNA methylation m6A-related genes YTHDF3 breast cancer biomarkers Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Breast cancer is one of the most common malignancies with significant molecular heterogeneity( 1 ). Breast cancer has surpassed lung cancer as the most commonly diagnosed cancer. It is also a major cause of cancer-related deaths among women in most countries, with an estimated 2.3 million new cases and over 680,000 deaths in 2020, accounting for 24.5% and 15.5% of women worldwide, respectively( 2 ). With the development of new medical technologies, many effective treatments have been found for breast cancer, but these are unable to cure all patients. Therefore, it is an important research direction to seek genetic targets for the early diagnosis and effective treatment of breast cancer. Abnormal epigenetic modification is a common biological characteristics for many human cancers( 3 ). There are various types of RNA modifications including N6-methyladenosine (m6A), 5-methylcytosine (m5C), pseudouridylation (ψ), and many other types of modifications. Among them, m6A, an epitranscriptomic regulator, is gradually being recognized as important in breast cancer, and it is a hot topic of current research( 4 ). m6A has been shown to be a reversible and widespread modification enriched in the 3’-Untranslated Regions (3’-UTRs) of mammalian mRNA. It is known to be ubiquitous in mRNA and non-coding RNA, and this RNA modification requires the participation of m6A-related genes, which are known as "writers" (methyltransferases), "erasers" (demethylases) and "readers" (binding proteins)( 5 ). Recently, related research in cancer has provided new insights for m6A, and a number of reports have confirmed that m6A-related genes are involved in the development and progression of human tumors( 6 ). However, little is known about the m6A regulatory factors associated with breast cancer, and comprehensive analysis on the genetics and epigenetics of m6A-related genes is still lacking. In this study, we identified differentially expressed m6A-related genes in breast cancer based on public omics databases. In addition, the potential clinical value and molecular biological mechanisms of these genes were evaluated by survival analysis and molecular regulatory network prediction. Methods Gene expression and survival data The TCGA cohort data of 1034 breast cancer patients and 104 normal adjacent control subjects were originated from Breast Cancer Gene-Expression Miner v4.7 (http://bcgenex.ico.unicancer.fr/BC-GEM/)(7), and the data of 947 patients with clinical parameter information were collected. These data sets were used to analyze the mRNA expression profile of m6A-related genes in breast cancer and to evaluate their correlation with clinical prognosis. In order to further analyze the expression of m6A-related genes, this study also investigates the 92 normal breast tissues from healthy population based on Genotype-Tissue Expression (GTEx)(8). Genetic and epigenetic evaluation This study recurs to open access resources genome cBioPortal (https://www.cbioportal.org), and its characteristic is to explore the interactive and multidimensional cancer data sets(9). Genetic changes of m6A-related genes were assessed from the invasive breast cancer database (TCGA, Provisional, 1108 cases). In order to further explore the effect of DNA methylation modification to mRNA expression, MethHC (http://methhc.mbc.nctu.edu.tw/) containing samples of 839 cases of breast cancer and control was used to study the promoter methylation of m6A-related genes(10). Gene regulation network analysis Online protein interaction analysis tool of STRING (https://string-db.org/) was used to explore the molecular function network(11). The confidence index was set to 0.4. In addition, gene annotation and pathway enrichment were analyzed by Metascape (http://metascape.org/)(12). Statistical method SPSS software (version 13.0) was used to statistical analysis. The difference between the two independent samples was analyzed by unpaired t test. Kaplan-meier survival analysis and log-rank test were performed on all m6A-related genes, and independent factors were further determined by multivariate Cox regression analysis. The difference of p<0.05 was statistically significant. Results The different mRNA expression of m6A-related genes in breast cancer To assess the changes of m6A-related genes in breast cancer, we analyzed RNA transcriptome data from the TCGA and GTEx project containing 1034 tumor cases, 104 non-tumor adjacent tissues (NAT), and 92 normal tissues from healthy individuals. In this study, mRNA expression differences of m6A-related genes were analyzed, including the "writers" of m6A, such as WTAP, KIAA1429, RBM15, RBM15B, METTL3, METTL14, and METTL16 , the "erasers" of m6A, such as FTO and ALKBH5 , and the "readers" of m6A, such as HNRNPA2B1, HNRNPC, YTHDF1, YTHDF2, YTHDF3, YTHDC1, YTHDC2, IGF2BP1, IGF2BP2, IGF2BP3, and eIF3A . The results showed that most of the m6A-related genes had significant differences in mRNA expression (Figure 1) . Compared with normal breast tissues from healthy population, ten genes were up-regulated, including KIAA1429 (P < 0.0001), RBM15 (P < 0.001), RBM15B (P < 0.0001), HNRNPC (P < 0.0001), YTHDF1 (P < 0.0001), YTHDF2 (P < 0.0001), YTHDF3 (P < 0.0001), IGF2BP1 (P < 0.0001), IGF2BP3 (P < 0.0001), and ALKBH5 (P < 0.0001), while the mRNA expression of eight genes WTAP (P < 0.0001), METTL3 (P < 0.0001), METTL14 (P < 0.05), HNRNPA2B1 (P < 0.001), YTHDC1 (P < 0.0001), YTHDC2 (P < 0.0001), IGF2BP2 (P < 0.0001), and FTO (P < 0.0001) were down-regulated, and there was no significant difference in other two genes METTL16 (P 0.1). To further discover the ectopic expression of the above m6A-related genes, an evidence based on the TCGA database showed that most of these m6A-related genes had similar abnormal expression modes. However, compared with NAT, the expression of HNRNPA2B1 (P < 0.0001) was significantly up-regulated in breast cancer, while the expression of YTHDF3 (P < 0.05) , eIF3A (P < 0.0001), and ALKBH5 (P < 0.0001) were down-regulated, but there was no difference in expression of several genes RBM15, RBM15B, and YTHDF2 (Figure 1) . Because NAT can be obtained during tumor resection, sample collection is relatively easy. The vast majority of solid tumor studies have used NAT as a control such as TCGA(13). However, transcriptome studies on NAT are very limited. Can NAT be used as a comparison obtaining true and reliable differentially expressed genes (DEGs) in tumor tissues remains questionable(14). Therefore, it is inevitable that there are some differences in gene expression of NAT and normal breast tissues from healthy population. In summary, several m6A-related genes may have important abnormal changes of mRNA expression in breast cancer, and these changes in clinical samples are basically consistent. The promoter methylation and gene amplification of m6A-related gene in breast cancer DNA methylation plays an important role in epigenetic regulation of gene transcription, and the promoter hypermethylation inhibits mRNA expression(15). Based on the MethHC database, this study found that only IGF2BP1, IGF2BP2, and IGF2BP3 had significant difference of promoter methylation in breast cancer compared with normal control group (P < 0.005), while the YTHDC1 had no relevant data. The promoter methylation of other m6A-related genes had no significant difference (Figure S1) . Combined with the results of down-regulation of IGF2BP2 mRNA expression, it can be basically inferred that the promoter methylation of IGF2BP2 is possibly related to its down-regulation. To further explore the mechanism of gene expression regulation, our study found that WTAP and ALKBH5 had mRNA down-regulation characteristics, and KIAA1429 (VIRMA), YTHDF1, YTHDF3, and IGF2BP1 had the up-regulation characteristics of gene amplification, while the other m6A-related genes had no obvious alteration (Figure S2 and S3), based on the analysis of cBioPortal gene mutations and copy number changes. These results primarily suggest that the up-regulation of KIAA1429 (VIRMA), YTHDF1, YTHDF3, and IGF2BP1 mRNA may be related to gene amplification. In general, the mRNA expression level of m6A-related genes may not be significantly related to molecular characteristics such as gene promoter methylation, gene mutation or gene amplification. Survival analysis of m6A-related genes in breast cancer In order to explore the potential correlation with the abnormal expression of m6A-related genes and prognosis of breast cancer patients, this study analyzed the overall survival rate of patients with different genes based on the data of 947 cases. As shown in Figures 2 and 3 , low mRNA expression of RBM15B (P = 0.008), high expression of METTL16 (P = 0.013), high expression of HNRNPC (P = 0.01), high expression of YTHDF1 (P = 0.002), high expression of YTHDF3 (P = 0.014) and high expression of IGF2BP1 (P < 0.001) were significantly correlated with lower OS in breast cancer patients. To further analyze the effect of other factors in breast cancer, such as age, clinical stage, and race, on the long-term survival of patients. This study analyzed the m6A-related genes through multivariate Cox regression (data not shown) and found that in addition to patient age and clinical stage, which were independent factors, only YTHDF3 was another independent factor for the OS of breast cancer patients (HR: 1.024；95%: 1.003-1.046; P = 0.024, 0.05) (Table S1). Potential molecular network of m6A-related gene YTHDF3 In order to evaluate the potential role and molecular regulation mechanism of YTHDF3 in tumorigenesis and progression, this study used STRING protein interaction online tool to retrieve the potential regulatory targets of YTHDF3. The maximum number of interacting genes was not more than 50. The statistical parameters of the analysis results were 224 interaction edges, 65 expected interaction edges, average node value 8.78, average local clustering coefficient 0.793, and protein interaction enrichment P value < 1.00E-16. In this network function cluster analysis, it was found that YTHDF3 was closely related to many genes, including METTL3, ALKBH5, WTAP, METTL14, VPS13B, PMFBP1, PPP1R35, KIAA1429, ZNF609, FTO, and CNOT7, etc (Figure 4A) . We further used Metascape to perform gene annotation and pathway enrichment analysis on these genes, and found that the most significant mRNA metabolic regulation pathways (GO1903311) related to functional enrichment were 22 genes, such as ELAVL1, HNRNPA2B1, HNRNPC, PABPN1, CNOT8, WTAP, SRSF10, PAPOLA, CNOT1, VIRMA, and RBMX etc. In addition, DNA dealkylation repair (GO0006307: ALKBH1, ALKBH5, FTO and ALKBH2), pri-miRNA (GO0031053: HNRNPA2B1, SRRT and METTL3) and telomerase stabilization (GO1904356: HNRNPA2B1, HNRNPC, EXOSC10 and DCP2) were also believed to be related to the development and progression of malignant tumors (Figure 4B and Table S2) . Therefore, the abnormal up-regulation of YTHDF3 may be closely related to the tumor-related molecules regulation such as mRNA metabolic pathway, DNA repair, miRNA and telomerase. Discussion Because of their significant heterogeneity in breast cancer, it is generally believed that genetic and epigenetic changes play an indispensable role in its initiation and progression. Although research results have improved the efficacy of breast cancer treatment and the prognosis of breast cancer patients, early diagnosis and precise individualized treatment remain major challenges( 16 ). Therefore, exploration and identification of the molecular features of breast cancer genomics is essential for basic research and clinical drug development. So far, increasing numbers of studies have shown the important role of m6A in tumorigenesis and development. Although abnormal m6A RNA methylation has been confirmed to be closely related to cancer, the role of m6A-specific regulatory mechanisms in tumorigenesis and development needs to be further elucidated. This study was based on transcriptomic analysis of m6A-related genes, including public data from TCGA, GTEx, cBioPortal and STRING. First, the expression patterns of m6A-related genes were analyzed at the mRNA level, then we explored the correlation of the expression of these genes with clinical prognosis and built molecular regulatory networks. The results show that m6A-related genes are abnormally expressed in breast cancer, but they are not significantly related to gene mutations or DNA methylation. The abnormal expression of multiple genes such as YTHDF3 is related to the poor prognosis of patients, and suggests that YTHDF3 may be involved in key tumor-associated molecular pathways such as RNA processing, metabolism and DNA repair. m6A is thought to be assembled by a methyltransferase complex that adds methylation modifications, and this complex is also called the m6A "writer". WTAP, KIAA1429, RBM15, METTL3 and METTL14 are the core components of this complex( 17 ). Studies have found that WTAP plays an important biological function in a variety of malignant tumors, including in cholangiocarcinoma( 18 ), lymphoma( 19 ), renal cell carcinoma( 20 ), ovarian cancer( 21 ), pancreatic cancer( 22 ), and hepatocellular carcinoma( 23 ). However, the mRNA expression of WTAP was decreased in breast cancer, which suggests that there might be different molecular mechanisms of WTAP in breast cancer. Consistent with the high expression of KIAA1429 mRNA in this study, it has been reported that KIAA1429 regulates CDK1 through m6A methylation to exert its carcinogenic effects in breast cancer( 24 ). Additionally, RBM15 regulates multiple signaling pathways such as Notch and Wnt, especially playing an important role in the growth and apoptosis of blood cells. There is evidence that it may play a key role in acute/chronic myeloid leukemia, Kaposi’s sarcoma and borderline phyllodes tumors( 25 , 26 ). In our study, the expression of RBM15 in breast cancer was significantly upregulated, suggesting it may have a biological role. Furthermore, studies have found that BAP1 is significantly positively correlated with the expression of RBM15B and USP19 in breast cancer( 27 ). In line with other study( 28 ), we found a mRNA upregulation of RBM15B in breast cancer, while high expression of RBM15B pointed to a better survival. The hepatitis B x interaction protein (HBXIP) upregulated METTL3 plays a role in the tumorigenesis of breast cancer by inhibiting the tumor suppressor gene let-7g ( 29 ), but there was a downregulation in METTL3 mRNA expression in this study. Another study has also found METTL3 was expressed at a low level in breast cancer( 28 ). We found a downregulation in the mRNA level of METTL14 in breast cancer, which was broadly consistent with the results of METTL14 targeting tumor suppressor function through the m6A modification pathway in various tumor studies( 30 – 33 ). METTL16 repeat frameshift mutations have only been reported in colon cancer( 34 ). However, the expression level of mRNA in this study was downregulated. In another research, down- and up-regulation of METTL16 are observed respectively, based on different databases, and await further research to reveal their biological significance( 28 ). On the other hand, the m6A demethylation process must be completed by the m6A demethylase, which is called the "eraser". FTO was found to be one of the m6A "erasers" in breast cancer that was downregulated in this study, which was in line with the result of one previous study based on TCGA database( 28 ). However, one study suggested that FTO expression is upregulated in breast cancer and promotes breast cancer progression through target inhibition of BNIP3( 35 ). ALKBH5, another demethylase, was observed to be downregulated and upregulated in breast cancer mRNA levels in our analysis compared with that in different breast normal tissues. Interestingly, Zhang et al. found that ALKBH5-mediated RNA methylation and demethylation were involved in the maintenance of stemness and pluripotency of breast cancer cells in hypoxic environments( 36 , 37 ). This evidence strongly supports that the demethylation induction of m6A "erasers" in breast cancer is related to tumor growth and proliferation. The m6A modification can be recognized by proteins that contain specific YTH domains such as DF1, DF2, DF3 and DC1, with DF family members DF1, DF2 and DF3 being highly similar to each other( 38 ). Additionally, two other members, HNRNPC and HNRNPA2B1, were identified as nuclear m6A binding proteins( 39 ). Previous studies suggested that HNRNPA2B1 participates in carcinogenesis through the STAT3 and ERK1/2 signaling pathways( 40 ), and its expression was upregulated in breast cancer, which was consistent with our observation of its mRNA level in breast cancer. HNRNPC controls endogenous dsRNA and the response of downstream interferons, and its expression is upregulated in breast cancer. This result is novel in terms of our understanding of HNRNPC binding with intron to regulate RNA splicing( 41 ). Studies have also revealed that YTHDF1 is abnormally expressed in colon cancer( 42 , 43 ), ovarian cancer( 44 ), and lung cancer( 45 ), and participates in tumor progression through specific molecular pathways. Similarly, YTHDF2 shows different carcinogenic and tumor suppressor effects in a variety of malignant tumors( 46 – 51 ). Recent studies have found that YTHDF3 is not only an important target of YAP, but also a key participant in the YAP signaling pathway. It promotes the degradation of the m6A-modified lncRNA GAS5 , and consequently participates in the development of colorectal cancer( 52 ). Our study found that the mRNA expression levels of YTHDF1 , YTHDF2 and YTHDF3 were upregulated in breast cancer compared with that in normal tissues from healthy population. Although a significant downregulation in the expression of YTHDC1 and YTHDC2 was found in breast cancer, it has been reported that YT521 ( YTHDC1 ) was over-expressed in endometrial carcinoma and promoted the metastatic process by regulating the mRNA splicing of VEGFA ( 53 ). Furthermore, YTHDC2 is involved in the metastasis of colon cancer by promoting the translation of HIF-1α ( 54 ). Proteins containing the YTH domain are considered “readers” of m6A and share the function of stabilizing mRNA and promoting its expression. In addition, other studies have highlighted the important functions of another type of m6A “reader” of IGF2BPs in cancer biology and gene regulation after transcription( 55 ). Although CRD-BP/IGF2BP1 is expressed at a low level in breast cancer, it is necessary for the clonal growth of breast cancer cells( 56 ). In this study, we found that the mRNA level in breast cancer was upregulated compared with that in normal tissues, which also preliminarily indicates its role in carcinogenesis. However, the mRNA expression of IGF2BP2 was downregulated in breast cancer, and which was probably opposite to other studies, await further research to uncover its biologic function. IGF2BP2 was also found to promote the migration of breast cancer cells and reduce cell adhesion( 57 ). Consistent with the upregulation of IGF2BP3 mRNA found in this study, some studies have found that it has a high expression level and regulates TRIM25 RNA to participate in the proliferation of breast cancer cells through the interaction of IGF2BP3 and miR-3614-3p ( 58 ). There are also reports that IGF2BP2 and IGF2BP3 synergistically promote the metastasis of triple-negative breast cancer by destabilizing progesterone receptors( 59 ). Moreover, eukaryotic initiation factor 3 (eIF3) binds directly to a single 5'-UTR m6A, and it can fully recruit the 43S complex to start translation without cap binding factor eIF4E( 60 ). Although eIF3A was down-regulated in this study, it has been suggested that eIF3A is upregulated in breast cancer and may be a new target for tumor therapy( 61 ). Our study found that the downregulation of IGF2BP2 expression may be related to its DNA methylation, and the amplification of YTHDF1 , YTHDF3 and IGF2BP1 were related to gene expression. It has been reported that the mRNA expression of YTHDF1 is significantly positively correlated with the copy number of genes in colorectal cancer. Additionally, in a study of 69 neuroblastoma samples, the copy number of IGF2BP1 was significantly higher in stage IV tumors than in stage I tumors( 62 ). These results further indicate that m6A disorders are common in breast cancer and play a key role in its tumorigenesis and progression. In addition, this study found that the abnormal expression of RBM15B , METTL16 , HNRNPC , YTHDF1 , YTHDF3 and IGF2BP1 predict poor prognosis of patients. Among these, YTHDF3 may be an independent prognostic factor for breast cancer, possibly serving as a new biomarker of breast cancer. The result is consistent with the results in two tumor studies( 63 – 67 ). In other studies on the prognosis of breast cancer with m6A-related genes, it has been found that high levels of FTO are significantly related to the low survival rate of breast cancer patients. The expression of IGF2BP3 is significantly related to the poor prognosis of breast cancer, which has an independent impact on the response to neoadjuvant chemotherapy and clinical prognosis( 35 , 68 , 69 ). Through the analysis of YTHDF3-related genes, we identified potential biological signaling pathways that have not been identified in human cancers. Among them, functional enrichment analysis of YTHDF3 identified molecular pathways that may play a key role in tumorigenesis and progression (Fig. 4 B: GO1903311, GO0050684, GO0061013, and GO0009451). In line with the expected results, we found that relevant pathways such as RNA modification, processing and metabolism were significantly enriched. Research results in recent years have also confirmed the important role of m6A in post-transcriptional modification( 70 ), including RNA transcription, processing, shearing and RNA stabilization and translation. In addition, it is currently known that alkylation damage of DNA and RNA is caused by endogenous compounds, environmental factors and alkylating drugs, and its DNA repair methods include direct base repair, base excision repair and nucleotide excision repair( 71 ). The AlkB family is a ubiquitous DNA repair enzyme, which removes alkyl adducts from bases by DNA dealkylation. There are nine kinds of AlkB homologous genes ( ALKBH1-8 and FTO ) in mammals, but usually only part of them has the function of DNA/RNA repair enzymes( 72 ). Our study suggested that the YTHDF3-related genes ALKBH1 , ALKBH2 , ALKBH5 and FTO may be involved in the process of dealkylation DNA repair (Fig. 4 B: GO0006307). Furthermore, studies have found that HNRNPA2B1 specifically binds to exosomal miRNAs by recognizing gene sequences and controls its loading into exosomes. At the same time, ubiquitination of HNRNPA2B1 in exosomes controls binding to miRNA. Therefore, the loading of miRNA into exosomes can be achieved by changing the expression level of HNRNPA2B1 ( 73 ). SRRT (Ars2) is a component of the nuclear RNA cap-binding complex, which is important for the biogenesis, cell proliferation and tumorigenicity of certain miRNAs. Studies have shown that intervention in SRRT expression can affect miRNA levels and play a biological role( 74 , 75 ). In addition, the first step of miRNA biogenesis is achieved by the processing of the initial miRNA (pri-miRNA) by the micro-processing complex (RNA binding protein DGCR8 and type III RNase DROSHA). This event requires DGCR8 to recognize the interaction between the stem of pri-miRNA hairpin structure and the flanking single stranded RNA. METTL3 can be methylated to label pri-miRNA for DGCR8 recognition and processing. Therefore, the deletion of METTL3 can significantly reduce the binding of DGCR8 to pri-miRNA( 76 ). Additionally, we found that HNRNPA2B1, SRRT and METTL3 are involved in pri-miRNA processing and other processes (Fig. 4 B, GO0031053). In terms of telomerase, the deficiency of dyskerin leads to the degradation of telomerase RNA mediated by PAPD5, which can be drived by EXOSC10, DCP2 and XRN1 enzymes. By knocking out DCP2 and/or EXOSC10 , telomerase activity and telomerase RNA in dyskerin or PARN-deficient cells can be restored (Fig. 4 B: GO1904356)( 77 ). Interestingly, a study found that YTHDF3-related genes EXOSC10 and DCP2 were significantly enriched in molecular pathways related to telomerase stabilization. Moreover, YTHDF3 overexpression clinically correlates with breast cancer brain metastases and promotes translation of the key brain metastatic genes ST6GALNAC5 and GJA1 in a recent study( 78 ). Although this study suggests the prognostic value of genes such as YTHDF3 in breast cancer and predicts the potential signaling pathways involved, experiments are still needed to further clarify the molecular mechanisms of YTHDF3 and other genes affecting tumor cell growth, apoptosis and metastasis. There were limitations to this study. First, the analysis was based on public datasets, and no cohort data was used to validate the results independently, which require confirmation to some inconsistencies at the mRNA and protein levels. Second, there was a lack of direct in vivo and in vitro evidence to confirm the biological role of YTHDF3 in breast cancer. Finally, studies have found increasing numbers of potential new m6A-related genes in recent years, which need to be analyzed. Therefore, additional studies are urgently needed to validate the findings of this study. For the future, we plan to evaluate the value of YTHDF3 as a potential biomarker for breast cancer. Conclusions In summary, this study comprehensively evaluated the potential roles and molecular mechanisms of m6A-related genes in breast cancer based on TCGA and public omics datasets. Although our work uncovered no important impact of genetic and epigenetic alterations on gene expression, m6A-related genes were abnormally expressed in breast cancer and were associated with the prognosis of patients. These findings suggest that these genes may function as candidate tumor suppressor genes. Hence, their biologic roles in tumorigenesis and cancer progression are worthy of further study. Based on the data herein, YTHDF3 may be used as a prognostic biomarker and therapeutic target for human breast cancer. Declarations Ethics approval and consent to participate The informed consent from patients was waived because of the public nature of the database. Ethics approval was not required for this study. Consent for publication Not applicable. Availability of data and materials The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material. Competing interests The authors declare that they have no competing interests. Funding This work was supported by Provincial College Students Innovation and Entrepreneurship Training Program (grant no. 65-01041402), the Luzhou - Southwest Medical University Applied Basic Research Project (grant no. 2019LZXNYDJ07), Science and Technology Department of Sichuan Province Youth Science Fund Project (application no. 22YYJC3571), and Southwest Medical University Scientific Research Project (grant no. 2021ZKQN053). Authors’ contributions Y Fan and X Li conceived and designed the study. Y Wang obtained data and performed analysis. Y Wang, Y Shi, and Y Fan drafted the manuscript. All authors reviewed the manuscript and approved the final version before submission. Acknowledgments This work was also supported by the students from southwest medical university. In addition, I deeply appreciate the contribution to this study made in various ways by my colleagues and friends. References Yeo SK, Guan JL. Breast Cancer: Multiple Subtypes within a Tumor? Trends in cancer. 2017;3(11):753–60. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2021. Bennett RL, Licht JD. Targeting Epigenetics in Cancer. Annu Rev Pharmacol Toxicol. 2018;58:187–207. Wu L, Wu D, Ning J, Liu W, Zhang D. Changes of N6-methyladenosine modulators promote breast cancer progression. BMC Cancer. 2019;19(1):326. Roignant JY, Soller M. m(6)A in mRNA: An Ancient Mechanism for Fine-Tuning Gene Expression. Trends Genet. 2017;33(6):380–90. Pan Y, Ma P, Liu Y, Li W, Shu Y. Multiple functions of m(6)A RNA methylation in cancer. J Hematol Oncol. 2018;11(1):48. Jezequel P, Gouraud W, Ben Azzouz F, Guerin-Charbonnel C, Juin PP, Lasla H, et al. bc-GenExMiner 4.5: new mining module computes breast cancer differential gene expression analyses. Database: the journal of biological databases and curation. 2021;2021. Consortium GT. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Sci (New York NY). 2020;369(6509):1318–30. Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012;2(5):401–4. Huang WY, Hsu SD, Huang HY, Sun YM, Chou CH, Weng SL, et al. MethHC: a database of DNA methylation and gene expression in human cancer. Nucleic Acids Res. 2015;43(Database issue):D856-61. Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2015;43(Database issue):D447-52. Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523. Cancer Genome Atlas Research N. Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet. 2013;45(10):1113–20. Aran D, Camarda R, Odegaard J, Paik H, Oskotsky B, Krings G, et al. Comprehensive analysis of normal adjacent to tumor transcriptomes. Nat Commun. 2017;8(1):1077. Xiang TX, Yuan Y, Li LL, Wang ZH, Dan LY, Chen Y, et al. Aberrant promoter CpG methylation and its translational applications in breast cancer. Chin J Cancer. 2013;32(1):12–20. Pasculli B, Barbano R, Parrella P. Epigenetics of breast cancer: Biology and clinical implication in the era of precision medicine. Sem Cancer Biol. 2018;51:22–35. Meyer KD, Jaffrey SR. Rethinking m(6)A Readers, Writers, and Erasers. Annu Rev Cell Dev Biol. 2017;33:319–42. Jo HJ, Shim HE, Han ME, Kim HJ, Kim KS, Baek S, et al. WTAP regulates migration and invasion of cholangiocarcinoma cells. J Gastroenterol. 2013;48(11):1271–82. Kuai Y, Gong X, Ding L, Li F, Lei L, Gong Y, et al. Wilms' tumor 1-associating protein plays an aggressive role in diffuse large B-cell lymphoma and forms a complex with BCL6 via Hsp90. Cell communication and signaling: CCS. 2018;16(1):50. Tang J, Wang F, Cheng G, Si S, Sun X, Han J, et al. Wilms' tumor 1-associating protein promotes renal cell carcinoma proliferation by regulating CDK2 mRNA stability. J Exp Clin Cancer Res. 2018;37(1):40. Yu HL, Ma XD, Tong JF, Li JQ, Guan XJ, Yang JH. WTAP is a prognostic marker of high-grade serous ovarian cancer and regulates the progression of ovarian cancer cells. OncoTargets and therapy. 2019;12:6191–201. Li BQ, Liang ZY, Seery S, Liu QF, You L, Zhang TP, et al. WT1 associated protein promotes metastasis and chemo-resistance to gemcitabine by stabilizing Fak mRNA in pancreatic cancer. Cancer Lett. 2019;451:48–57. Chen Y, Peng C, Chen J, Chen D, Yang B, He B, et al. WTAP facilitates progression of hepatocellular carcinoma via m6A-HuR-dependent epigenetic silencing of ETS1. Mol Cancer. 2019;18(1):127. Qian JY, Gao J, Sun X, Cao MD, Shi L, Xia TS, et al. KIAA1429 acts as an oncogenic factor in breast cancer by regulating CDK1 in an N6-methyladenosine-independent manner. Oncogene. 2019;38(33):6123–41. Garcia-Dios DA, Levi D, Shah V, Gillett C, Simpson MA, Hanby A, et al. MED12, TERT promoter and RBM15 mutations in primary and recurrent phyllodes tumours. Br J Cancer. 2018;118(2):277–84. Hu M, Yang Y, Ji Z, Luo J. RBM15 Functions in Blood Diseases. Curr Cancer Drug Targets. 2016;16(7):579–85. Shahriyari L, Abdel-Rahman M, Cebulla C. BAP1 expression is prognostic in breast and uveal melanoma but not colon cancer and is highly positively correlated with RBM15B and USP19. PLoS ONE. 2019;14(2):e0211507. Zhang B, Gu Y, Jiang G. Expression and Prognostic Characteristics of m(6) A RNA Methylation Regulators in Breast Cancer. Front Genet. 2020;11:604597. Cai X, Wang X, Cao C, Gao Y, Zhang S, Yang Z, et al. HBXIP-elevated methyltransferase METTL3 promotes the progression of breast cancer via inhibiting tumor suppressor let-7g. Cancer Lett. 2018;415:11–9. Gu C, Wang Z, Zhou N, Li G, Kou Y, Luo Y, et al. Mettl14 inhibits bladder TIC self-renewal and bladder tumorigenesis through N(6)-methyladenosine of Notch1. Mol Cancer. 2019;18(1):168. Weng H, Huang H, Wu H, Qin X, Zhao BS, Dong L, et al. METTL14 Inhibits Hematopoietic Stem/Progenitor Differentiation and Promotes Leukemogenesis via mRNA m(6)A Modification. Cell Stem Cell. 2018;22(2):191–205. e9. Chen X, Xu M, Xu X, Zeng K, Liu X, Sun L, et al. METTL14 Suppresses CRC Progression via Regulating N6-Methyladenosine-Dependent Primary miR-375 Processing. Mol therapy: J Am Soc Gene Therapy. 2020;28(2):599–612. Ma JZ, Yang F, Zhou CC, Liu F, Yuan JH, Wang F, et al. METTL14 suppresses the metastatic potential of hepatocellular carcinoma by modulating N(6) -methyladenosine-dependent primary MicroRNA processing. Hepatology. 2017;65(2):529–43. Yeon SY, Jo YS, Choi EJ, Kim MS, Yoo NJ, Lee SH. Frameshift Mutations in Repeat Sequences of ANK3, HACD4, TCP10L, TP53BP1, MFN1, LCMT2, RNMT, TRMT6, METTL8 and METTL16 Genes in Colon Cancers. Pathol Oncol Res. 2018;24(3):617–22. Niu Y, Lin Z, Wan A, Chen H, Liang H, Sun L, et al. RNA N6-methyladenosine demethylase FTO promotes breast tumor progression through inhibiting BNIP3. Mol Cancer. 2019;18(1):46. Zhang C, Zhi WI, Lu H, Samanta D, Chen I, Gabrielson E, et al. Hypoxia-inducible factors regulate pluripotency factor expression by ZNF217- and ALKBH5-mediated modulation of RNA methylation in breast cancer cells. Oncotarget. 2016;7(40):64527–42. Zhang C, Samanta D, Lu H, Bullen JW, Zhang H, Chen I, et al. Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m(6)A-demethylation of NANOG mRNA. Proc Natl Acad Sci U S A. 2016;113(14):E2047-56. Liao S, Sun H, Xu CYTH, Domain. A Family of N(6)-methyladenosine (m(6)A) Readers. Genom Proteom Bioinform. 2018;16(2):99–107. Alarcon CR, Goodarzi H, Lee H, Liu X, Tavazoie S, Tavazoie SF. HNRNPA2B1 Is a Mediator of m(6)A-Dependent Nuclear RNA Processing Events. Cell. 2015;162(6):1299–308. Hu Y, Sun Z, Deng J, Hu B, Yan W, Wei H, et al. Splicing factor hnRNPA2B1 contributes to tumorigenic potential of breast cancer cells through STAT3 and ERK1/2 signaling pathway. Tumour biology: the journal of the International Society for Oncodevelopmental Biology and Medicine. 2017;39(3):1010428317694318. Wu Y, Zhao W, Liu Y, Tan X, Li X, Zou Q, et al. Function of HNRNPC in breast cancer cells by controlling the dsRNA-induced interferon response. The EMBO journal. 2018;37(23). Nishizawa Y, Konno M, Asai A, Koseki J, Kawamoto K, Miyoshi N, et al. Oncogene c-Myc promotes epitranscriptome m(6)A reader YTHDF1 expression in colorectal cancer. Oncotarget. 2018;9(7):7476–86. Bai Y, Yang C, Wu R, Huang L, Song S, Li W, et al. YTHDF1 Regulates Tumorigenicity and Cancer Stem Cell-Like Activity in Human Colorectal Carcinoma. Front Oncol. 2019;9:332. Liu T, Wei Q, Jin J, Luo Q, Liu Y, Yang Y, et al. The m6A reader YTHDF1 promotes ovarian cancer progression via augmenting EIF3C translation. Nucleic Acids Res. 2020;48(7):3816–31. Shi Y, Fan S, Wu M, Zuo Z, Li X, Jiang L, et al. YTHDF1 links hypoxia adaptation and non-small cell lung cancer progression. Nat Commun. 2019;10(1):4892. Zhang J, Pi J, Liu Y, Yu J, Feng T. [Knockdown of YTH N(6)-methyladenosine RNA binding protein 2 (YTHDF2) inhibits proliferation and promotes apoptosis in MGC-803 gastric cancer cells]. Xi bao yu fen zi mian yi xue za zhi = Chinese. J Cell Mol Immunol. 2017;33(12):1628–34. Li J, Meng S, Xu M, Wang S, He L, Xu X, 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. 2018;9(3):3752–64. Li Z, Qian P, Shao W, Shi H, He XC, Gogol M, et al. Suppression of m(6)A reader Ythdf2 promotes hematopoietic stem cell expansion. Cell Res. 2018;28(9):904–17. Paris J, Morgan M, Campos J, Spencer GJ, Shmakova A, Ivanova I, et al. Targeting the RNA m(6)A Reader YTHDF2 Selectively Compromises Cancer Stem Cells in Acute Myeloid Leukemia. Cell Stem Cell. 2019;25(1):137–48. e6. Chen J, Sun Y, Xu X, Wang D, He J, Zhou H, et al. YTH domain family 2 orchestrates epithelial-mesenchymal transition/proliferation dichotomy in pancreatic cancer cells. Cell Cycle. 2017;16(23):2259–71. Zhong L, Liao D, Zhang M, Zeng C, Li X, Zhang R, et al. YTHDF2 suppresses cell proliferation and growth via destabilizing the EGFR mRNA in hepatocellular carcinoma. Cancer Lett. 2019;442:252–61. Ni W, Yao S, Zhou Y, Liu Y, Huang P, Zhou A, 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. Mol Cancer. 2019;18(1):143. Zhang B, Shao X, Zhou J, Qiu J, Wu Y, Cheng J. YT521 promotes metastases of endometrial cancer by differential splicing of vascular endothelial growth factor A. Tumour biology:. the journal of the International Society for Oncodevelopmental Biology and Medicine; 2015. Tanabe A, Tanikawa K, Tsunetomi M, Takai K, Ikeda H, Konno J, et al. RNA helicase YTHDC2 promotes cancer metastasis via the enhancement of the efficiency by which HIF-1alpha mRNA is translated. Cancer Lett. 2016;376(1):34–42. Huang H, Weng H, Sun W, Qin X, Shi H, Wu H, et al. Recognition of RNA N(6)-methyladenosine by IGF2BP proteins enhances mRNA stability and translation. Nat Cell Biol. 2018;20(3):285–95. Fakhraldeen SA, Clark RJ, Roopra A, Chin EN, Huang W, Castorino J, et al. Two Isoforms of the RNA Binding Protein, Coding Region Determinant-binding Protein (CRD-BP/IGF2BP1), Are Expressed in Breast Epithelium and Support Clonogenic Growth of Breast Tumor Cells. J Biol Chem. 2015;290(21):13386–400. Li Y, Francia G, Zhang JY. p62/IMP2 stimulates cell migration and reduces cell adhesion in breast cancer. Oncotarget. 2015;6(32):32656–68. Wang Z, Tong D, Han C, Zhao Z, Wang X, Jiang T, et al. Blockade of miR-3614 maturation by IGF2BP3 increases TRIM25 expression and promotes breast cancer cell proliferation. EBioMedicine. 2019;41:357–69. Kim HY, Ha Thi HT, Hong S. IMP2 and IMP3 cooperate to promote the metastasis of triple-negative breast cancer through destabilization of progesterone receptor. Cancer Lett. 2018;415:30–9. Meyer KD, Patil DP, Zhou J, Zinoviev A, Skabkin MA, Elemento O, et al. 5' UTR m(6)A Promotes Cap-Independent Translation. Cell. 2015;163(4):999–1010. Yin JY, Zhang JT, Zhang W, Zhou HH, Liu ZQ. eIF3a: A new anticancer drug target in the eIF family. Cancer Lett. 2018;412:81–7. Bell JL, Turlapati R, Liu T, Schulte JH, Huttelmaier S. IGF2BP1 harbors prognostic significance by gene gain and diverse expression in neuroblastoma. J Clin oncology: official J Am Soc Clin Oncol. 2015;33(11):1285–93. Liu L, Liu X, Dong Z, Li J, Yu Y, Chen X, et al. N6-methyladenosine-related Genomic Targets are Altered in Breast Cancer Tissue and Associated with Poor Survival. J Cancer. 2019;10(22):5447–59. Anita R, Paramasivam A, Priyadharsini JV, Chitra S. The m6A readers YTHDF1 and YTHDF3 aberrations associated with metastasis and predict poor prognosis in breast cancer patients. Am J cancer Res. 2020;10(8):2546–54. Zhao G, An J, Pu Q, Geng W, Song H, Zhao Q, et al. Gene Signatures and Cancer-Immune Phenotypes Based on m(6)A Regulators in Breast Cancer. Front Oncol. 2021;11:756412. Demircan T, Yavuz M, Akgul S. m(6)A Pathway Regulators Are Frequently Mutated in Breast Invasive Carcinoma and May Play an Important Role in Disease Pathogenesis. OMICS. 2021;25(10):660–78. Lv W, Tan Y, Xiong M, Zhao C, Wang Y, Wu M, et al. Analysis and validation of m6A regulatory network: a novel circBACH2/has-miR-944/HNRNPC axis in breast cancer progression. J Transl Med. 2021;19(1):527. Ohashi R, Sangen M, Namimatsu S, Takei H, Naito Z. IMP3 contributes to poor prognosis of patients with metaplastic breast carcinoma: A clinicopathological study. Annals of diagnostic pathology. 2017;31:30–5. Ohashi R, Sangen M, Namimatsu S, Yanagihara K, Yamashita K, Sakatani T, et al. Prognostic value of IMP3 expression as a determinant of chemosensitivity in triple-negative breast cancer. Pathol Res Pract. 2017;213(9):1160–5. Chen XY, Zhang J, Zhu JS. The role of m(6)A RNA methylation in human cancer. Mol Cancer. 2019;18(1):103. Drablos F, Feyzi E, Aas PA, Vaagbo CB, Kavli B, Bratlie MS, et al. Alkylation damage in DNA and RNA–repair mechanisms and medical significance. DNA Repair. 2004;3(11):1389–407. Fedeles BI, Singh V, Delaney JC, Li D, Essigmann JM. The AlkB Family of Fe(II)/alpha-Ketoglutarate-dependent Dioxygenases: Repairing Nucleic Acid Alkylation Damage and Beyond. J Biol Chem. 2015;290(34):20734–42. Villarroya-Beltri C, Gutierrez-Vazquez C, Sanchez-Cabo F, Perez-Hernandez D, Vazquez J, Martin-Cofreces N, et al. Sumoylated hnRNPA2B1 controls the sorting of miRNAs into exosomes through binding to specific motifs. Nat Commun. 2013;4:2980. Hu X, Xu S, Chen Y, Gao Z, Li Y, Hu J, et al. Depletion of Ars2 inhibits cell proliferation and leukemogenesis in acute myeloid leukemia by modulating the miR-6734-3p/p27 axis. Leukemia. 2019;33(5):1090–101. Chen Y, Hu X, Li Y, Zhang H, Fu R, Liu Y, et al. Ars2 promotes cell proliferation and tumorigenicity in glioblastoma through regulating miR-6798-3p. Sci Rep. 2018;8(1):15602. Alarcon CR, Lee H, Goodarzi H, Halberg N, Tavazoie SF. N6-methyladenosine marks primary microRNAs for processing. Nature. 2015;519(7544):482–5. Shukla S, Schmidt JC, Goldfarb KC, Cech TR, Parker R. Inhibition of telomerase RNA decay rescues telomerase deficiency caused by dyskerin or PARN defects. Nat Struct Mol Biol. 2016;23(4):286–92. Chang G, Shi L, Ye Y, Shi H, Zeng L, Tiwary S, et al. YTHDF3 Induces the Translation of m(6)A-Enriched Gene Transcripts to Promote Breast Cancer Brain Metastasis. Cancer Cell. 2020;38(6):857–71. e7. Tables Table 1: Multivariate Cox survival regression analysis results of m6A-related gene YTHDF3 Parameters HR 95%CI p-value YTHDF3 1.024 1.003-1.046 0.024 Age 1.036 1.023-1.050 <0.001 Race 1.275 0.892-1.821 0.182 Stage 2.263 1.796-2.851 <0.001 Note: HR, hazard ratio; 95%CI, confidence interval. Supplementary Files FigureS1.docx FigureS2.docx FigureS3.docx TableS1.docx TableS2.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1728752","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":111850404,"identity":"25334aff-f736-4760-84b0-b34f02e518bc","order_by":0,"name":"Yu Wang","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Wang","suffix":""},{"id":111850405,"identity":"ef302112-bf4b-4704-8da3-f277ab7dbe4e","order_by":1,"name":"Yan Shi","email":"","orcid":"","institution":"Southwest Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Shi","suffix":""},{"id":111850406,"identity":"203ee364-3c9d-4751-be64-62d2b143229b","order_by":2,"name":"Xiaohong Li","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaohong","middleName":"","lastName":"Li","suffix":""},{"id":111850407,"identity":"75164230-a18f-4ea8-9f46-2c24fd78bd7d","order_by":3,"name":"Yu Fan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYFACxgcMDBVQNg9xWpgNGBjOkKyFsY0ULQY3khk/F86rS1w7I4Hxwds2BnlzIrQwS8/cdjhx240EZsO5bQyGOxsIask/IM277UAuUAubNG8bQ4LBASJs+c07pw6khf03sVqAhjcwg21hJkqL5JnHbNY8xw7XbzvzsFlyzjkJww2EtPAdT2a+zVNTZ2x2PPnghzdlNvIEbVFAKGBsABISBNQDgXwDYTWjYBSMglEw0gEAgDBBSeEUx7sAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-3962-4377","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Fan","suffix":""}],"badges":[],"createdAt":"2022-06-06 04:40:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1728752/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1728752/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":22468088,"identity":"c88ef83a-e1fd-4b17-b605-c0c0f10e4363","added_by":"auto","created_at":"2022-06-09 16:14:37","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":185855,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferent mRNA expression of m6A-related genes in breast cancer.\u0026nbsp;\u003c/strong\u003eRed indicates up-regulated expression; Blue indicated down-regulation, black indicated no expression difference, and white indicated no gene expression data. Different colors indicate statistical differences. The statistical method of Dunnett-Tukey-Kramer's test was used for two comparisons. \u003cstrong\u003eNote:\u003c/strong\u003e The “Normal” includes the comparison between cancer group and the NAT group in TCGA, as well as comparison between cancer group and the healthy group in GTEx. \u003cstrong\u003eAbbreviation:\u003c/strong\u003e TCGA, The Cancer Genome Atlas; GTEx, Genotype-Tissue Expression.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/47646cfc1e33c9b315803c5c.jpg"},{"id":22468089,"identity":"85d912c8-1a40-4d57-bf48-e911dccefa1a","added_by":"auto","created_at":"2022-06-09 16:14:37","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":272202,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEctopic mRNA expression of m6A \"writers\" RBM15B, and METTL16 was significantly correlated with overall survival of breast cancer patients\u003c/strong\u003e \u0026nbsp;\u003cstrong\u003eA)\u003c/strong\u003e Low expression of RBM15B gene was associated with a lower overall survival rate (p =0.008, \u0026lt;0.01); \u003cstrong\u003eB)\u003c/strong\u003e High expression of METTL16 was associated with poor prognosis (p =0.013, \u0026lt;0.05). Blue represents the low expression group and green represents the high expression group. The cut-off value of the high expression group and the low expression group was set as the best expression cut-off value. The unit of mRNA expression value was FPKM.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/f4607d6181d4b71769481fcb.jpg"},{"id":22468971,"identity":"862ae57e-2142-42af-a880-6ba876484b4e","added_by":"auto","created_at":"2022-06-09 16:24:37","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":541667,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEctopic mRNA expression of m6A \"readers\" HNRNPC, YTHDF1, YTHDF3, and IGF2BP1 was significantly correlated with overall survival of breast cancer patients\u0026nbsp;A)\u003c/strong\u003e High mRNA expression of HNRNPC gene was associated with a lower overall survival rate in breast cancer patients, with a statistically significant difference (p =0.01, \u0026lt;0.05). \u003cstrong\u003eB-D)\u003c/strong\u003e High expression of YTHDF1, YTHDF3, and IGF2BP1 was significantly associated with poor prognosis (p =0.002, p =0.014, and p \u0026lt;0.001, respectively). Blue represents the low expression group and green represents the high expression group. The cut-off value of the high expression group and the low expression group was set as the best expression cut-off value. The unit of gene mRNA expression value was FPKM.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/d655bf3ccfbd73c7fe0445f5.jpg"},{"id":22468683,"identity":"96e3eb6b-b670-4357-9bc1-f9e3e69b20a3","added_by":"auto","created_at":"2022-06-09 16:19:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1267984,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe potential molecular regulatory network for YTHDF3\u0026nbsp;A) \u003c/strong\u003eProtein interaction network analysis by searching the gene/protein database interacting with YTHDF3, set the confidence level at 0.4, and limit the identification of 50 genes interacting with YTHDF3. Interactional edge widths indicate data credibility. \u003cstrong\u003eB) \u003c/strong\u003eMetascape polymerized 13 significant clusters. The following Ontology resources were used to analyze the relevant target Genes of YTHDF3: Kyoto Encyclopedia of Genes and Genomes Pathway and Gene Ontology Biological Processes. The length of the horizontal column represents log10 (p value), which is based on the best score item for each cluster.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/8c919247655440dc058d4ccc.png"},{"id":22631432,"identity":"b7b28614-058a-4a14-b3f1-266638ed46c5","added_by":"auto","created_at":"2022-06-14 13:17:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1560900,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/aaf69b0f-dd39-443f-a795-876934332b88.pdf"},{"id":22468093,"identity":"b39d84dc-9c56-4993-9ab7-defbffa6d98c","added_by":"auto","created_at":"2022-06-09 16:14:37","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":197593,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/814166cf064977731eef3025.docx"},{"id":22468094,"identity":"9693270b-c48f-4150-ac2d-d1ffe2785a8f","added_by":"auto","created_at":"2022-06-09 16:14:37","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":634835,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/f3c4b1180b21acf3e8aecb3b.docx"},{"id":22468095,"identity":"30f34744-ca07-4a03-a93e-f081df4c9301","added_by":"auto","created_at":"2022-06-09 16:14:37","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":803704,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS3.docx","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/333c1913abbd8e679962e69a.docx"},{"id":22468096,"identity":"dd653c0b-73fe-4679-9928-abb54c5750e0","added_by":"auto","created_at":"2022-06-09 16:14:37","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":13171,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/d2b3c6bdd4714cacd58f8039.docx"},{"id":22468092,"identity":"002ddca5-43f0-4c6e-b2b2-6cdd8d2abc6a","added_by":"auto","created_at":"2022-06-09 16:14:37","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":16532,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-1728752/v1/2b8e66e9e9c33d03def85c3a.docx"}],"financialInterests":"","formattedTitle":"Genetic identification of the m6A-related gene YTHDF3 as a putative biomarker for breast cancer","fulltext":[{"header":"Background","content":"\u003cp\u003eBreast cancer is one of the most common malignancies with significant molecular heterogeneity(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Breast cancer has surpassed lung cancer as the most commonly diagnosed cancer. It is also a major cause of cancer-related deaths among women in most countries, with an estimated 2.3\u0026nbsp;million new cases and over 680,000 deaths in 2020, accounting for 24.5% and 15.5% of women worldwide, respectively(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). With the development of new medical technologies, many effective treatments have been found for breast cancer, but these are unable to cure all patients. Therefore, it is an important research direction to seek genetic targets for the early diagnosis and effective treatment of breast cancer.\u003c/p\u003e \u003cp\u003eAbnormal epigenetic modification is a common biological characteristics for many human cancers(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). There are various types of RNA modifications including N6-methyladenosine (m6A), 5-methylcytosine (m5C), pseudouridylation (ψ), and many other types of modifications. Among them, m6A, an epitranscriptomic regulator, is gradually being recognized as important in breast cancer, and it is a hot topic of current research(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). m6A has been shown to be a reversible and widespread modification enriched in the 3\u0026rsquo;-Untranslated Regions (3\u0026rsquo;-UTRs) of mammalian mRNA. It is known to be ubiquitous in mRNA and non-coding RNA, and this RNA modification requires the participation of m6A-related genes, which are known as \"writers\" (methyltransferases), \"erasers\" (demethylases) and \"readers\" (binding proteins)(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Recently, related research in cancer has provided new insights for m6A, and a number of reports have confirmed that m6A-related genes are involved in the development and progression of human tumors(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, little is known about the m6A regulatory factors associated with breast cancer, and comprehensive analysis on the genetics and epigenetics of m6A-related genes is still lacking.\u003c/p\u003e \u003cp\u003eIn this study, we identified differentially expressed m6A-related genes in breast cancer based on public omics databases. In addition, the potential clinical value and molecular biological mechanisms of these genes were evaluated by survival analysis and molecular regulatory network prediction.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eGene \u003c/strong\u003e\u003cstrong\u003eexpression \u003c/strong\u003e\u003cstrong\u003eand survival data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe TCGA cohort data of 1034 breast cancer patients and 104 normal adjacent control subjects were originated from Breast Cancer Gene-Expression Miner v4.7 (http://bcgenex.ico.unicancer.fr/BC-GEM/)(7), and the data of 947 patients with clinical parameter information were collected. These data sets were used to analyze the mRNA expression profile of m6A-related genes in breast cancer and to evaluate their correlation with clinical prognosis. In order to further analyze the expression of m6A-related genes, this study also investigates the 92 normal breast tissues from healthy population based on Genotype-Tissue Expression (GTEx)(8).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenetic and epigenetic evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study recurs to open access resources genome cBioPortal (https://www.cbioportal.org), and its characteristic is to explore the interactive and multidimensional cancer data sets(9). Genetic changes of m6A-related genes were assessed from the invasive breast cancer database (TCGA, Provisional, 1108 cases). In order to further explore the effect of DNA methylation modification to mRNA expression, MethHC (http://methhc.mbc.nctu.edu.tw/) containing samples of 839 cases of breast cancer and control was used to study the promoter methylation of m6A-related genes(10).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene regulation network analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOnline protein interaction analysis tool of STRING (https://string-db.org/) was used to explore the molecular function network(11). The confidence index was set to 0.4. In addition, gene annotation and pathway enrichment were analyzed by Metascape (http://metascape.org/)(12).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSPSS software (version 13.0) was used to statistical analysis. The difference between the two independent samples was analyzed by unpaired t test. Kaplan-meier survival analysis and log-rank test were performed on all m6A-related genes, and independent factors were further determined by multivariate Cox regression analysis. The difference of p\u0026lt;0.05 was statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eThe different mRNA expression of m6A-related genes in breast cancer \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the changes of m6A-related genes in breast cancer, we analyzed RNA transcriptome data from the TCGA and GTEx project containing 1034 tumor cases, 104 non-tumor adjacent tissues (NAT), and 92 normal tissues from healthy individuals. In this study, mRNA expression differences of m6A-related genes were analyzed, including the \"writers\" of m6A, such as \u003cem\u003eWTAP, KIAA1429, RBM15, RBM15B, METTL3, METTL14, \u003c/em\u003eand\u003cem\u003e METTL16\u003c/em\u003e, the \"erasers\" of m6A, such as \u003cem\u003eFTO \u003c/em\u003eand\u003cem\u003e ALKBH5\u003c/em\u003e, and the \"readers\" of m6A, such as \u003cem\u003eHNRNPA2B1, HNRNPC, YTHDF1, YTHDF2, YTHDF3, YTHDC1, YTHDC2, IGF2BP1, IGF2BP2, IGF2BP3, \u003c/em\u003eand\u003cem\u003e eIF3A\u003c/em\u003e. The results showed that most of the m6A-related genes had significant differences in mRNA expression \u003cstrong\u003e(Figure 1)\u003c/strong\u003e. Compared with normal breast tissues from healthy population, ten genes were up-regulated, including \u003cem\u003eKIAA1429\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eRBM15\u003c/em\u003e (P \u0026lt; 0.001), \u003cem\u003eRBM15B\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eHNRNPC\u003c/em\u003e (P \u0026lt; 0.0001),\u003cem\u003e YTHDF1\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eYTHDF2\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eYTHDF3\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eIGF2BP1\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eIGF2BP3\u003c/em\u003e (P \u0026lt; 0.0001), and \u003cem\u003eALKBH5\u003c/em\u003e (P \u0026lt; 0.0001), while the mRNA expression of eight genes \u003cem\u003eWTAP\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eMETTL3\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eMETTL14\u003c/em\u003e (P \u0026lt; 0.05), \u003cem\u003eHNRNPA2B1\u003c/em\u003e (P \u0026lt; 0.001),\u003cem\u003e YTHDC1\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eYTHDC2\u003c/em\u003e (P \u0026lt; 0.0001), \u003cem\u003eIGF2BP2\u003c/em\u003e (P \u0026lt; 0.0001), and \u003cem\u003eFTO\u003c/em\u003e (P \u0026lt; 0.0001) were down-regulated, and there was no significant difference in other two genes \u003cem\u003eMETTL16 \u003c/em\u003e(P \u0026lt; 0.1) and \u003cem\u003eeIF3A\u003c/em\u003e (P \u0026gt; 0.1). To further discover the ectopic expression of the above m6A-related genes, an evidence based on the TCGA database showed that most of these m6A-related genes had similar abnormal expression modes. However, compared with NAT, the expression of \u003cem\u003eHNRNPA2B1\u003c/em\u003e (P \u0026lt; 0.0001) was significantly up-regulated in breast cancer, while the expression of \u003cem\u003eYTHDF3 \u003c/em\u003e(P \u0026lt; 0.05)\u003cem\u003e, eIF3A \u003c/em\u003e(P \u0026lt; 0.0001), and \u003cem\u003eALKBH5 \u003c/em\u003e(P \u0026lt; 0.0001) were down-regulated, but there was no difference in expression of several genes \u003cem\u003eRBM15, RBM15B, and YTHDF2\u003c/em\u003e\u003cstrong\u003e (Figure 1)\u003c/strong\u003e. Because NAT can be obtained during tumor resection, sample collection is relatively easy. The vast majority of solid tumor studies have used NAT as a control such as TCGA(13). However, transcriptome studies on NAT are very limited. Can NAT be used as a comparison obtaining true and reliable differentially expressed genes (DEGs) in tumor tissues remains questionable(14). Therefore, it is inevitable that there are some differences in gene expression of NAT and normal breast tissues from healthy population. In summary, several m6A-related genes may have important abnormal changes of mRNA expression in breast cancer, and these changes in clinical samples are basically consistent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe promoter methylation and gene amplification of m6A-related gene in breast cancer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDNA methylation plays an important role in epigenetic regulation of gene transcription, and the promoter hypermethylation inhibits mRNA expression(15). Based on the MethHC database, this study found that only \u003cem\u003eIGF2BP1, IGF2BP2, \u003c/em\u003eand\u003cem\u003e IGF2BP3\u003c/em\u003e had significant difference of promoter methylation in breast cancer compared with normal control group (P \u0026lt; 0.005), while the \u003cem\u003eYTHDC1\u003c/em\u003e had no relevant data. The promoter methylation of other m6A-related genes had no significant difference\u003cstrong\u003e (Figure S1)\u003c/strong\u003e. Combined with the results of down-regulation of \u003cem\u003eIGF2BP2\u003c/em\u003e mRNA expression, it can be basically inferred that the promoter methylation of \u003cem\u003eIGF2BP2\u003c/em\u003e is possibly related to its down-regulation. To further explore the mechanism of gene expression regulation, our study found that \u003cem\u003eWTAP \u003c/em\u003eand\u003cem\u003e ALKBH5\u003c/em\u003e had mRNA down-regulation characteristics, and \u003cem\u003eKIAA1429 (VIRMA), YTHDF1, YTHDF3, \u003c/em\u003eand\u003cem\u003e IGF2BP1\u003c/em\u003e had the up-regulation characteristics of gene amplification, while the other m6A-related genes had no obvious alteration \u003cstrong\u003e(Figure S2 and S3), \u003c/strong\u003ebased on the analysis of cBioPortal gene mutations and copy number changes. These results primarily suggest that the up-regulation of \u003cem\u003eKIAA1429 (VIRMA), YTHDF1, YTHDF3, and IGF2BP1\u003c/em\u003e mRNA may be related to gene amplification. In general, the mRNA expression level of m6A-related genes may not be significantly related to molecular characteristics such as gene promoter methylation, gene mutation or gene amplification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurvival analysis of m6A-related genes in breast cancer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn order to explore the potential correlation with the abnormal expression of m6A-related genes and prognosis of breast cancer patients, this study analyzed the overall survival rate of patients with different genes based on the data of 947 cases. As shown in \u003cstrong\u003eFigures 2 and 3\u003c/strong\u003e, low mRNA expression of \u003cem\u003eRBM15B\u003c/em\u003e (P = 0.008), high expression of \u003cem\u003eMETTL16\u003c/em\u003e (P = 0.013), high expression of \u003cem\u003eHNRNPC\u003c/em\u003e (P = 0.01), high expression of \u003cem\u003eYTHDF1\u003c/em\u003e (P = 0.002), high expression of\u003cem\u003e YTHDF3 \u003c/em\u003e(P = 0.014) and high expression of \u003cem\u003eIGF2BP1\u003c/em\u003e (P \u0026lt; 0.001) were significantly correlated with lower OS in breast cancer patients. To further analyze the effect of other factors in breast cancer, such as age, clinical stage, and race, on the long-term survival of patients. This study analyzed the m6A-related genes through multivariate Cox regression (data not shown) and found that in addition to patient age and clinical stage, which were independent factors, only \u003cem\u003eYTHDF3\u003c/em\u003e was another independent factor for the OS of breast cancer patients (HR: 1.024；95%: 1.003-1.046; P = 0.024, \u0026lt;0.05) \u003cstrong\u003e(Table 1). \u003c/strong\u003eThere was no significant difference in other m6A-related genes (P \u0026gt; 0.05) \u003cstrong\u003e(Table S1).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePotential molecular network of m6A-related gene YTHDF3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn order to evaluate the potential role and molecular regulation mechanism of YTHDF3 in tumorigenesis and progression, this study used STRING protein interaction online tool to retrieve the potential regulatory targets of YTHDF3. The maximum number of interacting genes was not more than 50. The statistical parameters of the analysis results were 224 interaction edges, 65 expected interaction edges, average node value 8.78, average local clustering coefficient 0.793, and protein interaction enrichment P value \u0026lt; 1.00E-16. In this network function cluster analysis, it was found that YTHDF3 was closely related to many genes, including METTL3, ALKBH5, WTAP, METTL14, VPS13B, PMFBP1, PPP1R35, KIAA1429, ZNF609, FTO, and CNOT7, etc \u003cstrong\u003e(Figure 4A)\u003c/strong\u003e. We further used Metascape to perform gene annotation and pathway enrichment analysis on these genes, and found that the most significant mRNA metabolic regulation pathways (GO1903311) related to functional enrichment were 22 genes, such as ELAVL1, HNRNPA2B1, HNRNPC, PABPN1, CNOT8, WTAP, SRSF10, PAPOLA, CNOT1, VIRMA, and RBMX etc. In addition, DNA dealkylation repair (GO0006307: ALKBH1, ALKBH5, FTO and ALKBH2), pri-miRNA (GO0031053: HNRNPA2B1, SRRT and METTL3) and telomerase stabilization (GO1904356: HNRNPA2B1, HNRNPC, EXOSC10 and DCP2) were also believed to be related to the development and progression of malignant tumors \u003cstrong\u003e(Figure 4B and Table S2)\u003c/strong\u003e. Therefore, the abnormal up-regulation of YTHDF3 may be closely related to the tumor-related molecules regulation such as mRNA metabolic pathway, DNA repair, miRNA and telomerase.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBecause of their significant heterogeneity in breast cancer, it is generally believed that genetic and epigenetic changes play an indispensable role in its initiation and progression. Although research results have improved the efficacy of breast cancer treatment and the prognosis of breast cancer patients, early diagnosis and precise individualized treatment remain major challenges(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Therefore, exploration and identification of the molecular features of breast cancer genomics is essential for basic research and clinical drug development. So far, increasing numbers of studies have shown the important role of m6A in tumorigenesis and development. Although abnormal m6A RNA methylation has been confirmed to be closely related to cancer, the role of m6A-specific regulatory mechanisms in tumorigenesis and development needs to be further elucidated. This study was based on transcriptomic analysis of m6A-related genes, including public data from TCGA, GTEx, cBioPortal and STRING. First, the expression patterns of m6A-related genes were analyzed at the mRNA level, then we explored the correlation of the expression of these genes with clinical prognosis and built molecular regulatory networks. The results show that m6A-related genes are abnormally expressed in breast cancer, but they are not significantly related to gene mutations or DNA methylation. The abnormal expression of multiple genes such as \u003cem\u003eYTHDF3\u003c/em\u003e is related to the poor prognosis of patients, and suggests that YTHDF3 may be involved in key tumor-associated molecular pathways such as RNA processing, metabolism and DNA repair.\u003c/p\u003e \u003cp\u003em6A is thought to be assembled by a methyltransferase complex that adds methylation modifications, and this complex is also called the m6A \"writer\". WTAP, KIAA1429, RBM15, METTL3 and METTL14 are the core components of this complex(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Studies have found that WTAP plays an important biological function in a variety of malignant tumors, including in cholangiocarcinoma(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), lymphoma(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), renal cell carcinoma(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), ovarian cancer(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), pancreatic cancer(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), and hepatocellular carcinoma(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). However, the mRNA expression of \u003cem\u003eWTAP\u003c/em\u003e was decreased in breast cancer, which suggests that there might be different molecular mechanisms of WTAP in breast cancer. Consistent with the high expression of \u003cem\u003eKIAA1429\u003c/em\u003e mRNA in this study, it has been reported that KIAA1429 regulates CDK1 through m6A methylation to exert its carcinogenic effects in breast cancer(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Additionally, RBM15 regulates multiple signaling pathways such as Notch and Wnt, especially playing an important role in the growth and apoptosis of blood cells. There is evidence that it may play a key role in acute/chronic myeloid leukemia, Kaposi\u0026rsquo;s sarcoma and borderline phyllodes tumors(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In our study, the expression of \u003cem\u003eRBM15\u003c/em\u003e in breast cancer was significantly upregulated, suggesting it may have a biological role. Furthermore, studies have found that \u003cem\u003eBAP1\u003c/em\u003e is significantly positively correlated with the expression of \u003cem\u003eRBM15B\u003c/em\u003e and \u003cem\u003eUSP19\u003c/em\u003e in breast cancer(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). In line with other study(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), we found a mRNA upregulation of \u003cem\u003eRBM15B\u003c/em\u003e in breast cancer, while high expression of \u003cem\u003eRBM15B\u003c/em\u003e pointed to a better survival. The hepatitis B x interaction protein (HBXIP) upregulated METTL3 plays a role in the tumorigenesis of breast cancer by inhibiting the tumor suppressor gene \u003cem\u003elet-7g\u003c/em\u003e(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), but there was a downregulation in METTL3 mRNA expression in this study. Another study has also found METTL3 was expressed at a low level in breast cancer(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). We found a downregulation in the mRNA level of METTL14 in breast cancer, which was broadly consistent with the results of METTL14 targeting tumor suppressor function through the m6A modification pathway in various tumor studies(\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). \u003cem\u003eMETTL16\u003c/em\u003e repeat frameshift mutations have only been reported in colon cancer(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). However, the expression level of mRNA in this study was downregulated. In another research, down- and up-regulation of \u003cem\u003eMETTL16\u003c/em\u003e are observed respectively, based on different databases, and await further research to reveal their biological significance(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). On the other hand, the m6A demethylation process must be completed by the m6A demethylase, which is called the \"eraser\". FTO was found to be one of the m6A \"erasers\" in breast cancer that was downregulated in this study, which was in line with the result of one previous study based on TCGA database(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). However, one study suggested that FTO expression is upregulated in breast cancer and promotes breast cancer progression through target inhibition of BNIP3(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). ALKBH5, another demethylase, was observed to be downregulated and upregulated in breast cancer mRNA levels in our analysis compared with that in different breast normal tissues. Interestingly, Zhang \u003cem\u003eet al.\u003c/em\u003e found that ALKBH5-mediated RNA methylation and demethylation were involved in the maintenance of stemness and pluripotency of breast cancer cells in hypoxic environments(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). This evidence strongly supports that the demethylation induction of m6A \"erasers\" in breast cancer is related to tumor growth and proliferation.\u003c/p\u003e \u003cp\u003eThe m6A modification can be recognized by proteins that contain specific YTH domains such as DF1, DF2, DF3 and DC1, with DF family members DF1, DF2 and DF3 being highly similar to each other(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Additionally, two other members, HNRNPC and HNRNPA2B1, were identified as nuclear m6A binding proteins(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Previous studies suggested that HNRNPA2B1 participates in carcinogenesis through the STAT3 and ERK1/2 signaling pathways(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), and its expression was upregulated in breast cancer, which was consistent with our observation of its mRNA level in breast cancer. HNRNPC controls endogenous dsRNA and the response of downstream interferons, and its expression is upregulated in breast cancer. This result is novel in terms of our understanding of HNRNPC binding with intron to regulate RNA splicing(\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Studies have also revealed that \u003cem\u003eYTHDF1\u003c/em\u003e is abnormally expressed in colon cancer(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e), ovarian cancer(\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e), and lung cancer(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), and participates in tumor progression through specific molecular pathways. Similarly, YTHDF2 shows different carcinogenic and tumor suppressor effects in a variety of malignant tumors(\u003cspan additionalcitationids=\"CR47 CR48 CR49 CR50\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Recent studies have found that YTHDF3 is not only an important target of YAP, but also a key participant in the YAP signaling pathway. It promotes the degradation of the m6A-modified lncRNA \u003cem\u003eGAS5\u003c/em\u003e, and consequently participates in the development of colorectal cancer(\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Our study found that the mRNA expression levels of \u003cem\u003eYTHDF1\u003c/em\u003e, \u003cem\u003eYTHDF2\u003c/em\u003e and \u003cem\u003eYTHDF3\u003c/em\u003e were upregulated in breast cancer compared with that in normal tissues from healthy population. Although a significant downregulation in the expression of \u003cem\u003eYTHDC1\u003c/em\u003e and \u003cem\u003eYTHDC2\u003c/em\u003e was found in breast cancer, it has been reported that \u003cem\u003eYT521\u003c/em\u003e (\u003cem\u003eYTHDC1\u003c/em\u003e) was over-expressed in endometrial carcinoma and promoted the metastatic process by regulating the mRNA splicing of \u003cem\u003eVEGFA\u003c/em\u003e(\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Furthermore, YTHDC2 is involved in the metastasis of colon cancer by promoting the translation of \u003cem\u003eHIF-1α\u003c/em\u003e(\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Proteins containing the YTH domain are considered \u0026ldquo;readers\u0026rdquo; of m6A and share the function of stabilizing mRNA and promoting its expression. In addition, other studies have highlighted the important functions of another type of m6A \u0026ldquo;reader\u0026rdquo; of IGF2BPs in cancer biology and gene regulation after transcription(\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Although \u003cem\u003eCRD-BP/IGF2BP1\u003c/em\u003e is expressed at a low level in breast cancer, it is necessary for the clonal growth of breast cancer cells(\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). In this study, we found that the mRNA level in breast cancer was upregulated compared with that in normal tissues, which also preliminarily indicates its role in carcinogenesis. However, the mRNA expression of \u003cem\u003eIGF2BP2\u003c/em\u003e was downregulated in breast cancer, and which was probably opposite to other studies, await further research to uncover its biologic function. IGF2BP2 was also found to promote the migration of breast cancer cells and reduce cell adhesion(\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Consistent with the upregulation of \u003cem\u003eIGF2BP3\u003c/em\u003e mRNA found in this study, some studies have found that it has a high expression level and regulates \u003cem\u003eTRIM25\u003c/em\u003e RNA to participate in the proliferation of breast cancer cells through the interaction of IGF2BP3 and \u003cem\u003emiR-3614-3p\u003c/em\u003e(\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). There are also reports that IGF2BP2 and IGF2BP3 synergistically promote the metastasis of triple-negative breast cancer by destabilizing progesterone receptors(\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). Moreover, eukaryotic initiation factor 3 (eIF3) binds directly to a single 5'-UTR m6A, and it can fully recruit the 43S complex to start translation without cap binding factor eIF4E(\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). Although \u003cem\u003eeIF3A\u003c/em\u003e was down-regulated in this study, it has been suggested that \u003cem\u003eeIF3A\u003c/em\u003e is upregulated in breast cancer and may be a new target for tumor therapy(\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). Our study found that the downregulation of \u003cem\u003eIGF2BP2\u003c/em\u003e expression may be related to its DNA methylation, and the amplification of \u003cem\u003eYTHDF1\u003c/em\u003e, \u003cem\u003eYTHDF3\u003c/em\u003e and \u003cem\u003eIGF2BP1\u003c/em\u003e were related to gene expression. It has been reported that the mRNA expression of \u003cem\u003eYTHDF1\u003c/em\u003e is significantly positively correlated with the copy number of genes in colorectal cancer. Additionally, in a study of 69 neuroblastoma samples, the copy number of \u003cem\u003eIGF2BP1\u003c/em\u003e was significantly higher in stage IV tumors than in stage I tumors(\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). These results further indicate that m6A disorders are common in breast cancer and play a key role in its tumorigenesis and progression.\u003c/p\u003e \u003cp\u003eIn addition, this study found that the abnormal expression of \u003cem\u003eRBM15B\u003c/em\u003e, \u003cem\u003eMETTL16\u003c/em\u003e, \u003cem\u003eHNRNPC\u003c/em\u003e, \u003cem\u003eYTHDF1\u003c/em\u003e, \u003cem\u003eYTHDF3\u003c/em\u003e and \u003cem\u003eIGF2BP1\u003c/em\u003e predict poor prognosis of patients. Among these, YTHDF3 may be an independent prognostic factor for breast cancer, possibly serving as a new biomarker of breast cancer. The result is consistent with the results in two tumor studies(\u003cspan additionalcitationids=\"CR64 CR65 CR66\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). In other studies on the prognosis of breast cancer with m6A-related genes, it has been found that high levels of \u003cem\u003eFTO\u003c/em\u003e are significantly related to the low survival rate of breast cancer patients. The expression of \u003cem\u003eIGF2BP3\u003c/em\u003e is significantly related to the poor prognosis of breast cancer, which has an independent impact on the response to neoadjuvant chemotherapy and clinical prognosis(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThrough the analysis of YTHDF3-related genes, we identified potential biological signaling pathways that have not been identified in human cancers. Among them, functional enrichment analysis of YTHDF3 identified molecular pathways that may play a key role in tumorigenesis and progression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB: GO1903311, GO0050684, GO0061013, and GO0009451). In line with the expected results, we found that relevant pathways such as RNA modification, processing and metabolism were significantly enriched. Research results in recent years have also confirmed the important role of m6A in post-transcriptional modification(\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e), including RNA transcription, processing, shearing and RNA stabilization and translation. In addition, it is currently known that alkylation damage of DNA and RNA is caused by endogenous compounds, environmental factors and alkylating drugs, and its DNA repair methods include direct base repair, base excision repair and nucleotide excision repair(\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). The AlkB family is a ubiquitous DNA repair enzyme, which removes alkyl adducts from bases by DNA dealkylation. There are nine kinds of AlkB homologous genes (\u003cem\u003eALKBH1-8\u003c/em\u003e and \u003cem\u003eFTO\u003c/em\u003e) in mammals, but usually only part of them has the function of DNA/RNA repair enzymes(\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e). Our study suggested that the YTHDF3-related genes \u003cem\u003eALKBH1\u003c/em\u003e, \u003cem\u003eALKBH2\u003c/em\u003e, \u003cem\u003eALKBH5\u003c/em\u003e and \u003cem\u003eFTO\u003c/em\u003e may be involved in the process of dealkylation DNA repair (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB: GO0006307). Furthermore, studies have found that HNRNPA2B1 specifically binds to exosomal miRNAs by recognizing gene sequences and controls its loading into exosomes. At the same time, ubiquitination of HNRNPA2B1 in exosomes controls binding to miRNA. Therefore, the loading of miRNA into exosomes can be achieved by changing the expression level of \u003cem\u003eHNRNPA2B1\u003c/em\u003e(\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). SRRT (Ars2) is a component of the nuclear RNA cap-binding complex, which is important for the biogenesis, cell proliferation and tumorigenicity of certain miRNAs. Studies have shown that intervention in \u003cem\u003eSRRT\u003c/em\u003e expression can affect miRNA levels and play a biological role(\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). In addition, the first step of miRNA biogenesis is achieved by the processing of the initial miRNA (pri-miRNA) by the micro-processing complex (RNA binding protein DGCR8 and type III RNase DROSHA). This event requires DGCR8 to recognize the interaction between the stem of pri-miRNA hairpin structure and the flanking single stranded RNA. \u003cem\u003eMETTL3\u003c/em\u003e can be methylated to label pri-miRNA for DGCR8 recognition and processing. Therefore, the deletion of \u003cem\u003eMETTL3\u003c/em\u003e can significantly reduce the binding of DGCR8 to pri-miRNA(\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). Additionally, we found that HNRNPA2B1, SRRT and METTL3 are involved in pri-miRNA processing and other processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, GO0031053). In terms of telomerase, the deficiency of dyskerin leads to the degradation of telomerase RNA mediated by PAPD5, which can be drived by EXOSC10, DCP2 and XRN1 enzymes. By knocking out \u003cem\u003eDCP2\u003c/em\u003e and/or \u003cem\u003eEXOSC10\u003c/em\u003e, telomerase activity and telomerase RNA in dyskerin or PARN-deficient cells can be restored (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB: GO1904356)(\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e). Interestingly, a study found that YTHDF3-related genes \u003cem\u003eEXOSC10\u003c/em\u003e and \u003cem\u003eDCP2\u003c/em\u003e were significantly enriched in molecular pathways related to telomerase stabilization. Moreover, YTHDF3 overexpression clinically correlates with breast cancer brain metastases and promotes translation of the key brain metastatic genes ST6GALNAC5 and GJA1 in a recent study(\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). Although this study suggests the prognostic value of genes such as \u003cem\u003eYTHDF3\u003c/em\u003e in breast cancer and predicts the potential signaling pathways involved, experiments are still needed to further clarify the molecular mechanisms of \u003cem\u003eYTHDF3\u003c/em\u003e and other genes affecting tumor cell growth, apoptosis and metastasis.\u003c/p\u003e \u003cp\u003eThere were limitations to this study. First, the analysis was based on public datasets, and no cohort data was used to validate the results independently, which require confirmation to some inconsistencies at the mRNA and protein levels. Second, there was a lack of direct \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e evidence to confirm the biological role of YTHDF3 in breast cancer. Finally, studies have found increasing numbers of potential new m6A-related genes in recent years, which need to be analyzed. Therefore, additional studies are urgently needed to validate the findings of this study. For the future, we plan to evaluate the value of YTHDF3 as a potential biomarker for breast cancer.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this study comprehensively evaluated the potential roles and molecular mechanisms of m6A-related genes in breast cancer based on TCGA and public omics datasets. Although our work uncovered no important impact of genetic and epigenetic alterations on gene expression, m6A-related genes were abnormally expressed in breast cancer and were associated with the prognosis of patients. These findings suggest that these genes may function as candidate tumor suppressor genes. Hence, their biologic roles in tumorigenesis and cancer progression are worthy of further study. Based on the data herein, YTHDF3 may be used as a prognostic biomarker and therapeutic target for human breast cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe informed consent from patients was waived because of the public nature of the database. Ethics approval was not required for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Provincial College Students Innovation and Entrepreneurship Training Program (grant no. 65-01041402), the Luzhou - Southwest Medical University Applied Basic Research Project (grant no. 2019LZXNYDJ07), Science and Technology Department of Sichuan Province Youth Science Fund Project (application no. 22YYJC3571), and Southwest Medical University Scientific Research Project (grant no. 2021ZKQN053).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY Fan and X Li conceived and designed the study. Y Wang obtained data and performed analysis. Y Wang, Y Shi, and Y Fan drafted the manuscript. All authors reviewed the manuscript and approved the final version before submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was also supported by the students from southwest medical university. In addition, I deeply appreciate the contribution to this study made in various ways by my colleagues and friends.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYeo SK, Guan JL. Breast Cancer: Multiple Subtypes within a Tumor? Trends in cancer. 2017;3(11):753\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBennett RL, Licht JD. Targeting Epigenetics in Cancer. Annu Rev Pharmacol Toxicol. 2018;58:187\u0026ndash;207.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu L, Wu D, Ning J, Liu W, Zhang D. Changes of N6-methyladenosine modulators promote breast cancer progression. BMC Cancer. 2019;19(1):326.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoignant JY, Soller M. m(6)A in mRNA: An Ancient Mechanism for Fine-Tuning Gene Expression. Trends Genet. 2017;33(6):380\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan Y, Ma P, Liu Y, Li W, Shu Y. Multiple functions of m(6)A RNA methylation in cancer. J Hematol Oncol. 2018;11(1):48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJezequel P, Gouraud W, Ben Azzouz F, Guerin-Charbonnel C, Juin PP, Lasla H, et al. bc-GenExMiner 4.5: new mining module computes breast cancer differential gene expression analyses. Database: the journal of biological databases and curation. 2021;2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConsortium GT. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Sci (New York NY). 2020;369(6509):1318\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012;2(5):401\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang WY, Hsu SD, Huang HY, Sun YM, Chou CH, Weng SL, et al. MethHC: a database of DNA methylation and gene expression in human cancer. Nucleic Acids Res. 2015;43(Database issue):D856-61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2015;43(Database issue):D447-52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCancer Genome Atlas Research N. Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet. 2013;45(10):1113\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAran D, Camarda R, Odegaard J, Paik H, Oskotsky B, Krings G, et al. Comprehensive analysis of normal adjacent to tumor transcriptomes. Nat Commun. 2017;8(1):1077.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiang TX, Yuan Y, Li LL, Wang ZH, Dan LY, Chen Y, et al. Aberrant promoter CpG methylation and its translational applications in breast cancer. Chin J Cancer. 2013;32(1):12\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePasculli B, Barbano R, Parrella P. Epigenetics of breast cancer: Biology and clinical implication in the era of precision medicine. Sem Cancer Biol. 2018;51:22\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeyer KD, Jaffrey SR. Rethinking m(6)A Readers, Writers, and Erasers. Annu Rev Cell Dev Biol. 2017;33:319\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJo HJ, Shim HE, Han ME, Kim HJ, Kim KS, Baek S, et al. WTAP regulates migration and invasion of cholangiocarcinoma cells. J Gastroenterol. 2013;48(11):1271\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuai Y, Gong X, Ding L, Li F, Lei L, Gong Y, et al. Wilms' tumor 1-associating protein plays an aggressive role in diffuse large B-cell lymphoma and forms a complex with BCL6 via Hsp90. Cell communication and signaling: CCS. 2018;16(1):50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang J, Wang F, Cheng G, Si S, Sun X, Han J, et al. Wilms' tumor 1-associating protein promotes renal cell carcinoma proliferation by regulating CDK2 mRNA stability. J Exp Clin Cancer Res. 2018;37(1):40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu HL, Ma XD, Tong JF, Li JQ, Guan XJ, Yang JH. WTAP is a prognostic marker of high-grade serous ovarian cancer and regulates the progression of ovarian cancer cells. OncoTargets and therapy. 2019;12:6191\u0026ndash;201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi BQ, Liang ZY, Seery S, Liu QF, You L, Zhang TP, et al. WT1 associated protein promotes metastasis and chemo-resistance to gemcitabine by stabilizing Fak mRNA in pancreatic cancer. Cancer Lett. 2019;451:48\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Peng C, Chen J, Chen D, Yang B, He B, et al. WTAP facilitates progression of hepatocellular carcinoma via m6A-HuR-dependent epigenetic silencing of ETS1. Mol Cancer. 2019;18(1):127.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQian JY, Gao J, Sun X, Cao MD, Shi L, Xia TS, et al. KIAA1429 acts as an oncogenic factor in breast cancer by regulating CDK1 in an N6-methyladenosine-independent manner. Oncogene. 2019;38(33):6123\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarcia-Dios DA, Levi D, Shah V, Gillett C, Simpson MA, Hanby A, et al. MED12, TERT promoter and RBM15 mutations in primary and recurrent phyllodes tumours. Br J Cancer. 2018;118(2):277\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu M, Yang Y, Ji Z, Luo J. RBM15 Functions in Blood Diseases. Curr Cancer Drug Targets. 2016;16(7):579\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShahriyari L, Abdel-Rahman M, Cebulla C. BAP1 expression is prognostic in breast and uveal melanoma but not colon cancer and is highly positively correlated with RBM15B and USP19. PLoS ONE. 2019;14(2):e0211507.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang B, Gu Y, Jiang G. Expression and Prognostic Characteristics of m(6) A RNA Methylation Regulators in Breast Cancer. Front Genet. 2020;11:604597.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCai X, Wang X, Cao C, Gao Y, Zhang S, Yang Z, et al. HBXIP-elevated methyltransferase METTL3 promotes the progression of breast cancer via inhibiting tumor suppressor let-7g. Cancer Lett. 2018;415:11\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu C, Wang Z, Zhou N, Li G, Kou Y, Luo Y, et al. Mettl14 inhibits bladder TIC self-renewal and bladder tumorigenesis through N(6)-methyladenosine of Notch1. Mol Cancer. 2019;18(1):168.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeng H, Huang H, Wu H, Qin X, Zhao BS, Dong L, et al. METTL14 Inhibits Hematopoietic Stem/Progenitor Differentiation and Promotes Leukemogenesis via mRNA m(6)A Modification. Cell Stem Cell. 2018;22(2):191\u0026ndash;205. e9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen X, Xu M, Xu X, Zeng K, Liu X, Sun L, et al. METTL14 Suppresses CRC Progression via Regulating N6-Methyladenosine-Dependent Primary miR-375 Processing. Mol therapy: J Am Soc Gene Therapy. 2020;28(2):599\u0026ndash;612.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMa JZ, Yang F, Zhou CC, Liu F, Yuan JH, Wang F, et al. METTL14 suppresses the metastatic potential of hepatocellular carcinoma by modulating N(6) -methyladenosine-dependent primary MicroRNA processing. Hepatology. 2017;65(2):529\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYeon SY, Jo YS, Choi EJ, Kim MS, Yoo NJ, Lee SH. Frameshift Mutations in Repeat Sequences of ANK3, HACD4, TCP10L, TP53BP1, MFN1, LCMT2, RNMT, TRMT6, METTL8 and METTL16 Genes in Colon Cancers. Pathol Oncol Res. 2018;24(3):617\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNiu Y, Lin Z, Wan A, Chen H, Liang H, Sun L, et al. RNA N6-methyladenosine demethylase FTO promotes breast tumor progression through inhibiting BNIP3. Mol Cancer. 2019;18(1):46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang C, Zhi WI, Lu H, Samanta D, Chen I, Gabrielson E, et al. Hypoxia-inducible factors regulate pluripotency factor expression by ZNF217- and ALKBH5-mediated modulation of RNA methylation in breast cancer cells. Oncotarget. 2016;7(40):64527\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang C, Samanta D, Lu H, Bullen JW, Zhang H, Chen I, et al. Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m(6)A-demethylation of NANOG mRNA. Proc Natl Acad Sci U S A. 2016;113(14):E2047-56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiao S, Sun H, Xu CYTH, Domain. A Family of N(6)-methyladenosine (m(6)A) Readers. Genom Proteom Bioinform. 2018;16(2):99\u0026ndash;107.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlarcon CR, Goodarzi H, Lee H, Liu X, Tavazoie S, Tavazoie SF. HNRNPA2B1 Is a Mediator of m(6)A-Dependent Nuclear RNA Processing Events. Cell. 2015;162(6):1299\u0026ndash;308.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu Y, Sun Z, Deng J, Hu B, Yan W, Wei H, et al. Splicing factor hnRNPA2B1 contributes to tumorigenic potential of breast cancer cells through STAT3 and ERK1/2 signaling pathway. Tumour biology: the journal of the International Society for Oncodevelopmental Biology and Medicine. 2017;39(3):1010428317694318.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Y, Zhao W, Liu Y, Tan X, Li X, Zou Q, et al. Function of HNRNPC in breast cancer cells by controlling the dsRNA-induced interferon response. The EMBO journal. 2018;37(23).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNishizawa Y, Konno M, Asai A, Koseki J, Kawamoto K, Miyoshi N, et al. Oncogene c-Myc promotes epitranscriptome m(6)A reader YTHDF1 expression in colorectal cancer. Oncotarget. 2018;9(7):7476\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBai Y, Yang C, Wu R, Huang L, Song S, Li W, et al. YTHDF1 Regulates Tumorigenicity and Cancer Stem Cell-Like Activity in Human Colorectal Carcinoma. Front Oncol. 2019;9:332.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu T, Wei Q, Jin J, Luo Q, Liu Y, Yang Y, et al. The m6A reader YTHDF1 promotes ovarian cancer progression via augmenting EIF3C translation. Nucleic Acids Res. 2020;48(7):3816\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi Y, Fan S, Wu M, Zuo Z, Li X, Jiang L, et al. YTHDF1 links hypoxia adaptation and non-small cell lung cancer progression. Nat Commun. 2019;10(1):4892.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang J, Pi J, Liu Y, Yu J, Feng T. [Knockdown of YTH N(6)-methyladenosine RNA binding protein 2 (YTHDF2) inhibits proliferation and promotes apoptosis in MGC-803 gastric cancer cells]. Xi bao yu fen zi mian yi xue za zhi = Chinese. J Cell Mol Immunol. 2017;33(12):1628\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi J, Meng S, Xu M, Wang S, He L, Xu X, 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. 2018;9(3):3752\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Z, Qian P, Shao W, Shi H, He XC, Gogol M, et al. Suppression of m(6)A reader Ythdf2 promotes hematopoietic stem cell expansion. Cell Res. 2018;28(9):904\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParis J, Morgan M, Campos J, Spencer GJ, Shmakova A, Ivanova I, et al. Targeting the RNA m(6)A Reader YTHDF2 Selectively Compromises Cancer Stem Cells in Acute Myeloid Leukemia. Cell Stem Cell. 2019;25(1):137\u0026ndash;48. e6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen J, Sun Y, Xu X, Wang D, He J, Zhou H, et al. YTH domain family 2 orchestrates epithelial-mesenchymal transition/proliferation dichotomy in pancreatic cancer cells. Cell Cycle. 2017;16(23):2259\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhong L, Liao D, Zhang M, Zeng C, Li X, Zhang R, et al. YTHDF2 suppresses cell proliferation and growth via destabilizing the EGFR mRNA in hepatocellular carcinoma. Cancer Lett. 2019;442:252\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNi W, Yao S, Zhou Y, Liu Y, Huang P, Zhou A, 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. Mol Cancer. 2019;18(1):143.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang B, Shao X, Zhou J, Qiu J, Wu Y, Cheng J. YT521 promotes metastases of endometrial cancer by differential splicing of vascular endothelial growth factor A. Tumour biology:. the journal of the International Society for Oncodevelopmental Biology and Medicine; 2015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTanabe A, Tanikawa K, Tsunetomi M, Takai K, Ikeda H, Konno J, et al. RNA helicase YTHDC2 promotes cancer metastasis via the enhancement of the efficiency by which HIF-1alpha mRNA is translated. Cancer Lett. 2016;376(1):34\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang H, Weng H, Sun W, Qin X, Shi H, Wu H, et al. Recognition of RNA N(6)-methyladenosine by IGF2BP proteins enhances mRNA stability and translation. Nat Cell Biol. 2018;20(3):285\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFakhraldeen SA, Clark RJ, Roopra A, Chin EN, Huang W, Castorino J, et al. Two Isoforms of the RNA Binding Protein, Coding Region Determinant-binding Protein (CRD-BP/IGF2BP1), Are Expressed in Breast Epithelium and Support Clonogenic Growth of Breast Tumor Cells. J Biol Chem. 2015;290(21):13386\u0026ndash;400.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Francia G, Zhang JY. p62/IMP2 stimulates cell migration and reduces cell adhesion in breast cancer. Oncotarget. 2015;6(32):32656\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Tong D, Han C, Zhao Z, Wang X, Jiang T, et al. Blockade of miR-3614 maturation by IGF2BP3 increases TRIM25 expression and promotes breast cancer cell proliferation. EBioMedicine. 2019;41:357\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim HY, Ha Thi HT, Hong S. IMP2 and IMP3 cooperate to promote the metastasis of triple-negative breast cancer through destabilization of progesterone receptor. Cancer Lett. 2018;415:30\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeyer KD, Patil DP, Zhou J, Zinoviev A, Skabkin MA, Elemento O, et al. 5' UTR m(6)A Promotes Cap-Independent Translation. Cell. 2015;163(4):999\u0026ndash;1010.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYin JY, Zhang JT, Zhang W, Zhou HH, Liu ZQ. eIF3a: A new anticancer drug target in the eIF family. Cancer Lett. 2018;412:81\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBell JL, Turlapati R, Liu T, Schulte JH, Huttelmaier S. IGF2BP1 harbors prognostic significance by gene gain and diverse expression in neuroblastoma. J Clin oncology: official J Am Soc Clin Oncol. 2015;33(11):1285\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu L, Liu X, Dong Z, Li J, Yu Y, Chen X, et al. N6-methyladenosine-related Genomic Targets are Altered in Breast Cancer Tissue and Associated with Poor Survival. J Cancer. 2019;10(22):5447\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnita R, Paramasivam A, Priyadharsini JV, Chitra S. The m6A readers YTHDF1 and YTHDF3 aberrations associated with metastasis and predict poor prognosis in breast cancer patients. Am J cancer Res. 2020;10(8):2546\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao G, An J, Pu Q, Geng W, Song H, Zhao Q, et al. Gene Signatures and Cancer-Immune Phenotypes Based on m(6)A Regulators in Breast Cancer. Front Oncol. 2021;11:756412.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemircan T, Yavuz M, Akgul S. m(6)A Pathway Regulators Are Frequently Mutated in Breast Invasive Carcinoma and May Play an Important Role in Disease Pathogenesis. OMICS. 2021;25(10):660\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLv W, Tan Y, Xiong M, Zhao C, Wang Y, Wu M, et al. Analysis and validation of m6A regulatory network: a novel circBACH2/has-miR-944/HNRNPC axis in breast cancer progression. J Transl Med. 2021;19(1):527.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOhashi R, Sangen M, Namimatsu S, Takei H, Naito Z. IMP3 contributes to poor prognosis of patients with metaplastic breast carcinoma: A clinicopathological study. Annals of diagnostic pathology. 2017;31:30\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOhashi R, Sangen M, Namimatsu S, Yanagihara K, Yamashita K, Sakatani T, et al. Prognostic value of IMP3 expression as a determinant of chemosensitivity in triple-negative breast cancer. Pathol Res Pract. 2017;213(9):1160\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen XY, Zhang J, Zhu JS. The role of m(6)A RNA methylation in human cancer. Mol Cancer. 2019;18(1):103.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDrablos F, Feyzi E, Aas PA, Vaagbo CB, Kavli B, Bratlie MS, et al. Alkylation damage in DNA and RNA\u0026ndash;repair mechanisms and medical significance. DNA Repair. 2004;3(11):1389\u0026ndash;407.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFedeles BI, Singh V, Delaney JC, Li D, Essigmann JM. The AlkB Family of Fe(II)/alpha-Ketoglutarate-dependent Dioxygenases: Repairing Nucleic Acid Alkylation Damage and Beyond. J Biol Chem. 2015;290(34):20734\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVillarroya-Beltri C, Gutierrez-Vazquez C, Sanchez-Cabo F, Perez-Hernandez D, Vazquez J, Martin-Cofreces N, et al. Sumoylated hnRNPA2B1 controls the sorting of miRNAs into exosomes through binding to specific motifs. Nat Commun. 2013;4:2980.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu X, Xu S, Chen Y, Gao Z, Li Y, Hu J, et al. Depletion of Ars2 inhibits cell proliferation and leukemogenesis in acute myeloid leukemia by modulating the miR-6734-3p/p27 axis. Leukemia. 2019;33(5):1090\u0026ndash;101.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Hu X, Li Y, Zhang H, Fu R, Liu Y, et al. Ars2 promotes cell proliferation and tumorigenicity in glioblastoma through regulating miR-6798-3p. Sci Rep. 2018;8(1):15602.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlarcon CR, Lee H, Goodarzi H, Halberg N, Tavazoie SF. N6-methyladenosine marks primary microRNAs for processing. Nature. 2015;519(7544):482\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShukla S, Schmidt JC, Goldfarb KC, Cech TR, Parker R. Inhibition of telomerase RNA decay rescues telomerase deficiency caused by dyskerin or PARN defects. Nat Struct Mol Biol. 2016;23(4):286\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChang G, Shi L, Ye Y, Shi H, Zeng L, Tiwary S, et al. YTHDF3 Induces the Translation of m(6)A-Enriched Gene Transcripts to Promote Breast Cancer Brain Metastasis. Cancer Cell. 2020;38(6):857\u0026ndash;71. e7.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Multivariate Cox survival regression analysis results of m6A-related gene YTHDF3\u003c/strong\u003e\u003c/p\u003e\n\u003ctable\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003eYTHDF3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1.024\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1.003-1.046\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u003cem\u003e0.024\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1.036\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1.023-1.050\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003eRace\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1.275\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.892-1.821\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.182\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003eStage\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e2.263\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1.796-2.851\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e HR, hazard ratio; 95%CI, confidence interval.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"RNA methylation, m6A-related genes, YTHDF3, breast cancer, biomarkers ","lastPublishedDoi":"10.21203/rs.3.rs-1728752/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1728752/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEctopic expression of m6A-related genes is a common feature in a variety of human tumors, but the expression pattern and prognostic value of these genes are poorly understood in breast cancer. This study comprehensively analyzed the expression profile of m6A-related genes and their clinical significance in breast cancer.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe mRNA expression of m6A-related genes was evaluated from TCGA and GTEx databases. Differences in gene amplification and DNA methylation were analyzed using cBioPortal and MethHC, respectively. Univariate and multivariate Cox survival analyses were performed based on the gene expression and clinical parameters. STRING and Metascape were used to analyze the potential molecular pathways involving these genes.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe majority of m6A-related genes showed significantly differential expression in breast cancer tissue samples, but the correlation with molecular characteristics such as gene promoter methylation and gene amplification was weak. Univariate overall survival analysis suggested that the ectopic expression of \u003cem\u003eRBM15B\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.008), \u003cem\u003eMETTL16\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.013), \u003cem\u003eHNRNPC\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.01), \u003cem\u003eYTHDF1\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.002), \u003cem\u003eYTHDF3\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.014), and \u003cem\u003eIGF2BP1\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly associated with prognosis. Further multivariate Cox regression survival analysis revealed that upregulation of \u003cem\u003eYTHDF3\u003c/em\u003e expression was an independent prognostic factor for the survival of breast cancer patients (HR: 1.024, 90%CI: 1.003\u0026ndash;1.046, p\u0026thinsp;=\u0026thinsp;0.024). This study also found that YTHDF3 was probably not only involved in the processing and metabolism of RNA, but also related to DNA repair, pri-miRNA processing, telomere stability and other important molecular pathways.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003em6A-related genes are abnormally expressed in breast cancer and are associated with the prognosis of patients, indicating the potential of these genes as biomarkers for breast cancer, among which YTHDF3 requires further study.\u003c/p\u003e","manuscriptTitle":"Genetic identification of the m6A-related gene YTHDF3 as a putative biomarker for breast cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-06-09 16:14:35","doi":"10.21203/rs.3.rs-1728752/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"db59fda5-90ef-4e10-8bf2-64d1cc494f22","owner":[],"postedDate":"June 9th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-06-14T13:17:48+00:00","versionOfRecord":[],"versionCreatedAt":"2022-06-09 16:14:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1728752","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1728752","identity":"rs-1728752","version":["v1"]},"buildId":"pf3fE39SIOqb-0xH_OWvX","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}