Circular RNAs (circRNAs) play an essential regulatory role in multiple cancers. However, the role of a large number of circRNAs in gastric cancer (GC) is still unknown. Here, hsa_circ_0139996 (circREPS2), a novel circRNA that was significantly downregulated in GC, was selected for further investigation. circREPS2 was validated and analyzed by DNA sequencing and quantitative real-time PCR. The roles of circREPS2 in GC cells were verified by gain- and loss-of-function experiments. Bioinformatics analysis, luciferase reporter, RNA pull-down, and RNA immunoprecipitation assays were performed to evaluate the functional mechanism of circREPS2 on microRNA-558 (miR-558)/RUNX3/β-catenin axis in GC cells. In the present study, we found that circREPS2 was downregulated in GC tissues and cell lines. Low expression of circREPS2 was associated with a higher tumor-node-metastasis (TNM) stage, poor tumor differentiation, and larger tumor size in GC patients. Functionally, circREPS2 significantly inhibited GC cell proliferation, migration, invasion, and epithelial-mesenchymal transformation (EMT) in vitro and tumorigenesis in vivo. Furthermore, our data demonstrated that circREPS2 acted as a miR-558 sponge and upregulated RUNX3 expression to inactivate β-catenin signaling in GC cells. In conclusion, circREPS2 suppresses the progression of GC via miR-558/RUNX3/β-catenin signaling and is a novel promising biomarker and target for GC treatment.

Gastric cancer (GC) is a serious malignant tumor with high mortality and poor prognosis. The prognosis and survival are much worse for advanced gastric cancer (AGC). Recently, immunotherapy has been widely promoted for AGC patients, and studies have shown that tumor mutation burden (TMB) is closely related to immunotherapy response. Here, RNA-seq data, matched clinical information, and MAF files were downloaded from the cancer genome atlas (TCGA)-STAD project in the TCGA database. The collation and visual analysis of mutation data were implemented by the “maftools” package in R. We calculated the TMB values for AGC patients and divided the patients into high- and low-TMB groups according to the median value of TMB. Then, the correlation between high or low TMB and clinicopathological parameters was calculated. Next, we examined the differences in gene expression patterns between the two groups by using the “limma” R package and identified the immune-related genes among the DEGs. Through univariate Cox regression analysis, 15 genes related to prognosis were obtained. Furthermore, the two hub genes (APOD and SLC22A17) were used to construct a risk model to evaluate the prognosis of AGC patients. ROC and survival curves and GEO data were used as a validation set to verify the reliability of this risk model. In addition, the correlation between TMB and tumor-infiltrating immune cells was examined. In conclusion, our results suggest that AGC patients with high TMB have a better prognosis. By testing the patient’s TMB, we could better guide immunotherapy and understand patient response to immunotherapy.

DEP domain containing 1 (DEPDC1) functions as an oncogene in hepatocellular carcinoma (HCC). However, the underlying mechanism of DEPDC1 remains largely unknown. The present study revealed that DEPDC1 knockdown inhibited HCC cell proliferation, colony formation and invasion in vitro and suppressed the growth of HCC xenografts in vivo. Furthermore, DEPDC1 overexpression promoted HCC cell proliferation, colony formation and invasion. DNA microarray, reverse transcription-quantitative-PCR and western blotting results demonstrated that DEPDC1 knockdown in Huh-7 significantly inhibited the expression of chemokine (C-C motif) ligand 20 (CCL20) and chemokine (C-C motif) receptor 6 (CCR6). In addition, the expression of CCL20 and CCR6 were upregulated in HCC tissues and cell lines, and were positively correlated with DEPDC1 expression. CCL20 or CCR6 knockdown via small interfering RNA reversed the effects of DEPDC1 overexpression in HCC cells. Furthermore, it was revealed that conditioned medium from DEPDC1 upregulated Li-7 and Hep3B cells led to angiogenesis in vitro, whereas CCL20 knockdown in Li-7 and Hep3B cells or CCR6 knockdown in human umbilical vein endothelial cells reversed the angiogenic effect of DEPDC1 overexpression. In conclusion, DEPDC1 facilitated cell proliferation, invasion and angiogenesis via the CCL20/CCR6 pathway in HCC.

Colorectal cancer (CRC) is a malignant tumor with high morbidity and mortality worldwide. Recent studies have shown that long noncoding RNAs (lncRNAs) play an important role in almost all human tumors, including CRC. Competitive endogenous RNA (ceRNA) regulatory networks have become hot topics in cancer research. Tumor-infiltrating immune cells (TICs) have also been reported to be closely related to the survival and prognosis of CRC patients. In this study, we used the lncRNA–miRNA–mRNA regulatory network combined with tumor immune cell infiltration to predict the survival and prognosis of 598 CRC patients. First, we downloaded the lncRNA, mRNA, and miRNA transcriptome data of CRC patients from The Cancer Genome Atlas (TCGA) database and identified differentially expressed genes through “limma” package of R software. The ceRNA regulatory network was established by using the “GDCRNATools” R package. Then, univariate Cox analysis and least absolute shrinkage and selection operator analysis were performed to identify the optimal prognostic network nodes, including SRPX, UST, H19, SNHG7, hsa-miR-29b-3p, and TTYH3. Next, we analyzed the differences in 22 types of TICs between 58 normal subjects and 206 CRC patients and included memory CD4 T cells, dendritic cells and neutrophils in the construction of a prognostic model. Finally, we identified the relationship between the ceRNA prognostic model and the infiltrating immune cell prognostic model. In conclusion, we constructed two prognostic models that provide insights on the prognosis and treatment strategy of CRC.

Emerging evidence indicated that circular RNAs (circRNAs) play essential roles in cancer progression. A large number of circRNAs have been reported to modulate cancer carcinogenesis. However, the underlying mechanisms by which circRNAs regulate gastric cancer remain largely unclear. By using circRNA microarray, we identified that circRAB31 may serve as a tumor suppressor. circRAB31 was downregulated in gastric cancer tissues and gastric cancer cell lines compared with normal tissues and a human gastric epithelial cell line (GES-1). Overexpression of circRAB31 suppressed gastric cancer proliferation and metastasis in vitro and in vivo, whereas silencing of circRAB31 had the opposite effects. Bioinformatic analysis as well as pull-down and luciferase assays revealed that circRAB31 exerted tumor-suppressive functions by binding directly to miR-885-5p. In addition, we demonstrated that circRAB31 could suppress PI3K/AKT signaling via the phosphatase and tensin homologue (PTEN)—a downstream target gene of miR-885-5p. In summary, our results demonstrated that circRAB31 could serve as a sponge of miR-885-5p to regulate gastric cancer cell proliferation, migration, and invasion by affecting the PTEN/PI3K/AKT signaling.

Esophageal cancer (EC) is a serious malignant tumor, both in terms of mortality and prognosis, and immune-related genes (IRGs) are key contributors to its development. In recent years, immunotherapy for tumors has been widely studied, but a practical prognostic model based on immune-related genes (IRGs) in EC has not been established and reported. In this study, we downloaded the gene expression profiles and matched clinical data of EC patients from The Cancer Genome Atlas (TCGA) database. We found 4,094 differentially expressed genes (DEGs) between EC and normal esophageal tissue (p2). Then, the intersection of DEGs and the immune genes in the ‘ImmPort’ database resulted in 303 differentially expressed immune-related genes (DEIRGs). Next, through univariate Cox regression analysis of DEIRGs, we obtained 17 immune genes related to prognosis. We detected nine optimal prognostic-associated IRGs (HSPA6, CACYBP, DKK1, EGF, FGF19, GAST, OSM, ANGPTL3, NR2F2) by Using Lasso regression and multivariate Cox regression analyses. Finally, we used those prognostic-associated IRGs to construct a risk model to predict the prognosis of EC patients. This model could accurately predict overall survival in EC and could be used as a classifier for the evaluation of low-risk and high-risk groups. In conclusion, we identified a practical and robust nine-gene prognostic model based on immune gene dataset. These genes may provide valuable biomarkers and prognostic predictors for EC patients and could be further studied to help understand the mechanism of EC occurrence and development.