Comprehensive exploration of programmed cell death landscape in lung adenocarcinoma combining multi-omic analysis and experimental verification

The mortality and therapeutic failure in lung adenocarcinoma (LUAD) are mainly resulted from the wide metastasis and chemotherapy resistance. Up to now, accurate and stable predictive prognostic indicator for revealing the progress and novel therapeutic strategies of LUAD is infrequent, nonetheless. Diversified programmed cell death (PCD) has been widely confirmed that participated in the occurrence and development of various malignant tumors, respectively. In this research, we integrated fourteen types of PCD, bulk multi-omic data from TCGA-LUAD and other cohorts in gene expression omnibus (GEO) and clinical LUAD patients to develop our analysis. Consequently, pivotal fourteen PCD genes, especially CAMP, CDK5R1, CTSW, DAPK2, GAB2, GAPDH, GATA2, HGF, MAPT, NAPSA, NUPR1, PIK3CG, PLA2G3, and SLC7A11, were utilized to establish the prognostic signature, namely cell death index (CDI). The validation in several external cohorts indicated that CDI can be regarded as a potential risk factor of LUAD patients. Combined with other common clinical information, a nomogram with potential predictive ability was constructed. Besides, according to the CDI signature, the tumor microenvironment (TME) and sensitivity to some potential chemotherapeutic drugs were further and deeply explored. Notably, verification and functional experiments further demonstrated the remarkable correlation between CDI and unfold protein response. Given all the above, a novel CDI gene signature was indicated to predict the prognosis and exploit precision therapeutic strategies of LUAD patients.