| 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: https://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 |
Hematology |
| Manuscript Type |
Observational Study |
| Article Title |
Omics and artificial intelligence integration for stratifying blast crisis CML using COSMIC signatures and pan-cancer precision drug repurposing
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Abdulkareem AlGarni, Nawaf Alanazi, Sarah AlMukhaylid, Sultan Alqahtani, Hassan Almasoudi, Yaqob Samir Taleb, Nada Alkhamis, Sameerah Shaheen, Abdulaziz Haji Siyal, Aamer Aleem, Rizwan Naeem, Masood A Shammas, Giuseppe Saglio, Deema Alroweilly, Asraf Hussain and Zafar Iqbal |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Asraf Hussain, MD, Department of Oncology, Chitwan Medical College, Bharatpur-10, Chitwan, Bharatpur 33915, Nepal. drasrafcardiology@gmail.com |
| Key Words |
Blast crisis chronic myeloid leukemia precision therapy; Pan-cancer genomic stratification; Artificial intelligence-guided drug repurposing; Catalogue of Somatic Mutations in Cancer signature-driven oncology; Machine learning in leukemia treatment |
| Core Tip |
This study integrates whole-exome sequencing, machine learning, and artificial intelligence-driven drug repurposing to stratify blast crisis chronic myeloid leukemia (BC-CML) into three molecular subtypes based on pan-cancer mutations and Catalogue of Somatic Mutations in Cancer signatures. By identifying cluster-specific therapies (e.g., polyadenosine-diphosphate-ribose polymerase, isocitrate dehydrogenase, and Janus kinase inhibitors), the framework enables precision oncology for BC-CML, offering a scalable model for real-time patient stratification and Food and Drug Administration/European Medicines Agency-approved drug repurposing in re-lapsed/refractory hematologic malignancies. |
| Publish Date |
2025-11-21 07:06 |
| Citation |
<p>AlGarni A, Alanazi N, AlMukhaylid S, Alqahtani S, Almasoudi H, Samir Taleb Y, Alkhamis N, Shaheen S, Haji Siyal A, Aleem A, Naeem R, Shammas MA, Saglio G, Alroweilly D, Hussain A, Iqbal Z. Omics and artificial intelligence integration for stratifying blast crisis CML using COSMIC signatures and pan-cancer precision drug repurposing. <i>World J Clin Oncol</i> 2025; 16(11): 111983</p> |
| URL |
https://www.wjgnet.com/2218-4333/full/v16/i11/111983.htm |
| DOI |
https://dx.doi.org/10.5306/wjco.v16.i11.111983 |
