Background/Aims: Renal cell carcinoma (RCC) is currently the ninth most common cancer in men. Interleukin (IL)-33 expression has previously been associated with a number of cancers; however, its biological role in RCC is poorly understood. In this study, we sought to elucidate the role of IL-33 in RCC. Methods: Serum IL-33 levels were measured by ELISA. IL-33 expression in clinical RCC samples was examined by immunocytochemistry. The proliferation and apoptosis rate of RCC were determined by CCK8 and flow cytometry. Mcl1 and Bcl-2 expression were measured by quantitative real-time PCR and western blotting. JNK expression were measured by western blotting and flow cytometry. The in vivo role of IL-33 in RCC tumorigenesis was examined by animal models. Results: We found that increased expression of IL-33 in RCC was associated with tumor-lymph node-metastasis (TNM) stage and inversely correlated with prognosis. IL-33 enhances RCC cell growth in vivo and stimulates RCC cell proliferation and prevents chemotherapy-induced tumor apoptosis in vitro. Furthermore, we demonstrated that IL-33 promotes RCC cell proliferation and chemotherapy resistance via its receptor ST2 and the JNK signaling activation in tumor cells. Conclusion: Our findings suggest that targeting IL-33/ST2 and JNK signaling may have potential value in the treatment of RCC.
Background Gastric cancer (GC) is one of the most common carcinomas of the digestive tract, and the prognosis for these patients may be poor. There is evidence that some long non-coding RNAs(lncRNAs) can predict the prognosis of patients with GC. However, few lncRNA signatures have been used to predict prognosis. Herein, we aimed to construct a risk score model based on the expression of five lncRNAs to predict the prognosis of patients with GC and provide new potential therapeutic targets. Methods We performed differentially expressed and survival analyses to identify differentially expressed survival-ralated lncRNAs by using GC patient expression profile data from The Cancer Genome Atlas (TCGA) database. We then established a formula including five lncRNAs to predict the prognosis of patients with GC. In addition, to verify the prognostic value of this risk score model, two independent Gene Expression Omnibus (GEO) datasets, GSE62254 (N = 300) and GSE15459 (N = 200), were employed as validation groups. Results Based on the characteristics of five lncRNAs, patients with GC were divided into high or low risk subgroups. The prognostic value of the risk score model with five lncRNAs was confirmed in both TCGA and the two independent GEO datasets. Furthermore, stratification analysis results showed that this model had an independent prognostic value in patients with stage II–IV GC. We constructed a nomogram model combining clinical factors and the five lncRNAs to increase the accuracy of prognostic prediction. Enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) suggested that the five lncRNAs are associated with multiple cancer occurrence and progression-related pathways. Conclusion The risk score model including five lncRNAs can predict the prognosis of patients with GC, especially those with stage II-IV, and may provide potential therapeutic targets in future.
Objective. To explore the expression, functions, and the possible mechanisms of cysteine-rich intestinal protein 1 (CRIP1) in epithelial ovarian cancer. Methods. Using open microarray datasets from The Cancer Genome Atlas (TCGA), we identified the tumorigenic genes in ovarian cancer. Then, we detected CRIP1 expression in 26 pairs of epithelial ovarian cancer tissue samples by immunohistochemistry (IHC) and performed a correlation analysis between CRIP1 and the clinicopathological features. In addition, epithelial ovarian cancer cell lines A2780 and OVCAR3 were used to examine CRIP1 expression by western blot and qRT-PCR. Various cell function experiments related to tumorigenesis were performed including the CCK8 assay, EdU, Annexin V-FITC/PI apoptosis assay, wound healing, and Transwell assay. In addition, the expression of epithelial-mesenchymal transition (EMT) markers was detected by western blot to illustrate the relationship between CRIP1 and EMT. Furthermore, KEGG pathway enrichment analysis and western blot were conducted to reveal the signaling pathways in which CRIP1 is involved in ovarian cancer pathogenesis. Results. CRIP1 was identified as an oncogene from the TCGA database. The IHC score demonstrated that the CRIP1 protein was expressed at a higher level in tumours than in tumour-adjacent tissues and was associated with a higher pathological stage, grade, and positive lymphatic metastasis. In cell models, CRIP1 was overexpressed in serous epithelial ovarian cancer. Cell function experiments showed that the knockdown of CRIP1 did not significantly affect cell proliferation or apoptosis but could exert an inhibitory effect on cell migration and invasion, and also induce changes in EMT markers. Furthermore, KEGG pathway enrichment analysis and western blot showed that CRIP1 could induce ovarian cancer cell metastasis through activation of the Wnt/β-catenin pathway. Conclusion. This study is the first to demonstrate that CRIP1 acts as an oncogene and may promote tumour metastasis by regulating the EMT-related Wnt/β-catenin signaling pathway, suggesting that CRIP1 may be an important biomarker for ovarian cancer metastasis and progression.
Background: Epithelial ovarian cancer (EOC) ranks first for female gynecological tumor-related deaths.Due to the limited efficacy of traditional chemotherapy strategies, potential therapeutic targets are urgently needed. Previous studies have reported a relationship between abnormal spindle-like microcephalyassociated protein (ASPM) and ovarian cancer based on immunohistochemistry (IHC) and bioinformatics analysis. However, the potential role of ASPM in the proliferation of ovarian cancer cells and its molecular mechanism remain to be elucidated. Therefore, we aimed to further investigate the potential role of ASPM and its underlying mechanism in EOC using integrated online databases, clinical samples, and cell models. Methods:We used online databases (Gene Expression Profiling Interactive Analysis, Cbioportal and Kaplan-Meier Plotter) to analyze differential ASPM expression in ovarian carcinoma and explore its prognostic value in ovarian cancer (OvCa) patients. Immunohistochemistry staining based on a clinical tissue microarray (TMA) comprised 75 cases of EOC tissue and 5 cases of adjacent normal ovary tissue was used to detect the ASPM expression and analyze the relationship between ASPM expression and EOC characteristics. Various cell function experiments related to tumorigenesis were performed including the CCK8 assay, 5-ethynyl-2'-deoxyuridine (EdU), colony formation assay and Transwell assay in EOC cell models (A2780 and OVCAR3) with knocked down ASPM by small interfering RNA (siRNA) to observe its role. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment was conducted to determine the signaling pathways in which ASPM was involved in the pathogenesis of ovarian cancer.Analysis of cell cycle distribution using flow cytometry was further performed to verify the pathways. Results:The expression profile based on data from The Cancer Genome Atlas (TCGA) database confirmed ASPM expression in EOC was higher compared with normal tissue, and further analysis suggested that higher expression was correlated with worse patient prognosis. Immunohistochemical analysis further indicated that ASPM was highly expressed in OvCa tissues and associated with a higher pathological stage, grade, and positive lymphatic metastasis. Cell models with knocked down ASPM by small interfering RNA (siRNA) significantly inhibited proliferation and migration. KEGG pathway enrichment and cell cycle analysis showed that ASPM silencing could inhibit ovarian cancer cell proliferation via synthesis (S) phase arrest.Conclusions: Our study confirmed that ASPM promoted proliferation and caused S phase arrest in EOC cells. ASPM may become a potential molecular marker for early screening and a valuable therapeutic target in EOC.
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