Evidence map›Paper›PMID 41355924›Full record

ArticleWorld journal of clinical oncology2025

Omics and artificial intelligence integration for stratifying blast crisis CML using COSMIC signatures and pan-cancer precision drug repurposing.

Abdulkareem AlGarni, Nawaf Alanazi, Sarah AlMukhaylid, Sultan Alqahtani, Hassan Almasoudi, Yaqob Samir Taleb, Nada Alkhamis, Sameerah Shaheen, Abdulaziz Haji Siyal, Aamer Aleem and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in World journal of clinical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Abdulkareem AlGarniDepartment of Oncology, King Abdulaziz Hospital, Al-Ahsa 31982, Saudi Arabia.
Nawaf AlanaziGenomic & 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.
Sarah AlMukhaylidGenomic & 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.
Sultan AlqahtaniCollege of Medicine, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS)/KAIMRC/KAMC, Riyadh 11481, Saudi Arabia.
Hassan AlmasoudiDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Najran University, Najran 61441, Saudi Arabia.
Yaqob Samir TalebGenomic & 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.
Nada AlkhamisGenomic & 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.
Sameerah ShaheenDepartment of Anatomy, Stem Cell Unit, College of Medicine, King Saud University, P. O. Box 2925 (28), Riyadh 11461, Saudi Arabia.
Abdulaziz Haji SiyalDepartment of Anatomy, Stem Cell Unit, College of Medicine, King Saud University, P. O. Box 2925 (28), Riyadh 11461, Saudi Arabia.
Aamer AleemDepartment of Medicine, College of Medicine, King Saud University Medical City, King Khalid University Hospital, King Saud University, Riyadh 11451, Saudi Arabia.
Rizwan NaeemDepartment of Oncology, Montefiore Medical Centre, Albert Einstein Medical College, New York, NY 10461, United States.
Masood A ShammasDepartment of Medical Oncology, Harvard (Dana Farber) Cancer Institute, Boston, MA 02132, United States.
Giuseppe SaglioDepartment of Oncology, University of Turin, Turin 10126, Italy.
Deema AlroweillyDepartment of Oncology, College of Medicine, King Saud University, Riyadh 11451, Saudi Arabia.
Asraf HussainDepartment of Oncology, Chitwan Medical College, Bharatpur 33915, Nepal. drasrafcardiology@gmail.com.
Zafar IqbalGenomic & 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.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough chronic-phase chronic myeloid leukemia (CP-CML) is treatable and nearly curable in about 50% of patients, accelerated-phase chronic myeloid leukemia (AP-CML) shows concerning drug resistance, while blast crisis chronic myeloid leukemia (BC-CML) is highly lethal. Advances in whole exome sequencing (WES) reveal pan-cancer mutations in BC-CML, supporting mutation-guided therapies beyond Breakpoint cluster region-Abelson. Artificial intelligence (AI) and machine learning (ML) enable genomic stratification and drug repurposing, addressing overlooked actionable mutations.

aimTo stratify BC-CML into molecular subtypes using WES, ML, and AI for precision drug repurposing.

methodsIncluded 123 CML patients (111 CP-CML, 5 AP-CML, 7 BC-CML). WES identified pan-cancer mutations. Variants annotated

resultsIn this exploratory, hypothesis-generating study of BC-CML patients (

conclusionThis WES-AI-ML framework provides mutation-guided therapies for BC-CML, enabling real-time stratification and Food and Drug Administration-approved drug repurposing. While this exploratory study is limited by its small sample size (

Indexed as

Artificial intelligence-guided drug repurposingBlast crisis chronic myeloid leukemia precision therapyCatalogue of Somatic Mutations in Cancer signature-driven oncologyMachine learning in leukemia treatmentPan-cancer genomic stratification

Identifiers

PMID41355924
PMCPMC12678951

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.