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Identifying a novel ferroptosis-related prognostic score for predicting prognosis in chronic lymphocytic leukemia

Citation

Xu, Wei et al. (2022), Identifying a novel ferroptosis-related prognostic score for predicting prognosis in chronic lymphocytic leukemia, Dryad, Dataset, https://doi.org/10.5061/dryad.z612jm6fp

Abstract

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.

MethodsThe 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.

ResultsA 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 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<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.

Methods

All the total RNA samples in our center were obtained from the purified CD19+ 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 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).

Usage Notes

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Funding

National Natural Science Foundation of China, Award: 81770166

National Natural Science Foundation of China, Award: 81720108002

National Natural Science Foundation of China, Award: 81800192

National Natural Science Foundation of China, Award: 82100207

National Science and Technology Major Project, Award: 2018ZX09734007

Jiangsu Province’s Medical Elite Programme, Award: ZDRCA2016022

Project of National Key Clinical Specialty, Jiangsu Provincial Special Program of Medical Science, Award: BE2017751

Nature Science Foundation for Youths of Jiangsu Province, Award: BK20210962

Nature Science Foundation for Youths of Jiangsu Province, Award: BK20171079

Young Scholars Fostering Fund of the First Affiliated Hospital of Nanjing Medical University, Award: PY2021026