Identification of common genes and pathways underlying imatinib and nilotinib treatment in CML: a Bioinformatics

Yalda Hekmatshoar1, Yalda Rahbar Saadat2, Tulin Ozkan3

  • 1Department of Medical Biology, School of Medicine, Altinbas University, Istanbul, Turkey.

Insights

This study identifies novel gene targets for chronic myeloid leukemia (CML) treatment by analyzing gene expression changes after imatinib and nilotinib therapy. Key upregulated and downregulated genes were pinpointed as potential diagnostic and therapeutic targets for CML patients.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • Imatinib (IMA) and nilotinib are crucial BCR-ABL tyrosine kinase inhibitors for chronic myeloid leukemia (CML).
  • Identifying novel therapeutic targets is essential for improving CML treatment outcomes.

Purpose of the Study:

  • To identify potential new therapeutic targets for CML by analyzing transcriptome-wide gene expression changes.
  • To discover common differentially expressed genes (DEGs) in K562 cells treated with imatinib and nilotinib.

Main Methods:

  • Downloaded and analyzed microarray data (GSE19567) from the Gene Expression Omnibus (GEO).
  • Identified common upregulated and downregulated genes between imatinib- and nilotinib-treated K562 cells.
  • Utilized STRING and Cytoscape for protein-protein interaction (PPI) network analysis and identified hub genes.

Main Results:

  • Identified 626 common upregulated and 268 common downregulated DEGs.
  • Gene Ontology (GO) analysis revealed enrichment in functions such as iron ion binding, protein tyrosine kinase activity, and transcription factor activity.
  • KEGG pathway analysis indicated associations with microRNAs in cancer, PI3K-Akt signaling, hematopoietic cell lineage, and lysosome pathways.
  • Identified specific upregulated (e.g., MYH9, RXRA, CYP1A1) and downregulated (e.g., YARS, CEBPB, CCND1, MYC, VEGFA) hub genes.

Conclusions:

  • The identified hub genes represent potential novel targets for CML diagnosis and therapy.
  • Transcriptome analysis provides valuable insights into the molecular mechanisms underlying CML treatment response.
  • Further validation of these genes could lead to the development of more effective CML treatment strategies.

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