Karmakar R, Kandalkar A, Wang HC, Mukundan A. From mutational signatures to practice: Artificial intelligence-guided repurposing for blast crisis chronic myeloid leukemia. World J Clin Oncol 2026; 17(2): 115068 [DOI: 10.5306/wjco.v17.i2.115068]
Corresponding Author of This Article
Arvind Mukundan, PhD, Assistant Professor, Postdoctoral Fellow, School of Engineering and Technology, Sanjivani University, Sanjivani Factory, Sahajan Anda Nagar, Kopargaon 423603, Maharastra, India. arvindmukund96@gmail.com
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Computer Science, Artificial Intelligence
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Letter to the Editor
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Feb 24, 2026 (publication date) through Feb 12, 2026
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World Journal of Clinical Oncology
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2218-4333
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Karmakar R, Kandalkar A, Wang HC, Mukundan A. From mutational signatures to practice: Artificial intelligence-guided repurposing for blast crisis chronic myeloid leukemia. World J Clin Oncol 2026; 17(2): 115068 [DOI: 10.5306/wjco.v17.i2.115068]
World J Clin Oncol. Feb 24, 2026; 17(2): 115068 Published online Feb 24, 2026. doi: 10.5306/wjco.v17.i2.115068
From mutational signatures to practice: Artificial intelligence-guided repurposing for blast crisis chronic myeloid leukemia
Riya Karmakar, Aditya Kandalkar, Hsiang-Chen Wang, Arvind Mukundan
Riya Karmakar, Hsiang-Chen Wang, Department of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan
Riya Karmakar, Arvind Mukundan, School of Engineering and Technology, Sanjivani University, Sanjivani Factory, Kopargaon 423603, Maharastra, India
Aditya Kandalkar, Department of Information Technology, Sanjivani College of Engineering, Kopargaon 423603, Maharastra, India
Co-first authors: Riya Karmakar and Aditya Kandalkar.
Co-corresponding authors: Hsiang-Chen Wang and Arvind Mukundan.
Author contributions: Mukundan A, Kandalkar A, Karmakar R, and Wang HC contributed to conceptualization, review, and editing; Mukundan A and Wang HC contributed to formal analysis and project administration; Karmakar R and Kandalkar A contributed to investigation and software; Wang HC contributed to supervision; Kandalkar A wrote the original draft; Mukundan A and Kandalkar A contributed equally to this manuscript and are co-first authors; Wang HC and Mukundan A contributed equally to the manuscript as co-corresponding authors. All authors have read and agreed to the published version of the manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Arvind Mukundan, PhD, Assistant Professor, Postdoctoral Fellow, School of Engineering and Technology, Sanjivani University, Sanjivani Factory, Sahajan Anda Nagar, Kopargaon 423603, Maharastra, India. arvindmukund96@gmail.com
Received: October 9, 2025 Revised: October 17, 2025 Accepted: December 18, 2025 Published online: February 24, 2026 Processing time: 122 Days and 15.5 Hours
Core Tip
Core Tip: An integrated omics-artificial intelligence pipeline categorizes blast crisis chronic myeloid leukemia into three actionable archetypes on the basis of whole exome data and Catalogue of Somatic Mutations in Cancer mutational signatures: breast cancer gene 2/tumor protein p53 [homologous recombination deficiency to poly(ADP-ribose) polymerase inhibitors], isocitrate dehydrogenases 1/2 or ten eleven translocation 2 (oncometabolism/epigenetics to isocitrate dehydrogenases inhibitors ± hypomethylating agents), and Janus kinase 2/colony stimulating factor 3 receptor (cytokine signaling to Janus kinase inhibitors). This method facilitates rapid, evidence-based repurposing in addition to tyrosine kinase inhibitor-based cytoreduction and use of transplant pathways. The prospective outcome is expected to iteratively enhance the mapping of signatures to drugs.
