Genetic variants in CHEK1 gene are associated with the prognosis of thoracic esophageal squamous cell carcinoma patients treated with radical resection

Network pharmacology and molecular docking reveal the mechanisms of curcumin activity against esophageal squamous cell carcinoma

Background: Curcumin (CUR), an effective traditional Chinese medicinal extract, displays good anti-cancer activity against various cancers. Nevertheless, the impacts and fundamental mechanisms of CUR to treat esophageal squamous cell carcinoma (ESCC) yet to be comprehensively clarified. This study examined the suppressive impacts of CUR on ESCC. Methods: For a comprehensive understanding of the effect of CUR in ESCC. The CUR targets and ESCC-related genes were identified respectively, and the intersection targets between CUR and ESCC were acquired. Then, we examined the intersection targets and discovered genes that were expressed differently in ESCC. Using DAVID, enrichment analyses were conducted on the targets of CUR-ESCC. The STRING database and Cytoscape v.3.9.1 were utilized to build networks for protein-protein interaction (PPI) and drug-target-pathway. Furthermore, the interactions between CUR and its core targets were confirmed by molecular docking studies. To confirm the effects of CUR on ESCC cells, in vitro experiments were finally conducted. Results: Overall, 47 potential CUR targets for ESCC treatment were identified. The KEGG pathway enrichment analysis identified 61 signaling pathways, primarily associated with the FoxO signaling, the cell cycle, cellular senescence, the IL-17 signaling pathway which play important roles in ESCC progression. In the PPI network and the docking results identified CHEK1 and CDK6 as the core targets that positively associated with ESCC survival. CUR arrested ESCC cells at the G2/M and S phases, as shown by flow cytometry. Colony formation and CCK8 assays showed that CUR can inhibit the proliferative ability of ESCC cells. The Transwell invasion results validated that CUR can significantly inhibit the invasion rates of ESCC cells. Conclusion: Collectively, these findings indicate that CUR exhibits pharmacological effects on multiple targets and pathways in ESCC.

Comprehensive Analysis of Candidate Diagnostic and Prognostic Biomarkers Associated with Lung Adenocarcinoma

Background

We aimed to screen and identify central genetic and molecular targets involved in advancement of lung adenocarcinoma (LUAD) and to perform an integrated analysis and clinical validation.

Material/Methods

The GEO2R technique was utilized to assess differentially expressed genes (DEGs) among the gene sets GSE75037, GSE85716, and GSE118370. Subsequently, gene Ontology (GO) analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) analytical methods were executed to determine related biofunctions and signaling pathways, which were annotated with tools from the Database for Annotation, Visualization and Integrated Discovery (DAVID) resource. Then, a protein-protein interaction (PPI) network complex consisting of all detected DEGs was built with the STRING web interface. Cytohubba and MCODE plug-ins for Cytoscape software and Gene Expression Profiling Interactive Analysis (GEPIA) were employed to identify the hub genes. Finally, the mRNA expression of the identified hub genes was quantitatively validated by The Cancer Genome Atlas (TCGA) database analysis and real-time quantitative polymerase chain reaction (RT-qPCR).

Results

We screened 146 upregulated DEGs and 431 downregulated DEGs with the criteria of |logFC| >1 and P<0.05, and the GO analysis indicated that DEGs were implicated in mitotic nuclear division (biological process, BP), the nucleus (cellular component, CC), and protein binding (molecular function, MF) and were associated with multiple KEGG pathways, such as the p53 signaling pathway in cancer. Then, the top 8 genes that predicted significantly different outcomes in LUAD patients were filtered from the DEGs and selected as hub genes. The TCGA database analysis and RT-qPCR results demonstrated that these genes were differentially expressed with the same trends in LUAD tissues compared with normal tissues.

Conclusions

Overall, we propose that 8 genes (PECAM1, CDK1, MKI67, SPP1, TOP2A, CHEK1, CCNB1, and RRM2) might be novel hub genes strongly associated with the progression and prognosis of LUAD.