Evidence map›Paper›PMID 39816079›Full record

ArticleNarra J2024

Promising candidate drug target genes for repurposing in cervical cancer: A bioinformatics-based approach.

Nurfi Pratiwi, Aida J Ulfah, Rachmadina Rachmadina, Lalu M Irham, Arief R Afief, Wirawan Adikusuma, Darmawi Darmawi, Rahmat A Kemal, Ina F Rangkuti, Maya Savira

Abstract read
In one paragraph

Article in Narra J, 2024. 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

10 authors.

Nurfi PratiwiMaster Program in Biomedical Sciences, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Aida J UlfahMaster Program in Biomedical Sciences, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Rachmadina RachmadinaMaster Program in Biomedical Sciences, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Lalu M IrhamFaculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia.
Arief R AfiefFaculty of Pharmacy, Universitas YPIB Majalengka, Majalengka, Indonesia.
Wirawan AdikusumaDepartment of Pharmacy, Universitas Muhammadiyah Mataram, Mataram, Indonesia.
Darmawi DarmawiDepartment of Histology, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Rahmat A KemalDepartment of Medical Biology, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Ina F RangkutiDepartment of Pathological Anatomy, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Maya SaviraGraduate School in Biomedical Sciences, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical cancer is the fourth most common cancer among women globally, and studies have shown that genetic variants play a significant role in its development. A variety of germline and somatic mutations are associated with cervical cancer. However, genomic data derived from these mutations have not been extensively utilized for the development of repurposed drugs for cervical cancer. The objective of this study was to identify novel potential drugs that could be repurposed for cervical cancer treatment through a bioinformatics approach. A comprehensive genomic and bioinformatics database integration strategy was employed to identify potential drug target genes for cervical cancer. Using the GWAS and PheWAS databases, a total of 232 genes associated with cervical cancer were identified. These pharmacological target genes were further refined by applying a biological threshold of six functional annotations. The drug target genes were then cross-referenced with cancer treatment candidates using the DrugBank database. Among the identified genes,

Indexed as

Antineoplastic AgentsComputational BiologyDrug RepositioningUterine Cervical NeoplasmsFemaleHumansAntineoplastic AgentsbioinformaticCervical cancerdrug candidatedrug target genesPARP inhibitor

Identifiers

PMID39816079
PMCPMC11731801

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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.