Necroptosis is a type of programmed necrosis that is different from apoptosis and necrosis. Lung cancer has the highest incidence and mortality worldwide, and lung adenocarcinoma is the most common subtype of lung cancer. However, the role of necroptosis in the occurrence and development of LUAD remains largely unexplored. In this paper, four NRGs and nine NRGs determined by big data analysis were used to effectively predict the risk of early LUAD (AUC = 0.994) and evaluate the prognostic effect on LUAD patients (AUC = 0.826). Meanwhile, ESTIMATE, single-sample gene set enrichment analysis (ssGSEA), genomic variation analysis (GSVA), gene set enrichment analysis (GSEA), and immune checkpoint analysis were used to explore the enrichment characteristics and immune research related to the prognostic model. In deep data mining, we were surprised to find that prognostic models also regulate the immune microenvironment, cell cycle, and DNA damage repair mechanisms. Thus, we demonstrated a significant correlation between model evaluation results, ICI treatment, and chemotherapeutic drug sensitivity. The low-risk population has a stronger tumor immune response, and the potential for ICI treatment is greater. People at high risk respond less to immunotherapy but respond well to chemotherapy drugs. In addition, PANX1, a core gene with important value in immune regulation, prognosis assessment, and early diagnosis, has been identified for the first time, which provides a new target for the immunotherapy of LUAD as well as a new theoretical basis for the basic research, clinical diagnosis, and individualized treatment of LUAD.