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©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Nov 24, 2025; 16(11): 111983
Published online Nov 24, 2025. doi: 10.5306/wjco.v16.i11.111983
Published online Nov 24, 2025. doi: 10.5306/wjco.v16.i11.111983
Omics and artificial intelligence integration for stratifying blast crisis CML using COSMIC signatures and pan-cancer precision drug repurposing
Abdulkareem AlGarni, Department of Oncology, King Abdulaziz Hospital, Al-Ahsa 31982, Saudi Arabia
Abdulkareem AlGarni, Nawaf Alanazi, Sarah AlMukhaylid, Yaqob Samir Taleb, Nada Alkhamis, Zafar Iqbal, Genomic & Experimental Precision Medicine (GEM), College of Applied Medical Sciences (COAMSA), King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS)/KAIMRC-ER/KAMC, Al-Ahsa 31982, Saudi Arabia
Nawaf Alanazi, Department of Oncology, King Abdulaziz Medical City, Al-Ahsa 31982, Saudi Arabia
Sultan Alqahtani, College of Medicine, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS)/KAIMRC/KAMC, Riyadh 11481, Saudi Arabia
Hassan Almasoudi, Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Najran University, Najran 61441, Saudi Arabia
Sameerah Shaheen, Abdulaziz Haji Siyal, Department of Anatomy, Stem Cell Unit, College of Medicine, King Saud University, P. O. Box 2925 (28), Riyadh 11461, Saudi Arabia
Aamer Aleem, Department of Medicine, College of Medicine, King Saud University Medical City, King Khalid University Hospital, King Saud University, Riyadh 11451, Saudi Arabia
Rizwan Naeem, Department of Oncology, Montefiore Medical Centre, Albert Einstein Medical College, New York, NY 10461, United States
Masood A Shammas, Department of Medical Oncology, Harvard (Dana Farber) Cancer Institute, Boston, MA 02132, United States
Giuseppe Saglio, Department of Oncology, University of Turin, Turin 10126, Italy
Deema Alroweilly, Department of Oncology, College of Medicine, King Saud University, Riyadh 11451, Saudi Arabia
Asraf Hussain, Department of Oncology, Chitwan Medical College, Bharatpur 33915, Nepal
Co-first authors: Abdulkareem AlGarni and Nawaf Alanazi.
Co-corresponding authors: Asraf Hussain and Zafar Iqbal.
Author contributions: AlGarni A, Alanazi N, AlMukhaylid S, and Alqahtani S performed the research; AlGarni A, Alanazi N, and Saglio G designed the research study; AlGarni A, Alanazi N, Saglio G, and Iqbal Z wrote the original draft; Almasoudi H and Samir Taleb Y developed and validated the methodology; Alkhamis N, Shaheen S, and Haji Siyal A carried out data curation and formal analysis; Aleem A, Naeem R, and Shamas MA performed software development and visualization; Alroweilly D conducted statistical validation; Hussain A and Iqbal Z supervised the project and secured funding; all authors reviewed and edited the manuscript, have read and agreed to the published version of the manuscript.
Institutional review board statement: The study was conducted in accordance with the King Abdullah International Medical Research Centre, National Guard Health Affairs, through project, No. RA17/002, approved it on 4th February 2019.
Informed consent statement: Written informed consent was obtained from the patients to publish this paper.
Conflict-of-interest statement: The authors acknowledge no conflicts of interest.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: Access to data made by next-generation sequencing can be obtained from NCBI, to which it was submitted, at https://www.ncbi.nlm.nih.gov/sra/PRJNA734750.
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/
Corresponding author: Asraf Hussain, MD, Department of Oncology, Chitwan Medical College, Bharatpur-10, Chitwan, Bharatpur 33915, Nepal. drasrafcardiology@gmail.com
Received: July 16, 2025
Revised: August 13, 2025
Accepted: September 30, 2025
Published online: November 24, 2025
Processing time: 128 Days and 22 Hours
Revised: August 13, 2025
Accepted: September 30, 2025
Published online: November 24, 2025
Processing time: 128 Days and 22 Hours
Core Tip
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.