Data Mining for Identification of Targets and Repurposed Drugs to Eliminate Persistent Chronic Myeloid Leukaemia Stem...

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Persistent leukaemic stem cells (LSCs) in chronic myeloid leukaemia (CML) exhibit resistance to tyrosine kinase inhibitors (TKIs).
• Identifying novel molecular targets is crucial for developing alternative therapeutic strategies against CML.
• This research focuses on the RAS/RAF signalling pathway for potential CML vulnerabilities.

Purpose of the Study:

• To identify active components within the RAS/RAF signalling pathway in persistent CML-LSCs.
• To explore potential drug combinations that could enhance TKI therapy efficacy.
• To investigate novel therapeutic avenues for TKI-resistant CML.

Main Methods:

• Analysis of gene expression in CML versus normal cells and TKI-treated versus untreated samples using public datasets (EMBL-EBI, Stemformatics).
• Utilized DESeq2 for differential gene expression analysis and the DepMap platform for assessing gene dependency (Chronos scores) and inhibitor sensitivity.
• Identified candidate inhibitors, including PP2A inhibitor LB-100, using DrugBank.

Main Results:

• PPP2CA showed significant gene dependency (negative Chronos scores) and consistent high expression in CML models.
• The PP2A inhibitor LB-100 demonstrated broad sensitivity across numerous cancer cell lines.
• BRAF was found to have limited relevance in CML, unlike in mutation-driven cancers.

Conclusions:

• PPP2CA represents a potential therapeutic vulnerability in CML due to its strong dependency and expression.
• LB-100 offers a potential novel therapeutic strategy for CML, possibly synergizing with TKIs.
• Further preclinical and clinical validation is required to confirm the translational applicability of LB-100 in patient-derived CML samples.