Integration of single-cell and bulk transcriptomics for deciphering prognostic value and immunotherapeutic features of floatptosis-mediated cell death in lung adenocarcinoma
Year: 2026
Type: article
Abstract: Background: Recent research has uncovered an unprecedented cell death pathway induced by outer membrane vesicles derived from Bergeyella cardium variant (BCV). This process promotes the pathological fusion of lysosome-related organelles via the SLC9A9 protein, leading to the formation of large vacuoles and ultimately inducing a terminal vacuolar cell death termed floatptosis. However, the role of floatptosis-related genes (FRGs) in lung adenocarcinoma (LUAD) remains largely unexplored. In this study, we constructed a LUAD prognostic model based on FRGs to predict patient prognosis and further explored the characteristics of lysosome fusion-associated terminal vacuolar cell death (floatptosis) at the single-cell level. Methods: , an FRG. A total of 50 genes were screened out via co-expression analysis. The AddModuleScore algorithm was utilized to calculate floatptosis scores across different cell clusters, which were then divided into high- and low-score subgroups. The differentially expressed genes (DEGs) derived from the two subgroups were enrolled in weighted gene co-expression network analysis (WGCNA) to screen key gene modules closely linked to LUAD. Single-cell and bulk transcriptome analyses combined with WGCNA identified 74 FRGs. Genes contained in these modules were further analyzed by differential expression analysis and univariate Cox regression. Based on FRGs, consensus clustering was applied to identify molecular subtypes, and least absolute shrinkage and selection operator (LASSO) regression was utilized to establish a prognostic signature. Combined with multiple immune infiltration algorithms, tumor mutational burden (TMB) analysis and cell communication analysis, we explored the correlation between floatptosis and the tumor microenvironment (TME), so as to provide novel therapeutic strategies for LUAD. Results: A total of 74 FRGs were identified through single-cell and bulk transcriptome analyses, among which 11 exhibited differential expression between tumor and normal tissues. Of these, 7 genes were found to be significantly correlated with overall survival (OS). Pseudotime trajectory analysis of macrophages revealed that risk-associated genes were predominantly upregulated at later stages, whereas protective genes tended to decrease over time. Five of these genes were ultimately selected to establish a prognostic signature based on FRGs. Patients stratified into the low-FRGs group showed a markedly better prognosis than those in the high-FRGs group. Intercellular communication analysis further demonstrated that macrophages with elevated FRGs expression displayed enhanced activity in the C-C motif chemokine ligand (CCL), activated leukocyte cell adhesion molecule (ALCAM), and colony-stimulating factor (CSF) signaling pathways. Conclusions: The prognostic model constructed based on FRGs allows for reliable survival prediction in LUAD patients and offers valuable insights into the immune microenvironment of LUAD. Notably, macrophages with high floatptosis scores can enhance the invasive and migratory capacities of tumor cells, making them promising novel therapeutic targets for LUAD.
Source: Translational Cancer Research
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W7224132978