Establishment and validation of prognostic model of lung adenocarcinoma based on apoptosis-related genes

Abstract Objective: Apoptosis is an autonomous cell death process controlled by genes that can keep the internal environment of cells relatively stable. Lately, many studies have shown that apoptosis plays an important role in the construction of tumor microenvironment, mainly through the release of a series of regulatory factors to control cell growth. Therefore, it is very valuable to find and explore the possible role of apoptosis in the pathogenesis of lung cancer and its impact on the prognosis of patients. Materials and Methods: We selected 10 apoptosis-related genes and used different statistical methods to construct a model to predict the survival and prognosis of patients with lung adenocarcinoma. Univariate and multivariate Cox analysis were used to evaluate the predictive power and value of prognostic models, as well as receiver operating characteristic (ROC) curve analysis. Results: We defined two subgroups (cluster1 and cluster2). Compared with cluster1, cluster2 was named "apoptosis inhibition subgroup". The survival prognosis of cluster1 was significantly better than that of cluster2, and the infiltration of immune cells in cluster2 suggested that its immune system was inhibited. Then, we established a new prognostic model of apoptosis-related genes to identify high-risk patients with lung adenocarcinoma. Two types of Cox proportional hazards analysis and ROC curve showed that our model can be used as a new independent factor for the prognosis of lung adenocarcinoma patients, and had strong predictive ability. Conclusion: Apoptosis is involved in the formation and development of lung adenocarcinoma and plays an important role. Our survival model can better predict the survival and prognosis of lung adenocarcinoma, and our study may be helpful for further research on new therapeutic targets and precise individualized treatment in the future.