Evidence map›Paper›PMID 40236999›Full record

ArticleCurrent research in toxicology2025

Bioinformatics study and cytotoxicity of several curcumin analogues in ovarian cancer.

Retno Murwanti, Ritmaleni, Navista Sri Octa Ujiantari, I Made Rhamandana Putra, Aliffian Farhan Wahyudi, Vigha Ilmanafi Arifka

Abstract read
In one paragraph

Article in Current research in 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. 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

6 authors.

Retno MurwantiDepartment of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
RitmaleniDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
Navista Sri Octa UjiantariDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
I Made Rhamandana PutraFaculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
Aliffian Farhan WahyudiFaculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
Vigha Ilmanafi ArifkaFaculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer ranks as Indonesia's third-leading cause of cancer-related death, emphasising the need for innovative treatments. This study combined bioinformatics, molecular docking, and experimental assays to tackle this challenge. We identified 166 ovarian cancer-related genes, with MYC standing out as a key target. Analysis of MYC mutations revealed prevalent alterations, though no significant survival differences were observed in patients with or without the mutations. Molecular docking pinpointed compound B155 as a promising MYC inhibitor. A preliminary cytotoxicity assay revealed compound B155's notable activity, with an 87.19 % inhibition of cell viability at 50 μM. Most of the other curcumin analogues only caused more than 50 % inhibition at the same concentration. This result suggests alternative mechanisms of action, possibly antioxidant effects, warranting further exploration. In summary, this study unveiled MYC as a prime target for ovarian cancer treatment, with curcumin analogues like B155 showing potential. Nonetheless, the complex factors affecting cytotoxicity underscore the need for deeper investigation into these compounds' mechanisms in ovarian cancer cells.

Indexed as

BioinformaticsCurcumin analoguesCytotoxicityDibenzylidene-cyclopentanoneOvarian cancer

Identifiers

PMID40236999
PMCPMC11999365

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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.