Novel Necroptosis-Related Gene Signature for Predicting Early Diagnosis and Prognosis and Immunotherapy of Gastric Cancer

Abstract

Simple SummaryNecroptosis plays an important role in the occurrence and development of many cancers. MLKL is an important component of necroptosis, and has been proved to be closely related to the prognosis of gastric cancer (GC). We determined an early diagnosis (FAP, CCT6A) and prognosis risk score (ZFP36, TP53I3, FAP, CCT6A) model of necroptosis-related genes (NRGs) in GC. Two models, respectively, can effectively predict the occurrence of GC and the prognosis of GC patients. The association between the prognostic risk score and the response to immunotherapy and immune checkpoint inhibitors (ICIs) was also analyzed. FAP was also identified as the core gene in the two models, and the relationship between its expression in GC and ICIs was analyzed. This discovery is the first time that NRGs were combined with immunotherapy for GC and provides a new target for immunotherapy for GC and a more accurate treatment scheme for GC patients.Necroptosis is a kind of programmed necrosis, which is different from apoptosis and pyroptosis. Its molecular mechanism has been described in inflammatory diseases. Gastric cancer (GC) is one of the most common malignancies worldwide with the third highest mortality. However, the role of necroptosis in the occurrence and progression of GC remains largely unexplored. Therefore, we investigated necroptosis-related genes (NRGs) by analyzing public transcriptomic data from GC samples. Our results indicate that 83 of 740 NRGs are dysregulated in GC tissues. Next, we identified necroptosis-associated early diagnosis and prognostic gene signatures for GC using machine learning. 2-NRGs (CCT6A and FAP) and 4-NRGs (ZFP36, TP53I3, FAP, and CCT6A), respectively, can effectively assess the risk of early GC (AUC = 0.943) and the prognosis of GC patients (AUC = 0.866). Through in-depth analysis, we were pleasantly surprised to find that there was a significant correlation between the 4-NRGs and GC immunotherapy effect and immune checkpoint inhibitors (ICIs), which could be used for the evaluation of immunosuppressants. Finally, we identified the core gene FAP, and established the relationship between FAP and ICIs in GC. These findings could provide a new target for immunotherapy for GC and a more effective treatment scheme for GC patients.