Integration of single-cell and bulk transcriptomics reveals the association of manganese metabolism-related genes with prognosis and immune infiltration in lung adenocarcinoma

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.