Evidence mapPaperPMID 40713639Full record

ReviewJournal of translational medicine2025

Multi-omics based and AI-driven drug repositioning for epigenetic therapy in female malignancies.

Annamaria Salvati, Viola Melone, Alessandro Giordano, Jessica Lamberti, Domenico Palumbo, Luigi Palo, Dilia Rea, Domenico Memoli, Vittoria Simonis, Elena Alexandrova and 5 more

Abstract readReview
In one paragraph

Review in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. c-Medical sciences (Basel, Switzerland) · 2026
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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

15 authors.

Annamaria Salvati *Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Viola Melone *Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Alessandro GiordanoLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Jessica LambertiLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Domenico PalumboLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Luigi PaloLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Dilia ReaLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Domenico MemoliLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Vittoria SimonisLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Elena AlexandrovaLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Francesco SilvestroLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Francesca RizzoLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Alessandro WeiszLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy.
Roberta TaralloLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy. rtarallo@unisa.it.ORCID 0000-0001-9668-3632
Giovanni NassaLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, via S. Allende, 1, Baronissi, 84081, SA, Italy. gnassa@unisa.it.

Funding

Fondazione AIRC per la ricerca sul cancro ETS IG-23068Ministero dell'Università e della Ricerca 202282CMEAMinistero dell'Università e della Ricerca 2022A7HJEM
6 · The paper itself

Abstract

Histone post-translational modifications (PTMs) have long been recognized as critical regulators of chromatin dynamics and gene expression, with aberrations in these processes driving tumorigenesis, immune escape, metastasis, and therapy resistance. While multi-omics technologies are generating ever more detailed maps of the histone landscape, translating these insights into clinical practice remains challenging. The ongoing convergence of high-throughput omics technologies and Artificial Intelligence (AI) is revolutionizing drug repositioning strategies, offering new precision tools to identify histone-targeted therapies for solid tumors. In this review, we explore how AI-driven multi-omics integration is currently reshaping therapeutic opportunities by uncovering novel drug-target-patient associations with unprecedented accuracy. Special focus is given to gynecologic and breast cancers, where chromatin remodeling dysregulation is particularly widespread, conventional therapeutic approaches have demonstrated substantial limitations and drug resistance represents a major clinical obstacle. These aggressive and lethal cancers exemplify areas where AI-powered repurposing of epi-drugs is making tangible clinical advances, enhancing tumor sensitivity to treatments like immunotherapy, but also offering new avenues to overcome challenging phenomena such as drug resistance and cancer relapse. We critically discuss these challenges and the effectiveness of a combination strategy approaches based on AI-driven patient stratification and biomarker-guided therapy optimization to maximize clinical benefits. In an era where precision oncology demands both specific drugs and the application of smarter strategies, the integration of AI, multi-omics, and targeting of chromatin remodelers may herald a transformative shift in the management of solid tumors, bridging the gap between biological insights and therapeutic innovation.

Indexed as

Artificial IntelligenceDrug RepositioningEpigenesis, GeneticNeoplasmsBreast NeoplasmsFemaleHumansMultiomics

Identifiers

PMID40713639
PMCPMC12297790

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.