PANoptosis subtypes predict prognosis and immune efficacy in gastric cancer

PANoptosis is a form of inflammatory programmed cell death that is regulated by the PANoptosome. This PANoptosis possesses key characteristics of pyroptosis, apoptosis, and necroptosis, yet cannot be fully explained by any of these cell death modes. The unique nature of this cell death mechanism has garnered significant interest. However, the specific role of PANoptosis-associated features in gastric cancer (GC) is still uncertain. Patients were categorized into different PAN subtypes based on the expression of genes related to the PANoptosome. We conducted a systematic analysis to investigate the variations in prognosis and tumor microenvironment (TME) among these subtypes. Furthermore, we developed a risk score, called PANoptosis-related risk score (PANS), which is constructed from genes associated with the PANoptosis. We comprehensively analyzed the correlation between PANS and GC prognosis, TME, immunotherapy efficacy and chemotherapeutic drug sensitivity. Additionally, we performed in vitro experiments to validate the impact of Keratin 7 (KRT7) on GC. We identified two PAN subtypes (PANcluster A and B). PANoptosome genes were highly expressed in PANcluster A. PANcluster A has the characteristics of favorable prognosis, abundant infiltration of anti-tumor lymphocytes, and sensitivity to immunotherapy, thus it was categorized as an immune-inflammatory type. Meanwhile, our constructed PANS can effectively predict the prognosis and immune efficacy of GC. Patients with low PANS have a good prognosis, and have the characteristics of high tumor mutation load (TMB), high microsatellite instability (MSI), low tumor purity and sensitivity to immunotherapy. In addition, PANS can also identify suitable populations for different chemotherapy drugs. Finally, we confirmed that KRT7 is highly expressed in GC. Knocking down the expression of KRT7 significantly weakens the proliferation and migration abilities of GC cells. The models based on PANoptosis signature help to identify the TME features of GC and can effectively predict the prognosis and immune efficacy of GC. Furthermore, the experimental verification results of KRT7 provide theoretical support for anti-tumor treatment.