Abstract
Lung cancer ranks as the primary contributor to cancer-related fatalities on a global scale, hallmarked by a poor prognosis. Programmed cell death (PCD) is critically involved in regulating the onset, progression, and treatment of lung adenocarcinoma (LUAD). Existing prognostic models concerning PCD focus solely on individual mechanisms and fail to account for the intricate interaction among multiple regulatory mechanisms. In this study, the LUAD samples were sorted into low immune cell invasion subtype (C1) and high immune cell invasion subtype (C2) by clustering analysis. A PCD prognostic signature model was developed by LASSO Cox regression analysis. Tumors in the high-risk group were categorized as "cold" and characterized by immunosuppression, which was linked to an unfavorable prognosis and sensitivity to drug therapy. However, the opposite was true for the low-risk group, which was associated with a favorable prognosis and sensitivity to immunotherapy. Single-cell analysis found that the PCD signature model could activate several immune cells, thereby affecting the tumor microenvironment (TME) of LUAD. Furthermore, ENO1, could be used as a target for LUAD prognosis and immunotherapy. This study aims to comprehensively explore the functional mechanisms of various PCD regulatory patterns in LUAD to provide accurate prognosis and personalized treatment plans.