Computational Methods for the Analysis of Genomic Data and Biological Processes

Identification of Potential Active Ingredients and Mechanisms of Cattail Pollen for Treating Infertile Patients With Endometriosis Based on Bioinformatics and Molecular Docking

Introduction: Cattail Pollen is a commonly used Chinese medicine for promoting blood circulation and removing blood stasis in infertility patients with endometriosis, but its ingredients and mechanism of action are still unclear. The aims of this study were to explore the potential active ingredients, targets and mechanisms of Cattail Pollen in treating infertility patients with endometriosis based on bioinformatics and molecular docking. Methods: The GSE120103 dataset was downloaded from the Gene Expression Omnibus (GEO) database to screen out differentially expressed genes. Cytoscape software was constructed to construct the protein–protein interaction network and screen for hub proteins, and molecular docking was performed to identify the binding activity of Cattail Pollen active ingredients and infertility genes. Then, DAVID software was used to perform gene ontology (GO) functional analysis and KEGG pathway enrichment analysis on differentially expressed genes. Results: There were 1320 differentially expressed genes in patients with endometriosis. ADCY5, RLN3, and ADCY6 proteins encoded by genes that were upregulated in infertile patients with endometriosis. Eight active ingredients of Cattail Pollen were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform: naringenin ((2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one), arachidonic acid, isorhamnetin, β-sitosterol, kaempferol, Testosterone palmitate, kaempferol-3-O-α-L-rhamnosyl(1→2)-β-D-glucoside and quercetin. Molecular docking identified that the binding activity of arachidonic acid with ADCY5, RLN3, and ADCY6; and testosterone palmitate with ADCY5 and ADCY6 was strong. GO analysis suggested that differentially expressed genes were involved in multiple biological processes, cellular components, and molecular functions. KEGG enrichment analysis found that differentially expressed genes were enriched in neuroactive ligand–receptor interaction, cytokine–cytokine receptor interaction, chemokine signaling pathway, and Jak-STAT signaling pathway. Conclusions: This study discovered the differentially expressed genes of naturally conceived and infertile patients with endometriosis, and clarified the effective ingredients, targets, and potential signaling pathways of Cattail Pollen in the treatment of infertility patients with endometriosis.

Establishment and Analysis of an Individualized Immune-Related Gene Signature for the Prognosis of Gastric Cancer

A growing number of studies have shown that immunity plays an important clinical role in the process of gastric cancer (GC). The purpose of this study was to explore the function of differentially expressed immune-related genes (DEIRGs) of GC, and construct a gene signature to predict the overall survival (OS) of patients. Gene expression profiles and clinical data of GC patients were downloaded from TCGA and GEO databases. Combined with immune-related genes (IRGs) downloaded from the ImmPort database, 357 DEIRGs in GC tissues and adjacent tissues were identified. Based on the analysis of Lasso and Cox in the training set, a prognostic risk scoring model consisting of 9 (RBP7, DES, CCR1, PNOC, SPP1, VIP, TNFRSF12A, TUBB3, PRKCG) DEIRGs was obtained. Functional analysis revealed that model genes may participate in the formation and development of tumor cells by affecting the function of cell gap junction intercellular communication (GJJC). According to the model score, the samples were divided into high-risk and low-risk groups. In multivariate Cox regression analysis, the risk score was an independent prognostic factor (HR = 1.674, 95% CI = 1.470–1.907, P < 0.001). Survival analysis showed that the OS of high-risk GC patients was significantly lower than that of low-risk GC patients (P < 0.001). The area under the receiver operating characteristic curve (ROC) of the model was greater than other clinical indicators when verified in various data sets, confirming that the prediction model has a reliable accuracy. In conclusion, this study has explored the biological functions of DEIRGs in GC and discovered novel gene targets for the treatment of GC. The constructed prognostic gene signature is helpful for clinicians to determine the prognosis of GC patients and formulate personalized treatment plans.