Development and functional validation of a disulfidoptosis-related gene prognostic model for lung adenocarcinoma based on bioinformatics and experimental validation DOI Creative Commons
Tao Shen,

Zhuming Lu,

Sisi Yang

et al.

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 10, 2025

Background Disulfidoptosis is increasingly linked to cancer progression, yet its immunological impacts and prognostic value in lung adenocarcinoma (LUAD) remain poorly understood. This study aims delineate the predictive significance of disulfidoptosis-related genes (DRGs) LUAD, their potential as therapeutic targets, interaction with tumor microenvironment. Methods We analyzed expression profiles 23 DRGs survival data, performing consensus clustering identify molecular subtypes. Survival analysis gene set variation (GSVA) were used explore cluster differences. Key selected for Cox LASSO regression develop a model. Tensin4 (TNS4), key model, was further evaluated through immunohistochemistry (IHC) LUAD normal tissues knockdown experiments vitro . Results Two clusters identified, 225 differentially expressed genes. A six-gene signature developed, which classified patients into high- low-risk groups, showing significant The risk score independently predicted prognosis correlated immunotherapy responses. IHC showed elevated TNS4 levels tissues, while reduced both cell proliferation migration. Conclusion highlights role validated offering new avenues targeted therapies, potentially improving treatment outcomes.

Language: Английский

Development and functional validation of a disulfidoptosis-related gene prognostic model for lung adenocarcinoma based on bioinformatics and experimental validation DOI Creative Commons
Tao Shen,

Zhuming Lu,

Sisi Yang

et al.

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 10, 2025

Background Disulfidoptosis is increasingly linked to cancer progression, yet its immunological impacts and prognostic value in lung adenocarcinoma (LUAD) remain poorly understood. This study aims delineate the predictive significance of disulfidoptosis-related genes (DRGs) LUAD, their potential as therapeutic targets, interaction with tumor microenvironment. Methods We analyzed expression profiles 23 DRGs survival data, performing consensus clustering identify molecular subtypes. Survival analysis gene set variation (GSVA) were used explore cluster differences. Key selected for Cox LASSO regression develop a model. Tensin4 (TNS4), key model, was further evaluated through immunohistochemistry (IHC) LUAD normal tissues knockdown experiments vitro . Results Two clusters identified, 225 differentially expressed genes. A six-gene signature developed, which classified patients into high- low-risk groups, showing significant The risk score independently predicted prognosis correlated immunotherapy responses. IHC showed elevated TNS4 levels tissues, while reduced both cell proliferation migration. Conclusion highlights role validated offering new avenues targeted therapies, potentially improving treatment outcomes.

Language: Английский

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