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Catalase (CAT) plays a crucial role in converting hydrogen peroxide (H₂O₂) into water and oxygen, which can help alleviate oxidative stress in body. However, whether CAT is associated with the prognosis and immunotherapy response in patients with non-small cell lung cancer (NSCLC) requires further investigation. This study collected data from over 3,170 NSCLC cases across multiple countries. Thirteen machine learning algorithms were employed to identify the most effective diagnostic model, with performance evaluated based on area under the curve (AUC) values. The prognostic significance of CAT expression was assessed in relation to survival, tumor recurrence, and tumor differentiation in NSCLC patients. Additionally, the effectiveness of immunotherapy in relation to CAT expression was evaluated using an immunotherapy dataset. The GDSC database was utilized to examine the correlation between CAT expression and sensitivity to potential therapeutic agents. A multi-omics approach was then applied to analyze the expression and distribution of CAT in NSCLC. In vitro experiments were conducted to validate CAT expression in lung cancer cell lines, and its impact on cell proliferation and migration was assessed using CCK-8 assays, scratch assays, and colony formation assays following transfection with a CAT overexpression construct. The regulatory role of CAT in oxidative stress was further evaluated by adding hydrogen peroxide. Finally, the xenograft tumor mouse model was established to observe the effect of CAT on macrophage phenotype. We first observed that CAT exhibited the highest AUC value in the machine learning model. Subsequent analyses revealed that NSCLC patients with high CAT expression had prolonged survival, reduced tumor recurrence, and reduced tumor poor differentiation, as confirmed by data from multiple global national databases. Moreover, these patients showed greater responsiveness to immunotherapy and experienced prolonged progression-free survival (PFS). The high CAT expression cohort also exhibited increased sensitivity to Cisplatin, Savolitinib, and Docetaxel. Additionally, we also verified the low expression of CAT in tumor tissues by RT-qPCR and immunohistochemistry. Furthermore, overexpression of CAT inhibited lung cancer cell proliferation and migration, while significantly enhancing its ability to regulate hydrogen peroxide levels. Notably, in the xenograft tumor mouse model, we observed that CAT may suppress tumor growth by alleviating tissue hypoxia and facilitating the polarization of tumor-associated macrophage from the M2 phenotype to M1. This study demonstrated the potential of CAT as a prognostic biomarker for NSCLC. Targeting CAT might provide an effective strategy for improving patient survival and the efficacy of immunotherapy.
Tian et al. (Fri,) studied this question.