Abstract

Gastric cancer (GC) is the most commonly diagnosed digestive system malignancy with a dismal survival outcome. The prognostic value of ubiquitination-related genes (URGs) in GC has yet to be discovered. Two GC cohort datasets were obtained from the Cancer Genome Atlas Program (TCGA) and Gene Expression Omnibus (GEO) databases. Stepwise Cox analysis was employed to generate a signature. Then, we applied unsupervised clustering analysis to determine subclusters in GC based on URGs. Single-cell analysis was carried out to depict the cellular location of model genes. The CIBERSORT method was performed to estimate the immune landscape. Finally, preliminary wet lab work was utilized to disclose the potential effect of OTULIN. Our proposed signature was set up based on five URGs (OTULIN, UBE2C, USP1, USP2, and MAPT) which could serve as a risk classifier to categorize GC cases. In addition, it was demonstrated that the ubiquitination-associated model could depict the immune landscape and forecast immunotherapy response for GC patients. Furthermore, in vitro experiments determined the function and effect of OUTLIN in GC. We observed that the knockdown of OUTLIN could suppress cell viability and metastatic ability of GC cell lines. Our data lays the groundwork for a comprehensive investigation into the role of URGs in GC and determined OTULIN as a candidate GC biomarker.

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