Gastric cancer is one of the most common malignant tumors in the digestive system. Surgery is currently considered to be the only radical treatment. As surgical techniques improve and progress is made in traditional radiotherapy, chemotherapy, and the implementation of neoadjuvant therapy, the 5-year survival rate of early gastric cancer can reach >95%. However, the low rate of early diagnosis means that most patients have advanced-stage disease at diagnosis and so the best surgical window is missed. Therefore, the main treatment for advanced gastric cancer is the combination of neoadjuvant chemoradiotherapy, molecular-targeted therapy, and immunotherapy. In this article, we summarize several common methods used to treat advanced gastric cancer and discuss the progress made in the treatment of gastric cancer in detail. Only clinical practice and clinical research will allow us to prolong the survival time of patients and allow the patients to truly benefit by paying attention to the individual patient characteristics, drug choice, and developing a reasonable and comprehensive treatment plan.

Water and its distribution and transport dynamics in green plant leaves are vital to the growth of plants. Owing to the high sensitivity of terahertz (THz) wave to water, THz

In the present research, a tumor-targeted gene carrier, PPP, was constructed through the modification of phenylboronic acid onto the surface of a polyamidoamine dendrimer, and then miR-34a delivery was employed as a model to evaluate its anti-tumor efficacy.

The present findings demonstrate that elevated circulating miR-658 is associated with MGC by activating PAX3-MET pathway.

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Background: siRNA-mediated polo-like kinase 1 (PLK1) silencing has been proposed as a promising therapeutic method for multiple cancers. However, the clinic application of this method is still hindered by the low specific delivery of siPLK1 to desired tumor lesions. Herein, folate (FA)-modified and leucine-bearing polyethylenimine was successfully synthesized and showed excellent targeted silencing to folate receptor overexpressed cells. Materials and Methods: The condensation of siPLK1 by FAN -Ac-L-Leu-PEI (NPF) was detected by the gel retardation assay. The targeted and silencing efficiency was evaluated by flow cytometry and confocal laser scanning microscope. The PLK1 expressions at gene or protein levels were detected by quantitative real-time PCR and Western blotting assay. Further impacts of the PLK1 silencing on cell viability, cell cycle, migration, and invasion were studied by MTT, colony formation, wound healing and transwell assays. Results: The NPF and siPLK1 could efficiently assemble to stable nanoparticles at a weight ratio of 3.0 and showed excellent condensation and protection effect. Owing to the FA-mediated targeted delivery, the uptake and silencing efficiency of NPF/siPLK1 to SGC-7901 cells was higher than that without FA modification. Moreover, NPF-mediated PLK1 silencing showed significant antitumor activity in vitro. The anti-proliferation effect of PLK1 silencing was induced via the mitochondrial-dependent apoptosis pathway with the cell cycle arrest of 45% at G2 phase and the apoptotic ratio of 28.3%. Conclusion: FAN -Ac-L-Leu-PEI (NPF) could generate targeted delivery siPLK1 to FA receptor overexpressed cells and dramatically downregulate the expression of PLK1 expression.

Background Bioinformatics was used to analyze the skin cutaneous melanoma (SKCM) gene expression profile to provide a theoretical basis for further studying the mechanism underlying metastatic SKCM and the clinical prognosis. Methods We downloaded the gene expression profiles of 358 metastatic and 102 primary (nonmetastatic) CM samples from The Cancer Genome Atlas (TCGA) database as a training dataset and the GSE65904 dataset from the National Center for Biotechnology Information database as a validation dataset. Differentially expressed genes (DEGs) were screened using the limma package of R3.4.1, and prognosis-related feature DEGs were screened using Logit regression (LR) and survival analyses. We also used the STRING online database, Cytoscape software, and Database for Annotation, Visualization and Integrated Discovery software for protein–protein interaction network, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses based on the screened DEGs. Results Of the 876 DEGs selected, 11 (ZNF750, NLRP6, TGM3, KRTDAP, CAMSAP3, KRT6C, CALML5, SPRR2E, CD3G, RTP5, and FAM83C) were screened using LR analysis. The survival prognosis of nonmetastatic group was better compared to the metastatic group between the TCGA training and validation datasets. The 11 DEGs were involved in 9 KEGG signaling pathways, and of these 11 DEGs, CALML5 was a feature DEG involved in the melanogenesis pathway, 12 targets of which were collected. Conclusion The feature DEGs screened, such as CALML5, are related to the prognosis of metastatic CM according to LR. Our results provide new ideas for exploring the molecular mechanism underlying CM metastasis and finding new diagnostic prognostic markers.

Background Colorectal cancer (CRC) is a multifactorial tumor and a leading cause of cancer-specific deaths worldwide. Recent research has shown that the alteration of intestinal flora contributes to the development of CRC. However, the molecular mechanism by which intestinal flora influences the pathogenesis of CRC remains unclear. This study aims to explore the key genes underlying the effect of intestinal flora on CRC and therapeutic drugs for CRC. Methods Intestinal flora-related genes were determined using text mining. Based on The Cancer Genome Atlas database, differentially expressed genes (DEGs) between CRC and normal samples were identified with the limma package of the R software. Then, the intersection of the two gene sets was selected for enrichment analyses using the tool Database for Annotation, Visualization and Integrated Discovery. Protein interaction network analysis was performed for identifying the key genes using STRING and Cytoscape. The correlation of the key genes with overall survival of CRC patients was analyzed. Finally, the key genes were queried against the Drug-Gene Interaction database to find drug candidates for treating CRC. Results 518 genes associated with intestinal flora were determined by text mining. Based on The Cancer Genome Atlas database, we identified 48 DEGs associated with intestinal flora, including 25 up-regulated and 23 down-regulated DEGs in CRC. The enrichment analyses indicated that the selected genes were mainly involved in cell–cell signaling, immune response, cytokine-cytokine receptor interaction, and JAK-STAT signaling pathway. The protein–protein interaction network was constructed with 13 nodes and 35 edges. Moreover, 8 genes in the significant cluster were considered as the key genes and chemokine (C-X-C motif) ligand 8 (CXCL8) correlated positively with the overall survival of CRC patients. Finally, a total of 24 drugs were predicted as possible drugs for CRC treatment using the Drug-Gene Interaction database. Conclusions These findings of this study may provide new insights into CRC pathogenesis and treatments. The prediction of drug-gene interaction is of great practical significance for exploring new drugs or novel targets for existing drugs.