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Publication Name World Journal of Clinical Oncology
Manuscript ID 115068
Country India
Received
2025-10-09 02:49
Peer-Review Started
2025-10-09 02:49
First Decision by Editorial Office Director
2025-10-17 07:40
Return for Revision
2025-10-17 07:40
Revised
2025-10-17 20:05
Publication Fee Transferred
Second Decision by Editor
2025-12-18 02:40
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director
2025-12-18 08:26
Articles in Press
2025-12-18 08:26
Edit the Manuscript by Language Editor
Typeset the Manuscript
2026-01-29 10:19
Publish the Manuscript Online
2026-02-06 06:30
ISSN 2218-4333 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Copyright © The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Computer Science, Artificial Intelligence
Manuscript Type Letter to the Editor
Article Title From mutational signatures to practice: Artificial intelligence-guided repurposing for blast crisis chronic myeloid leukemia
Manuscript Source Invited Manuscript
All Author List Riya Karmakar, Aditya Kandalkar, Hsiang-Chen Wang and Arvind Mukundan
ORCID
Author(s) ORCID Number
Hsiang-Chen Wang http://orcid.org/0000-0003-4107-2062
Arvind Mukundan http://orcid.org/0000-0002-7741-3722
Funding Agency and Grant Number
Corresponding Author Arvind Mukundan, Assistant Professor, PhD, Postdoctoral Fellow, School of Engineering and Technology, Sanjivani University, Sanjivani Factory, Sahajan Anda Nagar, Kopargaon 423603, Maharastra, India. arvindmukund96@gmail.com
Key Words Blast crisis chronic myeloid leukemia; Mutational signatures; Artificial intelligence; Machine learning; Whole exome sequencing; Homologous recombination deficiency; Poly(ADP-ribose) polymerase inhibitor
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.
Publish Date 2026-02-06 06:30
Citation

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

URL https://www.wjgnet.com/2218-4333/full/v17/i2/115068.htm
DOI https://dx.doi.org/10.5306/wjco.v17.i2.115068
Full Article (PDF) WJCO-17-115068-with-cover.pdf
Manuscript File 115068_Auto_Edited_114505.docx
Answering Reviewers 115068-answering-reviewers.pdf
Audio Core Tip 115068-audio.mp3
Conflict-of-Interest Disclosure Form 115068-conflict-of-interest-statement.pdf
Copyright License Agreement 115068-copyright-assignment.pdf
Non-Native Speakers of English Editing Certificate 115068-non-native-speakers.pdf
Peer-review Report 115068-peer-reviews.pdf
Scientific Misconduct Check 115068-scientific-misconduct-check.png
Scientific Editor Work List 115068-scientific-editor-work-list.pdf
CrossCheck Report 115068-crosscheck-report.pdf