miR193b Promotes Apoptosis of Gastric Cancer Cells via Directly Mediating the Akt Pathway

An emphasis on the interaction of signaling pathways highlights the role of miRNAs in the etiology and treatment resistance of gastric cancer

Gastric cancer (GC) is 4th in incidence and mortality rates globally. Several genetic and epigenetic factors, including microRNAs (miRNAs), affect its initiation and progression. miRNAs are short chains of nucleic acids that can regulate several cellular processes by controlling their gene expression. So, dysregulation of miRNAs expressions is associated with GC initiation, progression, invasion capacity, apoptosis evasions, angiogenesis, promotion and EMT enhancement. Of important pathways in GC and controlled by miRNAs are Wnt/β-catenin signaling, HMGA2/mTOR/P-gp, PI3K/AKT/c-Myc, VEGFR and TGFb signaling. Hence, this review was conducted to review an updated view of the role of miRNAs in GC pathogenesis and their modulatory effects on responses to different GC treatment modalities.

The Molecular Roles and Clinical Implications of Non-Coding RNAs in Gastric Cancer

Gastric cancer (GC) is one of the most common malignancies in the world. It is also the fifth most common cancer in China. In recent years, a large number of studies have proved that non-coding RNAs (ncRNAs) can regulate cell proliferation, invasion, metastasis, apoptosis, and angiogenesis. NcRNAs also influence the therapeutic resistance of gastric cancer. NcRNAs mainly consist of miRNAs, lncRNAs and circRNAs. In this paper, we summarized ncRNAs as biomarkers and therapeutic targets for gastric cancer, and also reviewed their role in clinical trials and diagnosis. We sum up different ncRNAs and related moleculars and signaling pathway in gastric cancer, like Bcl-2, PTEN, Wnt signaling. In addition, the potential clinical application of ncRNAs in overcoming chemotherapy and radiotherapy resistance in GC in the future were also focused on.

Combined Action of Anti-MUC1 Monoclonal Antibody and Pyrazole-Platinum(II) Complexes Reveals Higher Effectiveness towards Apoptotic Response in Comparison with Monotherapy in AGS Gastric Cancer Cells

MUC1 mucin is a transmembrane glycoprotein aberrantly overexpressed and underglycosylated in most epithelium origin cancers. Combining chemotherapeutics with monoclonal antibodies toward cancer-related antigens is one of the new strategies in cancer therapies. In this study, we assessed the effectiveness of 10 μM cisplatin (cisPt), two pyrazole-platinum(II) complexes (PtPz4 and PtPz6), and 5 μg/mL anti-MUC1 used as monotherapy, as well as cisplatin and its derivatives combined with mAb on apoptotic response and specific cancer-related sugar antigens in AGS gastric cancer cells. Flow cytometry, RT-PCR, Western blotting, and ELISA tests were applied to determine the influence of examined compounds on analyzed factors. PtPz6 combined with anti-MUC1 revealed the strongest apoptotic response compared to control and monotherapy. The combined action of both cisPt derivatives and anti-MUC1 was more effective than monotherapy in relation to Bad, Bcl-xL, Bcl-2, caspase-9, caspase-3, as well as pro- and cleaved caspase-3 protein, and T, sialyl Tn sugar antigens in cell lysates, and Tn, T, sialyl Tn, sialyl T antigens in culture medium. Additionally, PtPz4 administrated with mAb was revealed to be more potent than used alone with regard to Bax protein and Bid expression, and PtPz6 used in complex with anti-MUC1 revealed more efficient action towards Akt and sialyl T antigen expression. These data indicate the rationality of the potential application of combined treatment of anti-MUC1 and cisPt derivatives in gastric cancer therapy.

Identification of Hub Genes and Construction of a Transcriptional Regulatory Network Associated With Tumor Recurrence in Colorectal Cancer by Weighted Gene Co-expression Network Analysis

Tumor recurrence is one of the most important risk factors that can negatively affect the survival rate of colorectal cancer (CRC) patients. However, the key regulators dictating this process and their exact mechanisms are understudied. This study aimed to construct a gene co-expression network to predict the hub genes affecting CRC recurrence and to inspect the regulatory network of hub genes and transcription factors (TFs). A total of 177 cases from the GSE17536 dataset were analyzed via weighted gene co-expression network analysis to explore the modules related to CRC recurrence. Functional annotation of the key module genes was assessed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein and protein interaction network was then built to screen hub genes. Samples from the Cancer Genome Atlas (TCGA) were further used to validate the hub genes. Construction of a TFs-miRNAs–hub genes network was also conducted using StarBase and Cytoscape approaches. After identification and validation, a total of five genes (TIMP1, SPARCL1, MYL9, TPM2, and CNN1) were selected as hub genes. A regulatory network of TFs-miRNAs-targets with 29 TFs, 58 miRNAs, and five hub genes was instituted, including model GATA6-MIR106A-CNN1, SP4-MIR424-TPM2, SP4-MIR326-MYL9, ETS1-MIR22-TIMP1, and ETS1-MIR22-SPARCL1. In conclusion, the identification of these hub genes and the prediction of the Regulatory relationship of TFs-miRNAs-hub genes may provide a novel insight for understanding the underlying mechanism for CRC recurrence.