Published online Jul 26, 2023. doi: 10.12998/wjcc.v11.i21.5023
Peer-review started: March 3, 2023
First decision: May 19, 2023
Revised: June 1, 2023
Accepted: June 26, 2023
Article in press: June 26, 2023
Published online: July 26, 2023
Processing time: 145 Days and 11.7 Hours
Gastric cancer (GC) is one of the most common cancers and has a poor prognosis. Treatment of GC has remained unchanged over the past few years. Genetic factors have been revealed to play an important role in susceptibility to GC. Significantly upregulated genes associated with poor prognosis were detected in GC using integrated bioinformatics methods.
In order to identify core prognostic biomarkers in GC, several databases were searched for GC-related genes as tumor markers, and cellular tests were performed to confirm the results.
Bioinformatics analysis of the molecular mechanism involved in GC revealed that three differentially expressed genes (DEGs) (BIRC5, TRIP13, or UBE2C) play critical roles in the progression of GC. Bioinformatics were used to identify hub genes and important pathways in GC, resulting in a biological relationship between the pathways and gene expression likely involved in GC.
In the theoretical analysis, microarray data information, data processing of DEGs, Gene Ontology and pathway enrichment analysis, PPI network and module analysis, and survival analysis were used. In the cellular experiments, RNA sequencing expression of core genes, patient samples and RT-PCR detection, cells and transfection, CCK-8 assay, apoptosis assay, colony formation assay, and statistical analysis were used.
Three hundred and forty-eight GC tissues and 141 normal tissues were analyzed; 251 DEGs were identified including 187 down-regulated genes and 64 up-regulated genes. We found that knockdown of BIRC5, TRIP13, or UBE2C significantly inhibited cell proliferation and induced cell apoptosis. Knockdown of BIRC5, TRIP13, or UBE2C increased cellular sensitivity to cisplatin.
The molecular mechanism of GC, via bioinformatics analysis, showed that three DEGs (BIRC5, TRIP13, or UBE2C) played key roles in the progression of GC. These findings will help to elucidate GC pathogenesis and identify novel biomarkers or drug targets for improved diagnostics and therapeutics for GC.
Bioinformatics was used to identify hub genes and important pathways in GC, resulting in a biological relationship between the pathways and gene expression likely involved in the progression of GC. Bioinformatics analysis revealed the relevant genes and cellular pathways involved in the genesis and development of GC.