N6-methyladenosine binding protein YTHDF2 predicts better prognosis in patients with gastric cancer

Background: The potential role of N6-methyladenosine (m6A) in cancer progression has received tremendous attention over the past few years. The aim of this study was to evaluate the effect of YTH N6-methyladenosine RNA binding protein 2 (YTHDF2) on the prognosis of patients and its potential role in gastric cancer. Methods: A total of 305 gastric cancer patients with clinical information were identied from the TCGA dataset. Limma package was used to analyze the differential m6A regulators; the Cox regression model was used to determine the risk factor for OS. A 1:1 propensity score matching (PSM) analysis was employed to adjust for the difference in baseline clinicopathological characteristics between the YTHDF2 low and high expression group. The Cox regression analysis was reused to identify the risk factors for overall survival (OS). GO and KEGG analysis were used to explore the potential role and function of YTHDF2 in gastric cancer. Results: Nineteen m6A methylation regulators were expressed in gastric cancer tissues; YTHDF2 was associated with the prognosis of gastric cancer patients. The expression level of YTHDF2, patient age, and tumor stage were independent risk factors for OS. After PSM, YTHDF2 expression led to a relatively better prognosis and stage. Patients in stage IV had a signicantly poor prognosis. The expression of YTHDF2 was associated with cancer-related functions and pathways in gastric cancer. Conclusions: The high expression of YTHDF2 can predict a better prognosis of gastric cancer patients. YTHDF2 exerts a critical role in gastric cancer progression.

Recently, it has been reported that YTHDF2 can help LINC00470-METTL3 mediated PTEN mRNA degradation in GC [9]. Also, knockdown of YTHDF2 can inhibit proliferation and promote apoptosis in the MGC803 GC cell line [10]. However, the relationship between YTHDF2 and prognosis of GC patients remains unclear.
In this study, we evaluated the effect of YTHDF2 on the prognosis of patients and its potential roles in GC.

Data source and acquisition
The expression data of GC and normal tissues were collected from The Cancer Genome Atlas (TCGA)

Statistical analysis
To determine the expression level of 22 m6A methylation regulators in tumor and normal tissues, the limma package was used for analysis. A Chi-square test was used to compare the distribution of clinicopathological features between patients with low and high expression of YTHDF2. The Cox regression model was chosen to identify m6A regulators and independent prognostic factors for OS.
Hazard ratios (HRs) and 95% con dence interval (95% CIs) were also determined. OS was estimated by the Kaplan-Meier method, with a log-rank test to determine statistical signi cance. Patients in the low and high expression levels of YTHDF2 were matched at a ratio of 1:1 through propensity score matching (PSM); a total of 212 patients were included for subsequent analysis. GO and KEGG analysis of differentially expressed genes between YTHDF2 low and high expression groups were performed using the cluster Pro ler package. SPSS version 23.0 (SPSS Inc., Chicago, IL, USA) and R software for windows version R-4.0.2 (The R Foundation for Statistical Computing, Vienna, Austria) were used for data analysis. A P-value < 0.05 was considered statistically signi cant.
The YTHDF2 expression level in baseline clinicopathological characteristics To understand the relationship between 19 m6A methylation regulators and patient prognosis, we performed univariate Cox regression analysis for 19 regulators, respectively. We found that m6A "reader" YTHDF2 was obviously associated with the OS (Additional le 1). The results also indicated that YTHDF2 might perform as a protective factor role in GC (HR = 0.629, p = 0.027). Consequently, GC patients were divided into low and high expression groups according to the expression level of YTHDF2 in GC tissues ( Figure 2A). Combining the baseline clinicopathological characteristics of the patients, we found that gender and subtype were both related to the expression of YTHDF2 (Table 1). Yet, the YTHDF2 expression level was signi cantly higher in females than in males, while no difference was found in MSS, MSS-L,

Risk factors of patient survival
To explore the risk factors that can in uence the prognosis of GC patients in baseline clinicopathological characteristics, univariate and multivariate Cox regression analyses were used for determining the risk factors for OS. As a result, YTHDF2 expression, patient age, and tumor stage were con rmed as signi cant predictive factors for OS (Table 2). Patients with higher YTHDF2 expression had signi cantly better OS. Compared with patients younger than 65 years old, those > 65 years old were at high risk of worse OS. In terms of stage, an increased risk of poor prognosis was detected in stage III and IV, as compared with stage I and II. We further performed Cox regression analyses for each clinicopathological subgroup of GC patients (Figure 3), which revealed that patients younger than 65 years old, male patients, patients with T3-4, M0, N0, and MSS subtype had a better prognosis.
To ensure the accuracy of the risk factors obtained by our previous analysis, and to exclude the interference of other factors, we used propensity score matching (PSM) to match patients with low and high expression of YTHDF2 on a 1:1 basis. The probability of the YTHDF2 expression level was used as a propensity score, and the nearest neighbor optimal matching algorithm was used to nd the best match for each patient. Successful matching was considered as the standard difference (SD) less than 0.2 (Table 3). Cox regression analysis was used to analyze the prognostic factors of patients with PSM. The high expression level of YTHDF2 and stage IV were independent risk factors affecting the prognosis of patients (Table 4). Moreover, survival analysis showed that patients with high expression of YTHDF2 had signi cantly better OS, and patients with stage IV had a worse OS than those with other stages ( Figure 4A and 4B). The potential role of YTHDF2 in GC To explore the potential role of YTHDF2 in GC, we identi ed 3066 differential expression genes (DEGs) [|log 2 (Fold Change)| > 1 and p <0.05] between the low and high expression level of YTHDF2 ( Figure 4C and 4D). The Gene Ontology (GO) analyses showed the DEGs were mainly enriched in cancer-and methylation-associated biological progress, cellular component and molecular function, such as histone modi cation, methylation, methyltransferase complex, histone methyltransferase complex, methyltransferase activity, and p53 binding ( Figure 5A and 5B). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analyses were primarily enriched in several cancer-associated pathways, such as cell cycle, RNA degradation, mismatch repair, viral carcinogenesis, apoptosis, and p53 signaling pathway.

Discussion
Over recent years, m6A methylation modi cation of RNA has received increasing attention. m6A was rst described in the 1970s. It is the most abundant internal modi er of mRNA and long noncoding RNA (lncRNA) in most eukaryotes [11]. With the development of high-throughput sequencing technology, m6A was found to be mainly distributed in stop and 3'-UTR regions [12][13][14]. The dynamic regulation of m6A modi cation has shown to be signi cantly associated with the occurrence and development of complex human diseases, including the progression of tumors [6,15,16].
A previous study suggested that m6A "reader" YTHDF1 promotes gastric carcinogenesis by regulating the translation of FZD7 and is associated with poor prognosis of GC [17]. Moreover, "writer" METTL3 promotes GC cell proliferation, promotes or inhibits GC progression by regulating the expression of downstream target genes, regulates MYC signaling pathway, and promotes epithelial-mesenchymal transition (EMT) and GC metastasis [18][19][20][21][22]. As for other m6A regulators, FTO, ALKBH5, WTAP, and KIAA 1429 are involved in the progression of GC, thus affecting the prognosis of patients [23][24][25]. Regretfully, so far, only a few studies have reported on the regulatory function of YTHDF2 and its effect on prognosis in GC.
YTHDF2 has been associated with the prognosis of patients with a variety of tumors, including hepatocellular carcinoma, prostate cancer, and osteosarcoma [26][27][28]. In this study, we found that m6A methylation regulator YTHDF2 is an independent protective prognostic factor for OS [p = 0.018; HR (95%  [29]. In this study, after PSM based on the expression of YTHDF2, stage III was no longer an independent prognostic risk factor for OS [p = 0.084; HR (95% CI): 2.15 (0.90-5.10)], but it still failed to change the poor prognosis of stage IV patients. Moreover, YTHDF2 was more likely expressed in female patients; but the difference in YTHDF2 expression between genders did not suggest it could affect the prognosis of patients.
Based on the functional analysis, we found that these differentially expressed genes were associated with a variety of tumor-related functions, including methylation, methyltransferase, cell cycle, RNA degradation, gene mismatch repair, apoptosis, and p53 signaling pathway. In addition, we also found that these genes are potentially associated with histone modi cation and histone methylation in GO analysis.
In our previous study, we discovered that histone methyltransferase SETD1A interacts with HIF1α to enhance glycolysis and promote GC progression [30]. Therefore, we believe that YTHDF2 has an important role in GC.
Our study has several limitations. The overall sample size is relatively small. Although we tried, we were not able to nd data sets containing valid clinical information in databases such as Gene-Expression Omnibus (GEO). We have predicted and analyzed the prognosis and function of YTHDF2; yet, additional in vivo and in vitro experiments should be performed to verify the results.

Conclusions
Our study is the rst study to predict m6A "reader" YTHDF2 as a protective prognosis factor in patients with GC. YTHDF2 may have a critical role in tumor regulation by regulating the expression of downstream target genes in GC.   (B-I) Differences of YTHDF2 expression among age, gender, stage, grade, subtype, T, N, and M groups. *p < 0.05, NS means no signi cance.

Figure 3
Prognosis analysis in subtypes of each baseline clinicopathological characteristics group. The hazard ratios (HR) and 95% con dence intervals (CI) were calculated by univariate Cox regression.

Figure 4
The survival and differential expression genes analysis of YTHDF2 in gastric cancer. (A, B) The survival analysis between low and high YTHDF2 expression groups before propensity score matching (A) and after propensity score matching (B). (C) Expression differences of the top 30 differential expression genes between low and high YTHDF2 expression groups. Red and blue represent the relatively high or low expression, respectively. (D) The volcano showed differential expression genes between low and high YTHDF2 expression groups.

Figure 5
The potential role and function of YTHDF2-related genes. Functional annotation of the differential expression genes between low and high YTHDF2 expression groups using GO (A, B) and KEGG pathway (C, D) analysis.

Supplementary Files
This is a list of supplementary les associated with this preprint. Click to download.