Abstract Background Lung adenocarcinoma (LUAD) is associated with a poor prognosis. Manganese metabolism plays a critical role in antitumor immunity. The prognostic significance of manganese metabolism–related genes (MRGs) in LUAD remains unclear. Methods Single‐cell RNA sequencing and TCGA transcriptomic data were integrated to identify expressed MRGs. Cell subpopulations were defined using AUCell scoring. A prognostic signature was constructed using univariate Cox regression, LASSO regression and multivariate Cox analysis. A nomogram incorporating the manganese metabolism–related risk score (MRS) and clinical variables was developed, and predictive performance was evaluated using receiver operating characteristic curves. Immune infiltration patterns and drug sensitivity were further analysed. Results A robust prognostic model based on nine genes, including KLRF1, demonstrated strong predictive performance. Patients in the high‐MRS group exhibited increased M1 macrophage infiltration and shorter overall survival, whereas the low‐MRS group was characterised by enrichment of resting dendritic cells. Drug sensitivity analyses suggested that JQ1 and Vorinostat may be more effective in low‐MRS patients, while Pevonedistat and LCL161 may be preferable for high‐MRS patients. In vitro experiments confirmed that high PTMA expression promoted malignant phenotypes in LUAD cells, and that combined JQ1 treatment and PTMA knockdown exerted synergistic antitumor effects. Conclusions We established and validated a prognostic signature based on nine MRGs. The synergistic antitumor effects of JQ1 and PTMA suppression were verified. This model provides a novel biomarker framework and therapeutic guidance for prognostic assessment and personalised treatment in LUAD.
Li et al. (2026) studied this question.