GENE AND METABOLITE SIGNATURES IN CHRONIC MYELOID LEUKEMIA PROGRESSION: IMPLICATIONS FOR THERAPEUTIC RESISTANCE AND BIOMARKER DISCOVERY

Abstract

Introduction: Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm characterized by the presence of the Philadelphia chromosome (Ph) and/or the BCR::ABL1 oncogene, which encodes the constitutively activated Bcr-Abl tyrosine kinase protein. Bcr-Abl tyrosine kinase promotes the activation of various cellular signaling pathways, resulting in exacerbated cell proliferation and resistance to apoptosis. CML is initially diagnosed in the chronic phase, characterized by uncontrolled clonal expansion and a high white blood cell count. Without an effective drug intervention, CML may progress to accelerated and blast phases, characterized by high counts of immature myeloid/lymphoid cells in the bone marrow and peripheral blood. The tyrosine kinase inhibitor (TKI) is the gold standard treatment for CML patients. This therapy can induce high rates of hematological, cytogenetic, and molecular remission in CML patients. However, disease progression and therapeutic resistance remain a challenge in improving the prognosis of CML patients. In this context, studies on the cellular and molecular mechanisms involved in TKI resistance and CML progression are still necessary to identify new biomarkers and therapeutic targets. Aims: 1) To describe gene signatures that predicts CML progression and response to therapy; 2) To explore the relationship between transcriptomic and the metabolomic plasma profiles from CML patients. Subjects, Material and methods: Three publicly available gene expression datasets comparing patients with CML in the chronic phase (CP) and CML patients in the advanced phase (AP) were analyzed. The in silico analysis was performed to identify the set of differentially expressed genes (DEGs) and the gene signature associated with progression. The results were validated through gene expression in patients at different stages of CML using real-time PCR. Additionally, lipid mediators were quantified in plasma samples from 28 CML patients using Liquid Chromatography-Mass Spectrometry (LC/MS). Results: The in silico analysis by principal component analysis (PCA) revealed the separation of samples from CML patients in CP and AP. The Venn diagram identified the most significant DEGs distinguishing AP from CP in CML patients. Furthermore, DEG analysis highlighted the enrichment of the sphingolipid pathway. Metabolomic analysis of the plasma by LC/MS indicated that CML patients in different phases presented differential profiles of active metabolites. Conclusion: Transcriptome analysis revealed gene signatures that have the potential to become biomarkers for CML progression. Additionally, the gene enrichment analysis highlighted the differential bioactive metabolites in CML patients at advanced phases. The analysis of differentially abundant metabolites emerged as a promising criterion to identify patients predisposed to progression and who may not respond effectively to TKIs. Support: Supported by CNPq (number 308326/2021-0 and 406361/2021-5); CAPES (process number 001) and FAPESP process number 2021/06841-3 and 2018/00583-0.