Purpose: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the clinic all over the world, which has become a public health challenge. The T/N/M staging system plays a core role in HCC prognosis. However, it cannot precisely stratify the risk of HCC prognosis. MiR-454-3p plays an important role in the progression of tumors. Therefore, we need to develop more reliable prognostic markers for HCC patients which can focus on miR-454-3p. Methods: We used Chi-square and Fisher exact tests to assess correlations between miR-454-3p expression and clinical parameters in liver cancer patients from The Cancer Genome Atlas database (TCGA). Then, Cox regression analysis, Kaplan-Meier curve, and log-rank test were used to compare the difference of survival between the high-expression group and low-expression group, and P value was included. Finally, we used TCGA data set to carry out gene enrichment analysis. Results: In this research, the expression of miR-454-3p increased in HCC and was associated with patient survival, G3/G4 staging, III/IV staging and T staging. Higher miR-454-3p expressed patients had shorter survival time. Besides, mitotic spindle, G2M checkpoint, and E2F targets were differentially enriched in miR-454-3p high-expression phenotype by Gene set enrichment analysis. Conclusion: Overexpression of miR-454-3p may be a significant and independent predictor of poor prognosis in HCC patients.

Breast cancer is a frequent female malignant tumor with high mortality and poor prognosis. Peroxidasin like (PXDNL) has many biological functions, including characteristic activity of hormone biosynthesis, host defense, and cell motility. In addition, PXDNL is closely connected with the progression of breast cancer. In this study, we found that PXDNL may be an independent prognostic biomarker of breast cancer. We tested the mRNA expression of PXDNL in breast cancer by detecting The Cancer Genome Atlas (TCGA) database. The chi-squared test was used to evaluate clinical correlation. The receiver operating characteristic (ROC) curves were drawn to evaluate diagnosis potential in breast cancer. Subsequently, survival analyses were performed to identify the relevance between the expression of PXDNL and the overall survival/relapse-free survival of patients with breast cancer. Univariate/multivariate Cox regression model was executed to detect risk factors affecting the prognosis of patients with breast cancer. PXDNL is highly expressed in breast cancer tissues and is related to survival status of patients. The ROC curve showed that PXDNL had beneficial diagnostic ability in breast cancer. Survival analysis indicated that patients with breast cancer with high PXDNL expression generally had decreased overall survival/relapse-free survival. Univariate/multivariate Cox model analyses further suggested an association between PXDNL expression and prognosis of patients with breast cancer. High PXDNL expression is a potential and independent prognostic biomarker in breast cancer.

Ovarian cancer has the highest mortality among gynecological cancers. Although ovarian cancer usually responds well to chemotherapy, most patients still have a poor prognosis. EIF2B5 is a crucial molecule in posttranscriptional modifications involved in tumor progression, and here we investigated the prognostic role of EIF2B5 in ovarian cancer. We examined the differential expression of EIF2B5 mRNA in ovarian cancer by exploring The Cancer Genome Atlas (TCGA) database. The chi square test was used to identify a clinical correlation. Survival analysis and Cox regression model were performed to determine the association between EIF2B5 expression and overall survival (OS) in ovarian cancer patients. As a result, Low EIF2B5 expression was found in ovarian cancer tissues and correlated with survival status. Survival analysis showed that ovarian cancer patients with low EIF2B5 expression had a short OS. Moreover, Cox regression analysis indicated that low EIF2B5 expression was an independent risk factor for a poor prognosis in ovarian cancer. Additionally, according to gene set enrichment analysis, mesenchymal transition, angiogenesis, coagulation, and bile acid metabolism were differentially enriched in ovarian cancer with high EIF2B5 expression. In conclusion, Low EIF2B5 expression is an independent risk factor for a poor prognosis in ovarian cancer patients.