Identifying a novel ferroptosis-related prognostic score for predicting prognosis in chronic lymphocytic leukemia - Pan, Bihui; Li, Yue; Xu, Zhangdi; Miao, Yi; Yin, Hua; Kong, Yilin; Zhang, Xinyu; Liang, Jinhua; Xia, Yi; Wang, Li; Li, Jianyong; Wu, Jiazhu; et al. (Frontiers in Immunology, 2022)
Background: Chronic lymphocytic leukemia (CLL) is the most common leukemia in the western world. Although the treatment landscape for CLL is rapidly evolving, there are still part of the patients remain drug resistance or disease refractory. Ferroptosis is a type of lipid peroxidation-induced cell death, and has been suggested with the prognostic value in several cancers. Our research aims to build a prognostic model to improve risk stratification in CLL patients and facilitate more accurate assessment for clinical management. Methods: The differentially expressed ferroptosis-related genes (FRGs) in CLL were filtered through univariate Cox regression analysis based on public databases. Least Absolute Shrinkage and Selection Operator (LASSO) Cox algorithms were performed to construct a prognostic risk model. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were performed to estimate the immune infiltration score and immune-related pathways. A total of thirty-six CLL patients in our center were enrolled in this study as a validation cohort. Moreover, a nomogram model was established to predict the prognosis. Results: A total of differentially expressed 15 FRGs with prognostic significance were screened out. After minimizing the potential risk of overfitting, we constructed a novel ferroptosis-related prognostic score (FPS) model with nine FRGs (AKR1C3, BECN1, CAV1, CDKN2A, CXCL2, JDP2, SIRT1, SLC1A5 and SP1), and stratified patients into low risk and high risk groups. Kaplan–Meier analysis showed that patients with high FPS had worse overall survival (OS) (P<0.0001) and treatment free survival (TFS) (P<0.0001). ROC curves evaluated the prognostic prediction ability of FPS model. Additionally, the immune cell types and immune-related pathways were correlated with the risk scores in CLL patients. In the validation cohort, the results confirmed that the high-risk group was related to worse OS (P<0.0001), progress-free survival (PFS) (P=0.0140) and TFS (P=0.0072). In the multivariate analysis, only FPS (P=0.011) and CLL-IPI (P=0.010) were independent risk indicators for OS. Furthermore, we established a nomogram including FPS and CLL-IPI which could strongly and reliably predict individual prognosis. Conclusion: A novel FPS model could be used in CLL for prognostic prediction. The model index may also facilitate the development of new clinical ferroptosis-targeted therapies in patients with CLL.