DOI: 10.5061/dryad.z612jm6fp
title: Identifying a novel ferroptosis-related prognostic score for predicting prognosis in chronic lymphocytic leukemia

description: 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 some patients who remain drug resistance or
 disease refractory. Ferroptosis is a type of lipid peroxidation-induced
 cell death and has been suggested with a 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&lt;0.0001) and treatment-free
 survival (TFS) (P&lt;0.0001). ROC curves evaluated the prognostic
 prediction ability of the 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&lt;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.
description: All the total RNA samples in
 our center were obtained from the purified CD19<sup>+</sup> B
 cells of CLL patients using a CD19+ B-cell selection kit (Miltenyi Biotech,
 Gladbach, Germany). The quality of the extracted RNA was assessed
 using an RNeasy Micro Kit (QIAGEN, Hilden,
 Germany). The prepared
 sequencing libraries were
 sequenced by a HiSeq X Ten high-throughput sequencing system.
 The sequences were mapped to hg38 (humangenome 38) and aligned
 using Bowtie and BLAT (the BLAST-like alignment
 tool).
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