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Articles Published Processes
2/6/2026 6:30:40 AM | Browse: 46 | Download: 165
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Received |
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2025-10-09 02:49 |
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Peer-Review Started |
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2025-10-09 02:49 |
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First Decision by Editorial Office Director |
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2025-10-17 07:40 |
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Return for Revision |
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2025-10-17 07:40 |
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Revised |
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2025-10-17 20:05 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2025-12-18 02:40 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2025-12-18 08:26 |
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Articles in Press |
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2025-12-18 08:26 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-01-29 10:19 |
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Publish the Manuscript Online |
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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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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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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
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Riya Karmakar, Aditya Kandalkar, Hsiang-Chen Wang and Arvind Mukundan |
| ORCID |
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| Funding Agency and Grant Number |
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| 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 |
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