Evidence map›Paper›PMID 40764606›Full record

ArticleBMC pharmacology & toxicology2025

Integrative genomic and bioinformatic prioritization of drug repurposing candidates for prostate cancer.

Lalu Muhammad Irham, Wirawan Adikusuma, Arief Rahman Afief, Sabiah Khairi, Rockie Chong, Syarifatul Mufidah, Rahmat Dani Satria, Eko Mugiyanto, Darmawi Darmawi, Danang Prasetyaning Amukti and 3 more

Abstract read
In one paragraph

Article in BMC pharmacology & toxicology, 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. Review
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

13 authors.

Lalu Muhammad IrhamFaculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, 55166, Indonesia. lalu.irham@pharm.uad.ac.id.
Wirawan AdikusumaResearch Center for Computing, Research Organization for Electronics and Informatics, National Research and Innovation Agency (BRIN), Cibinong, 16911, Indonesia.
Arief Rahman AfiefFaculty of Pharmacy, YPIB University, Majalengka, Indonesia.
Sabiah KhairiSchool of Nursing, College of Nursing, Taipei Medical University, Taipei, 11031, Taiwan.
Rockie ChongDepartment of Chemistry and Biochemistry, University of California, Los Angeles, USA.
Syarifatul MufidahFaculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, 55166, Indonesia.
Rahmat Dani SatriaDepartment of Clinical Pathology and Laboratory Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia.
Eko MugiyantoDepartment of Pharmacy, Faculty of Health Science, University of Muhammadiyah Pekajangan Pekalongan, Pekalongan, Indonesia.
Darmawi DarmawiDepartment of Histology, Faculty of Medicine, Universitas Riau, Diponegoro St No.1, Pekanbaru, Indonesia.
Danang Prasetyaning AmuktiDepartment of Pharmacy, Faculty of Health Sciences, Alma Ata University, Yogyakarta, Indonesia.
Brilliant Citra WirsahadaDepartment of Surgery, Faculty of Medicine, Universitas Muhammadiyah Surabya, Surabaya, Indonesia.
Petrina Theda PhilothraDepartement of Rehabilitation Medicine, General Hospital Yogyakarta City, Yogyakarta, Indonesia.
Indra JayaFaculty of Medicine, Universitas Riau, Pekanbaru, Riau, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveProstate cancer remains a prevalent global health challenge, with limited treatment options for advanced stages. There is a critical need to identify effective therapies through systematic integration of genomic and biological data.

methodsWe analyzed 10,911 single nucleotide polymorphisms (SNPs) in 554 genes from genome- and phenome-wide association studies to identify biological risk genes for prostate cancer. Bioinformatic analysis was used to map these genes to key pathways and potential drug targets. Drug repurposing opportunities were assessed through Connectivity Map (CMap) transcriptomic signature analysis in the PC3 prostate cancer cell line, with additional molecular docking studies to evaluate drug-target interactions.

resultsWe identified 77 prostate cancer-associated genes. Drug repurposing analysis revealed 59 drugs targeting 13 genes, including 11 approved for prostate cancer and 22 in clinical or preclinical development. Notably, 26 candidate drugs had not been previously linked to prostate cancer. CMap analysis prioritized five candidates: estradiol-benzoate and estradiol-cypionate (targeting ESR2), which showed the highest CMap scores, danazol and oxymetholone (targeting AR), and selumetinib (targeting MAP2K1/MEK), each demonstrating potential to modulate key pathways in prostate cancer. Molecular docking analysis further supported these findings, revealing that estradiol-benzoate and estradiol-cypionate have strong predicted binding affinities for ESR2, while selumetinib robustly interacts with MAP2K1. Conversely, danazol and oxymetholone displayed weaker predicted binding, suggesting a more limited capacity for direct protein engagement.

conclusionsIntegrating genomics, bioinformatics, and molecular docking provides an effective strategy for identifying and prioritizing drug repurposing candidates in prostate cancer. Estradiol-benzoate, estradiol-cypionate, and selumetinib emerge as promising candidates, meriting further preclinical and clinical evaluation for advanced prostate cancer therapy.

Indexed as

Antineoplastic AgentsDrug RepositioningProstatic NeoplasmsComputational BiologyGenomicsHumansMaleMolecular Docking SimulationPC-3 CellsPolymorphism, Single NucleotideAntineoplastic AgentsBioinformaticsDrug repurposingDrug target genesESR2 and MAP2K1Germline variantsProstate cancer

Identifiers

PMID40764606
PMCPMC12326658

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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.