Identification of immune subtypes of Ph-neg B-ALL with ferroptosis related genes and the potential implementation of Sorafenib

Abstract

Abstract Background The clinical outcome of Philadelphia chromosome-negative B cell acute lymphoblastic leukemia (Ph-neg B-ALL) varies considerably from one person to another after clinical treatment due to lack of targeted therapies and leukemia’s heterogeneity. Ferroptosis is a recently discovered programmed cell death strongly correlated with cancers. Nevertheless, few related studies have reported its significance in acute lymphoblastic leukemia. Methods Herein, we collected clinical data of 80 Ph-neg B-ALL patients diagnosed in our center and performed RNA-seq with their initial bone marrow fluid samples. Throughout unsupervised machine learning K-means clustering with 24 ferroptosis related genes (FRGs), the clustered patients were parted into three variant risk groups and were performed with bioinformatics analysis. Results As a result, we discovered significant heterogeneity of both immune microenvironment and genomic variance. Furthermore, the immune check point inhibitors response and potential implementation of Sorafenib in Ph-neg B-ALL was also analyzed in our cohort. Lastly, one prognostic model based on 8 FRGs was developed to evaluate the risk of Ph-neg B-ALL patients. Conclusion Jointly, our study proved the crucial role of ferroptosis in Ph-neg B-ALL and Sorafenib is likely to improve the survival of high-risk Ph-neg B-ALL patients.

Keywords

• Ferroptosis
• Acute lymphoblastic leukemia
• Unsupervised clustering
• Sorafenib
• Immune