1. IntroductionGastric cancer (GC) is the third most common cause of cancer-related death globally, with a low 5-year survival rate [1]. Indeed, in recent years, with the establishment of multidisciplinary team (MDT) care, GC treatment has substantially improved. Albeit multiple therapeutic approaches are available currently, it is difficult to accurately determine the optimal treatment for an individual gastric cancer (GC) patient due to clinical and genetic heterogeneity [2]. The Lauren classification is an internationally recognized histopathological classification that sorts GC into three subtypes: intestinal type, diffuse type and mixed type [3]. However, several studies have shown significant heterogeneity in biological behavior among the three subtypes of gastric cancers [4,5,6,7]. Importantly, diffuse-type GC has been documented to exhibit more aggressive behavior and a poorer prognosis, accounting for one-third of all GC patients [5]. This subtype of GC is more common in women and younger patients and is more genetic-related [8]. Nowadays, the AJCC TNM staging system is widely used to evaluate the prognosis of GC patients [9,10]. Nevertheless, multiple studies reported that the AJCC TNM staging system sometimes exhibited poor accuracy in predicting the prognosis of cancer patients, partly due to staging migration [11]. With the advancement of cancer molecular biology, cancer-specific gene signatures have been harnessed to develop new prediction tools. However, there are limited prognosis-related genes associated with diffuse-type GC. Accordingly, an effective prediction model is urgently needed to help oncologists evaluate GC patient prognosis in the clinic.

In this study, we obtained three GC datasets with Lauren classification data from the GEO database to identify differentially expressed genes (DEGs). Then, the DEGs were validated with external datasets. Univariate regression analysis and Kaplan–Meier analysis were applied to select the overall survival-related DEGs. A prognostic nomogram incorporating prognostic gene signatures and clinical survival-related characteristics was established to predict overall survival. In summary, we uncovered new gene signatures for diffuse-type GC and established a nomogram that exhibited good performance in predicting the overall survival of diffuse-type GC patients.

4. DiscussionCompared to intestinal-type gastric cancer, diffuse-type gastric cancer exhibits a more aggressive phenotype with a relatively poor prognosis and a 5-year overall survival rate of 32.1% [15]. It is widely acknowledged that the treatment failure of diffuse-type gastric cancer is due to drug resistance and disease progression, including tumor recurrence and metastasis. The prognostic model is important to clinicians to provide individualized treatment by determining which patients would benefit most from a particular or a combination of treatment approaches, including radical surgery, adjuvant chemotherapy, neoadjuvant chemotherapy, targeted molecular medicine or immunotherapy. However, today the big problem is that the prognostic model based on clinical characteristics and histopathological characteristics is not accurate [16,17]. Accordingly, it is important to develop a novel prognostic model for improving patient management by stratifying patients according to their characteristics.In the present study, we constructed a nomogram that incorporated a two-gene (MEF2C and TRIM15) signature and clinicopathological parameters to assist clinicians in determining the prognosis of individual diffuse-type GC patients. The sensitivity and specificity of our prognostic model were more satisfying than the TNM staging system (Figure 5). Gene set enrichment analysis showed that MEF2C and TRIM15 were closely related to invasive and metastasis signaling pathways in diffuse-type gastric cancer. The MAPK signaling pathway was the most significant in the high MEF2C expression group of diffuse-type gastric cancer (Figure 7A). Moreover, the glycosaminoglycan biosynthesis chondroitin sulfate signaling pathway was the most enriched in the low TRIM15 expression group of diffuse-type gastric cancer (Figure 7B). MEF2C upregulation and TRIM15 downregulation in diffuse-type gastric cancer were related to poor prognoses.In recent years, multiple gene signatures, mRNAs or non-coding RNAs have been used to evaluate the prognosis of gastric cancer patients [18,19,20]. Nevertheless, rare studies have focused on the Lauren subtype-specific gene signature to evaluate the prognosis of diffuse-type gastric cancer. Moreover, few studies have sought to combine the TNM stage with the multi-gene signature to assess the prognosis of diffuse-type gastric cancer. A previous study reported a three-gene signature to predict the prognosis of diffuse-type gastric cancer [21]. However, the prognostic model only considered the three-gene expression level, but lacked the clinical parameters of the diffuse-type gastric cancer patients. The TNM staging system only considers tumor invasion depth, lymph node metastasis and distant metastasis. The biological characteristics of the tumors, such as the immune infiltration status, drug response and intracellular signal pathways are not reflected in the TNM staging system. However, the genomic sequence of the tumor is an effective tool to uncover heterogeneous malignance [22,23]. Several tumor biomarkers can help guide treatment decisions, including Human Epidermal Growth Factor Receptor-2 (HER2), Programmed Cell Death-Ligand 1 (PDL1) and Vascular Endothelial Growth Factor Receptor (VEGFR) [24,25,26]. Accordingly, in the current study, we identified risk factors, including age, T stage, N stage, M stage, the expression level of TRIM15 and MEF2C and established a prognostic model. Finally, a nomogram integrating a two-gene signature and clinicopathologic features was constructed and yielded an accurate prediction of overall survival. Through ROC curves, Kaplan–Meier analysis and decision curve analysis of the external validation in the TCGA-STAD dataset, as a supplement to AJCC staging, our two-gene signature and nomogram demonstrated a similar predictive performance with the training set (Figure 5). Our predictive nomogram will exhibit a potential value of diffuse-type GC in future clinical practice. Similarly, several previous studies integrated clinical features and risk scores based on the expression level of risk genes into a novel prognostic nomogram [27,28,29]. The predictive value of their integrated nomograms was also better than using the risk factor alone. These studies and our present study have a certain reference significance for future clinical research.MEF2C and TRIM15 have previously been reported to be associated with gastric cancer. Interestingly, Myocyte Enhancer Factor 2C (MEF2C) has been documented in pathways of organelle biogenesis and maintenance and transcriptional misregulation in cancer, which involved DNA-binding transcription factor activity and protein heterodimerization activity. MEF2C has been associated with DNA methylation and enhanced PD-L1 expression in gastric cancer [30,31]. Recent studies have also shown that MEF2C plays an important role in myocilin mediating cancer-induced muscle wasting and cachexia in cancer patients [32] and regulates chemotherapeutic resistance [33] and the disease progression of acute myeloid leukemia [34]. TRIM15 is a member of the tripartite motif (TRIM) family. The protein encoded by TRIM15 has a TRIM motif, including three zinc-binding domains, a RING, a B-box type 1, a B-box type 2 and a coiled-coil region. However, the biological function of TRIM15 remains unknown. Our GSEA results showed that TRIM15 was correlated with the glycosaminoglycan biosynthesis chondroitin sulfate signaling pathway in diffuse-type gastric cancer. Importantly, a recent study has found that the expression of TRIM15 is an independent risk factor of prognosis in gastric cancer patients [35]. However, the roles of the MEF2C and TRIM15 genes in diffuse-type gastric cancer are still unclear. Our current study disclosed that MEF2C and TRIM15 could promote invasion and metastasis through cancer-related signaling pathways: the MEF2C-activated MAPK signaling pathway and the TRIM15-activated glycosaminoglycan biosynthesis chondroitin sulfate signaling pathway (Figure 7). Moreover, our studies revealed poor prognoses associated with upregulated MEF2C and downregulated TRIM15 expression in diffuse-type gastric cancer. Accordingly, the present research revealed the roles of these two genes in diffuse-type gastric cancer and established a risk model to complement the AJCC staging system to improve the outcomes of diffuse-type gastric cancer. However, further in vivo studies are needed to explore the molecular mechanism underlying the oncological function of these two genes in diffuse-type gastric cancer.

This study contains several limitations. First, our study was based on RNA sequence data rather than proteomics, which could have affected the accuracy of our prediction model. Accordingly, the expression of these two genes should be analyzed in another study with a large sample of diffuse-type gastric cancer patients to validate the predictive performance of our model. Furthermore, it may be hard to promote the utilization of multi-genome sequencing during clinical practice due to its high price and practicability. With the development of sequencing technology and precision medicine, the identified two-gene signature will be clinically feasible. Moreover, our predictive model should be externally validated with another large sample of diffuse-type gastric cancer patients.