Evidence map›Paper›PMID 42156642›Full record

ArticleJournal of the Egyptian National Cancer Institute2026

Unlocking new therapeutic horizons through integrative bioinformatics and transcriptomics for drug repositioning in breast cancer therapy.

Wirawan Adikusuma, Lalu Muhammad Irham, Rahmat Dani Satria, Ika Nurlaila, Dyah Laksmi Dewi, Firdayani Firdayani, Inna Syafarina

Abstract read
In one paragraph

Article in Journal of the Egyptian National Cancer Institute, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Wirawan AdikusumaResearch Center for Computing, Research Organization for Electronics and Informatics, National Research and Innovation Agency, Jakarta, Indonesia. adikusuma28@gmail.com.
Lalu Muhammad IrhamFaculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia. lalu.irham@pharm.uad.ac.id.
Rahmat Dani SatriaDepartment of Clinical Pathology and Laboratory Medicine, Faculty of Medicine, Public Health and Nursing, Gadjah Mada University, Yogyakarta, Indonesia.
Ika NurlailaCollaboration Research Center for Precision Oncology Based Omics, Yogyakarta, Indonesia.
Dyah Laksmi DewiCollaboration Research Center for Precision Oncology Based Omics, Yogyakarta, Indonesia.
Firdayani FirdayaniResearch Center for Vaccine and Drugs, Research Organization for Health, National Research and Innovation Agency, Jakarta, Indonesia.
Inna SyafarinaResearch Center for Computing, Research Organization for Electronics and Informatics, National Research and Innovation Agency, Jakarta, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer (BRCA) remains one of the most frequently diagnosed malignancies and a leading cause of cancer-related mortality among women worldwide. Its molecular heterogeneity and limited therapeutic options for aggressive subtypes highlight the need for novel treatment strategies. Drug repositioning offers a promising approach by identifying new therapeutic uses for existing drugs with established safety profiles.

methodsWe applied an integrative transcriptomic and bioinformatics framework to identify candidate drug targets and repurposed drugs for BRCA. Differentially expressed genes (DEGs) were identified from four Gene Expression Omnibus (GEO) microarray datasets using the limma package with thresholds of |log2 fold change| > 1 and false discovery rate (FDR) < 0.05. Overlapping DEGs were expanded through protein-protein interaction analysis using the STRING database. Functional annotation across ten biological evidence categories was performed using WebGestalt to prioritize BRCA risk genes through a multi-criteria scoring approach. Drug-gene interactions were then analyzed using the Drug-Gene Interaction Database (DGIdb), and tissue-specific gene expression was evaluated using the GTEx database.

resultsTwenty-eight consistently dysregulated genes were identified and expanded into a 77-gene interaction network. Functional prioritization yielded 18 BRCA risk genes, including five druggable targets associated with 11 candidate drugs. ITGB7 emerged as a promising biomarker and therapeutic target, with vedolizumab identified as the top candidate drug.

conclusionsThis study highlights the potential of integrative transcriptomic analysis to identify biomarkers and drug repositioning candidates in BRCA, providing a foundation for further experimental validation.

Indexed as

Antineoplastic AgentsBreast NeoplasmsComputational BiologyDrug RepositioningTranscriptomeFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansProtein Interaction MapsAntineoplastic AgentsBreast cancerDrug repositioningITGB7TranscriptomicsVedolizumab

Identifiers

PMID42156642
PMCPMC13313288

What Socratic holds

Textmetadata
LicenceCC BY
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.