Molecular subtypes and prognostic signature rooted in disulfidptosis highlight tumor microenvironment in lung...

A highly aggressive and lethal malignancy, characterized by its heterogeneity, lung adenocarcinoma (LUAD) presents significant challenges in prognosis and treatment. Disulfidptosis, a newly identified form of regulated cell death, offers novel insights into cancer progression, yet its role in LUAD remains poorly understood.

We identified disulfidptosis-related genes (DRGs) from prior studies and analyzed their interactions and functional enrichment. Molecular subtypes were identified through consensus clustering based on DRG expression, and a prognostic DRG signature was developed using multivariate Cox regression analysis. A nomogram integrating clinical variables was developed to predict survival. Comprehensive analyses, including single-cell RNA sequencing, immune infiltration, and drug sensitivity, were validated using clinical specimens, LUAD cell lines, Western blotting (WB) and immunohistochemistry (IHC).

A total of 16 DRGs were identified, classifying LUAD patients into three distinct subtypes with differential survival and immune profiles. A 4-gene signature (GYS1, NDUFA11, NDUFB10, SLC7A11) was used to build a risk score model, demonstrating robust prognostic accuracy. A nomogram combining this signature with clinical features reliably predicted 1-, 3-, and 5-year survival. The signature correlated with immune cell infiltration, with single-cell analysis revealing DRG enrichment in myeloid cells. Notably, SLC7A11 and GYS1 were positively associated with chemotherapeutic drug sensitivity. Validation through reverse transcription quantitative polymerase chain reaction (RT-qPCR), WB and IHC confirmed upregulated DRG expression in LUAD tissues and cell lines.

This research highlights the essential role of DRGs in modulating the tumor microenvironment, influencing therapeutic response, and determining the prognosis of LUAD. The risk model and nomogram, derived from DRG expression, offer robust tools for survival prediction and personalized treatment stratification, facilitating the development of disulfidptosis-targeted therapeutic strategies.