Effects of plant-based medicinal food on postoperative recurrence and lung metastasis of gastric cancer regulated by Wnt/β-catenin-EMT signaling pathway and VEGF-C/D-VEGFR-3 cascade in a mouse model

The phytochemical and pharmacological profile of dandelion

Dandelion (Taraxacum genus), a perennial herb belonging to the Asteraceae family is widely distributed in hillside grasslands, roadsides, fields, and river beaches in middle and low-altitude areas. It has a long history of traditional Chinese medicine usage as a heat-clearing and detoxifying agent, often consumed as tea or vegetable. Multiple pharmacological studies have demonstrated the antiviral, antibacterial, anti-inflammatory, immune-regulating, antioxidant, anti-tumor, and other effects of the Taraxacum genus. Bioactive compounds associated with these effects include triterpenes and their saponins, phenolic acids, sterols and their glycosides, flavonoids, organic acids, volatile oils, and saccharides.

Machine learning methods predict recurrence of pN3b gastric cancer after radical resection

Background

The incidence of stage pN3b gastric cancer (GC) is low, and the clinical prognosis is poor, with a high rate of postoperative recurrence. Machine learning (ML) methods can predict the recurrence of GC after surgery. However, the prognostic significance for pN3b remains unclear. Therefore, we aimed to predict the recurrence of pN3b through ML models.

Methods

This retrospective study included 336 patients with pN3b GC who underwent radical surgery. A 3-fold cross-validation was used to partition the participants into training and test cohorts. Linear combinations of new variable features were constructed using principal component analysis (PCA). Various ML algorithms, including random forest, support vector machine (SVM), logistic regression, multilayer perceptron (MLP), extreme gradient boosting (XGBoost), and Gaussian naive Bayes (GNB), were utilized to establish a recurrence prediction model. Model performance was evaluated using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). Python was used for the analysis of ML algorithms.

Results

Nine principal components with a cumulative variance interpretation rate of 90.71% were identified. The output results of the test set showed that random forests had the highest AUC (0.927) for predicting overall recurrence with an accuracy rate of 80.5%. Random forests had the highest AUC (0.940) for predicting regional recurrence with an accuracy of 89.7%. For predicting distant recurrence, random forests had the highest AUC (0.896) with an accuracy of 84.3%. For peritoneal recurrence, random forests had the highest AUC (0.923) with an accuracy of 83.3%.

Conclusions

ML can personalize the prediction of postoperative recurrence in patients with GC with stage pN3b.

Diagnostic value of long noncoding RNA SNHG15 in gastric cancer: in vitro and in silico studies

LncRNA SNHG15 has been recognized as the main factor in the progression of various cancer types. However, the underlying mechanisms are not well clarified. This research aimed to explore the diagnostic potential of SNHG15 in gastric cancer (GC) patients and also the effects of SNHG15-miRNA-mRNA network in GC pathobiology. The expression level of SNHG15 in GC tissues and adjacent normal tissues (ANTs) was evaluated by qRT-PCR and also considered in relation to clinicopathologic factors. The ROC curve was explored to consider the specificity and sensitivity of SNHG15. Gene ontology functional annotation and KEGG pathway analysis were performed in order to predict the effects of SNHG15-miRNA-mRNA network in GC pathobiology. SNHG15 was overexpressed in GC tissues compared to ANTs (fold change= 3.87 and P-value = 0.0022). The SNHG15 expression level was not significantly associated with clinicopathologic factors. ROC curve indicated the specificity of 63.51 and sensitivity of 79.73 and the AUC of 0.744 (P-value < 0.0001). Further gene network analysis revealed that SNHG15 interacts with has-miR-613, has-miR-542-3p, and has-miR-1236-3p, and may be involved in the GC pathobiology by affecting the EGFR tyrosine kinase inhibitor resistance, HIF-1 signaling pathway, and VEGF signaling pathway. It can be concluded that SNHG15 may be a diagnostic factor in GC and may contribute in a variety of cancer-related signaling pathways.

Knockdown of SETD5 inhibited glycolysis and tumor growth in gastric cancer cells by down-regulating Akt signaling pathway

Gastric cancer (GC) is the 5th most common cancer and the 3rd leading cause of cancer-related death worldwide. It is of great significance to study the underlying molecular mechanism of GC, and targeting glycolysis is a good strategy to treat GC. SET domain containing 5 (SETD5) contains a catalytic methyltransferase SET domain, which is known as a lysine methyltransferase that affects the progression of multiple cancers. However, its possible role in GC was still unclear. Here, we revealed that SETD5 was highly expressed in GC and was associated with a poor prognosis. Further through the in vitro experiments, we revealed that the downregulation of SETD5 inhibited the proliferation and migration of GC cells. Knockdown of SETD5 inhibited glucose consumption and glycolysis. Further studies have shown that SETD5 knockdown restrained the Akt signaling pathway. Therefore, we thought that SETD5 could act as a GC target.

Lymphangiogenesis in gastric cancer: function and mechanism

Increased lymphangiogenesis and lymph node (LN) metastasis are thought to be important steps in cancer metastasis, and are associated with patient's poor prognosis. There is increasing evidence that the lymphatic system may play a crucial role in regulating tumor immune response and limiting tumor metastasis, since tumor lymphangiogenesis is more prominent in tumor metastasis and diffusion. Lymphangiogenesis takes place in embryonic development, wound healing, and a variety of pathological conditions, including tumors. Tumor cells and tumor microenvironment cells generate growth factors (such as lymphangiogenesis factor VEGF-C/D), which can promote lymphangiogenesis, thereby inducing the metastasis and diffusion of tumor cells. Nevertheless, the current research on lymphangiogenesis in gastric cancer is relatively scattered and lacks a comprehensive understanding. Therefore, in this review, we aim to provide a detailed perspective on molecules and signal transduction pathways that regulate gastric cancer lymphogenesis, which may provide new insights for the diagnosis and treatment of cancer.