In this study, the differentially expressed miRNAs in STAD were identified by bioinformatics technology using the TCGA-STAD database. The differentially expressed miRNAs were then integrated with clinical parameters to establish a prognostic risk model, which was composed of the five differentially expressed miRNAs. This model was shown to have a good prognostic performance in the training set, test set, and all patients, as the AUC of the ROC curve was greater than 0.7, indicating a moderate accuracy when it was used to predict the 3-year survival. More importantly, multivariate Cox regression analysis further demonstrated that this model could independently predict the prognosis of STAD. Therefore, the five differentially expressed miRNAs included in this model can be used as a biomarker for the prediction of OS of STAD patients. Based on the analysis of the miRNA target genes and their enrichment pathways, several gastric cancer-related signaling pathways were found, including the Notch, mitogen-activated protein kinase, and transforming growth factor-beta signaling pathways. Furthermore, our study found a potential role of our prognostic risk model in the molecular pathogenesis, clinical progression, and prognosis of gastric cancer, which is likely to aid in the preventive diagnosis and individualized treatment of gastric cancer.
Among the five differentially expressed miRNAs mentioned above, two of them (miR-143-5p and miR-9-3p) indicated a high risk of STAD (their expression level was negatively correlated with the OS). They have been considered as tumor-suppressor genes in recent years, such as miR-143-5p in lung cancer, esophageal cancer, pancreatic cancer, gallbladder cancer, and osteosarcoma; and miR-9-3p in bladder cancer, liver cancer, nasopharyngeal cancer, and breast cancer. However, there is no related report about the functions of miR-143-5p and miR-9-3p in human gastric cancer. The results of the data from the TCGA-STAD database indicated that both of them have a low expression level in STAD. Our experiments also found that the expression level of both of these miRNAs in the gastric cancer cell line was lower than that in the normal gastric cell line. In our prognostic model, the cases with highly expressed miR-143-5p and miR-9-3p had a positive correlation with a poor prognosis. Therefore, the specific mechanism of the role of these two miRNAs in gastric cancer still needs to be further clarified.
Meanwhile, the three other miRNAs, including miR-135b-3p, miR-196b-3p, and miR-942-3p, indicated a low risk of STAD (the expression level was positively correlated with the OS). Currently, the specific mechanism of these three miRNAs has been rarely studied, and their correlation with gastric cancer also needs further study. It is believed that with further in-depth studies, the biological role and potential mechanism of these miRNAs will become clearer.
According to ROC curve analysis, the AUC value of our prognostic risk model was greater than 0.7 (between 0.7 and 0.9) in both the training group and the test group, indicating that the prognostic model had a moderate accuracy for the diagnosis of STAD. Univariate and multivariate Cox regression analyses revealed that this model could independently predict the OS (HR = 1.971, P < 0.001).
However, our study still has some shortcomings, such as the fact that the random assignment of data came from a single database into the training set and the test set. A separate set of external tests should be created to make the results more convincing. Second, the follow-up time of the TCGA-STAD study cohort was relatively short (the average follow-up time was only 20.78 months), and the exclusion rate was relatively high, which may reduce the reliability of the Kaplan–Meier analysis method. In the future, it is necessary to recruit more STAD patients and to conduct longer follow-up studies in order to verify the findings of this study. In addition, the complex effects and specific mechanisms of these differentially expressed miRNAs in STAD need to be further investigated.