ArticleDiscover oncology2025
The immune infiltration and prognostic significance of complement and coagulation cascade-related genes in lung adenocarcinoma.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer. Previous studies have highlighted the critical roles of complement and coagulation cascades in tumor development, maintenance, and therapeutic response. However, the overall impact of complement and coagulation cascade-related (CCCR) genes on LUAD progression and their role in the tumor microenvironment (TME) remain insufficiently explored. Therefore, we screened CCCR genes with important roles in LUAD using RNA sequencing data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Subsequently, a prognostic model, based on 8 hub genes (IGFBP1, TUBB, PLEK2, CNTNAP2, CPS1, EREG, CENPE, HBEGF) identified using the Lasso-Cox algorithm, was developed to stratify LUAD patients into high- and low-risk groups. This model demonstrated strong predictive capability and calibration, with an AUC of 0.816 in the external validation cohort. Multiomics clustering revealed that 2 cancer subtypes (CSs) are associated with prognosis, with CS2 demonstrating the most favorable prognostic outcome and validating the validity of the prognostic model. Additionally, we analyzed the immune infiltration, tumor mutation burden (TMB) and immunophenoscore (IPS) of the riskscore in the models. Through this analysis, we have identified for the first time CCCR genes are highly associated with clinical characteristics, immune cell infiltration patterns, and immune therapeutic responses of LUAD. This prognostic model constructed based on CCCR genes represents a valid tool for the prognosis of LUAD patients. Our findings provide valuable insights into the prognostic and immunological relevance of CCCR genes in LUAD, offering a robust foundation for personalized treatment strategies and future research.
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