Data Mining for Identification of Targets and Repurposed Drugs to Eliminate Persistent Chronic Myeloid Leukaemia Stem Cells: Targeting RAS/RAF Signalling

利用数据挖掘识别靶点和可重新利用的药物以消除持续存在的慢性粒细胞白血病干细胞:靶向 RAS/RAF 信号通路

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Abstract

BACKGROUND: Persistent leukaemic stem cells (LSCs) in chronic myeloid leukaemia (CML) are insensitive to targeted tyrosine kinase inhibitors (TKIs). Identifying alternative molecular vulnerabilities may offer new therapeutic opportunities. This study aimed to identify active RAS/RAF signalling pathway components in persistent CML-LSCs using publicly available datasets to propose a novel drug combination that could synergise with TKI therapy. METHODS: EMBL-EBI Single Cell Expression Atlas and Stemformatics were used to analyse gene expression within the chosen signalling pathway using DESeq2 analysis in R Studio. Genes that showed statistically significant differences across three comparisons (CML vs. normal; post vs. pre TKI; post TKI vs. normal) were evaluated for gene dependency (Chronos scores), expression profiles, and inhibitor sensitivity using the DepMap platform, with a focus on CML cell lines. Candidate inhibitors were identified using DrugBank. RESULTS: PPP2CA demonstrated broad essentiality with negative Chronos scores consistent with strong gene dependency. Its expression was consistently high, reinforcing its biological relevance in CML. LB-100 was found as a PP2A inhibitor under trial. Sensitivity analysis revealed LB-100 affected 548 cancer cell lines broadly. CONCLUSION: PPP2CA represents a promising therapeutic vulnerability in CML, supported by both strong dependency and consistent expression in myeloid models, while BRAF showed limited relevance outside mutation-driven cancers. Variation in experimental platforms, sample representation, and data integration across public datasets is a recognised study limitation. Nonetheless, LB-100 may provide a novel therapeutic avenue in CML, provided further preclinical functional and clinical validation is performed in patient-derived samples to confirm translational applicability of the findings.

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