Interleukin (IL)-8 and extracellular signal-regulated kinase (ERK) 2 play key roles in tumor progression, but the relationship between IL-8 and/or ERK2 expression in hepatocellular carcinoma (HCC) tissues and postoperative recurrence or survival is unclear. The expression levels of IL-8 and ERK2 in both HCC tissues and non-tumor liver tissues were analyzed using the Oncomine™ database and immunohistochemistry assay. Reverse transcription-quantitative PCR was then used to evaluate the expression levels of IL-8 and ERK2 in the tumor tissues of 67 patients with HCC undergoing radical hepatectomy. Pearson's correlation, Kaplan-Meier, Cox univariate and multivariate survival analyses were utilized to determine the correlation between IL-8 and ERK2 expression in HCC tissues, and their potential prognostic significance. As indicated by the data from the Oncomine™ database, and the patient samples, IL-8 and ERK2 were expressed at significantly higher levels in HCC tissues than in non-tumor liver tissues (P<0.05). The rates of high IL-8 and ERK2 expression in HCC tissues were 43.28 (29/67) and 34.33% (23/67), respectively, and the IL-8 and ERK2 expression levels were positively correlated (r=0.764; P<0.001). Both ERK2 expression and IL-8/ERK2 co-expression were significantly associated with tumor size and differentiation (P<0.05). Additionally, high expression levels of IL-8, ERK2 and IL-8/ERK2 co-expression were all significantly associated with poor overall survival (OS; P<0.05) and disease-free survival (DFS; P<0.05). Multivariate Cox regression analysis also showed that high expression levels of IL-8, ERK2, and IL-8 and ERK2 were independent prognostic factors for OS and DFS (P<0.05). The results of the present study indicate a significant increase in the risk of recurrence and mortality in HCC patients with high expression levels of IL-8 and/or ERK2, compared with patients with low expression. Therefore, IL-8 and ERK2 may be predictors of postoperative prognosis in patients with HCC.

ObjectiveAlternative splicing (AS) is the mechanism by which a few genes encode numerous proteins, and it redefines the concept of gene expression regulation. Recent studies showed that dysregulation of AS was an important cause of tumorigenesis and microenvironment formation. Therefore, we performed a systematic analysis to examine the role of AS in breast cancer (Breast Cancer, BrCa) progression.MethodsThe present study included 993 BrCa patients from The Cancer Genome Atlas (TCGA) database in the genome-wide analysis of AS events. We used differential and prognostic analyses and found differentially expressed alternative splicing (DEAS) events and independent prognostic factors related to patients’ overall survival (OS) and disease-free survival (DFS). We divided the patients into two groups based on these AS events and analyzed their clinical features, molecular subtyping and immune characteristics. We also constructed a splicing factor (SF) regulation network for key AS events and verified the existence of AS events in tissue samples using real-time quantitative PCR.ResultsA total of 678 AS events were identified as differentially expressed, of which 13 and 10 AS events were independent prognostic factors of patients’ OS and DFS, respectively. Unsupervised clustering analysis based on these prognostic factors indicated that the Cluster 1 group had a better prognosis and more immune cell infiltration. SFs were significantly related to the expression of AS events, and AA-RPS21 was significantly upregulated in tumors.ConclusionAlternative splicing expands the mechanism of breast cancer progression from a new perspective. Notably, alternative splicing may affect the patient’s prognosis by affecting the infiltration of immune cells. Our research provides important guidance for subsequent studies of AS in breast cancer.

Background: T4a gastric cancer (GC) is a subtype of advanced GC (AGC), which urgently needs a comprehensive grade method for better treatment strategy choosing. The purpose of this study was to develop two nomograms for predicting the prognosis of patients with T4a GC.Methods: A total of 1,129 patients diagnosed as T4a GC between 2010 and 2015 were extracted from the Surveillance, Epidemiology, and End Result (SEER) program database. Univariate and multivariate Cox analyses were performed to explore the independent predictors and to establish nomogram for overall survival (OS) of the patients, whereas competing risk analyses were performed to find the independent predictors and to establish nomogram for cancer-specific survival (CSS) of the patients. The area under the curve (AUC), calibration curve, decision curve analysis (DCA), and Kaplan–Meier analysis were performed to evaluate the nomograms.Results: Older age, larger tumor size, black race, signet ring cell carcinoma (SRCC), more lymph node involvement, the absence of surgery, the absence of radiotherapy, and the absence of chemotherapy were identified as independent prognostic factors for both OS and CSS. In the training cohort, the AUCs of the OS nomogram were 0.760, 0.743, and 0.723 for 1-, 3-, and 5-year OS, whereas the AUCs of the CSS nomogram were 0.724, 0.703, and 0.713 for 1-, 3-, and 5-year CSS, respectively. The calibration curve and DCA indicated that both nomograms can effectively predict OS and CSS, respectively. The abovementioned results were also confirmed in the validation cohort. Stratification of the patients into high- and low-risk groups highlighted the differences in prognosis between the two groups both in training and in validation cohorts.Conclusions: Age, tumor size, race, histologic type, N stage, surgery status, radiotherapy, and chemotherapy were confirmed as independent prognostic factors for both OS and CSS in patients with T4a GC. Two nomograms based on the abovementioned variables were constructed to provide more accurate individual survival predictions for them.