Evidence map›Paper›PMID 40063190›Full record

ArticleIrish journal of medical science2025

Let-7a microRNA modulates caspase-3-dependent apoptosis in melanoma cells treated with dabrafenib and trametinib combination.

Murat Keser, Harika Atmaca

Abstract read
In one paragraph

Article in Irish journal of medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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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

2 authors.

Murat KeserDepartment of Medical Oncology, Izmir Tepecik Education and Research Hospital, University of Health Sciences, Izmir, Türkiye.ORCID http://orcid.org/0000-0003-3834-0863
Harika AtmacaDepartment of Biology, Faculty of Engineering and Natural Sciences, Celal Bayar University, 45140, Manisa, Türkiye. harika.atmaca@cbu.edu.tr.ORCID https://orcid.org/0000-0002-8459-4373

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalignant melanoma is an aggressive tumor with high resistance to therapy. The emergence of RAS-driven secondary cancers and BRAF-inhibitor resistance has led to the development of combination therapies targeting both BRAF and MEK.

aimsThis study explored the mechanisms underlying the synergistic effects of dabrafenib (DAB) and trametinib (TM) in drug-resistant A375 and RPMI 7951 melanoma cells.

methodsCytotoxicity was assessed via MTT assay and combination effects were evaluated via combination index analysis. Apoptosis was analyzed by DNA fragmentation ELISA, while ectopic let-7a miRNA expression and inhibition were performed using lipofection. Gene expression levels were quantified by qRT-PCR, and protein expression was assessed via Western blot.

resultsThe combination of 0.7 μM DAB and 5.0 μM TM exhibited synergistic cytotoxicity by inhibiting the pERK1/2 signaling pathway and inducing MITF expression. This resulted in mitochondria-mediated apoptosis, characterized by a decrease in anti-apoptotic Bcl-2 and an increase in pro-apoptotic Bax, caspase-9, and caspase-3 levels. Additionally, Let-7a was identified as a crucial regulator of apoptosis sensitivity by targeting caspase-3, the key executor of apoptosis.

conclusionsThese findings provide new insights into overcoming melanoma drug resistance through combined BRAF/MEK inhibition.

Indexed as

ApoptosisCaspase 3ImidazolesMelanomaMicroRNAsOximesPyridonesPyrimidinonesCell Line, TumorDrug Resistance, NeoplasmDrug SynergismHumansCASP3 protein, humanCaspase 3dabrafenibImidazolesMicroRNAsmirnlet7 microRNA, humanOximesPyridonesPyrimidinonestrametinibApoptosisDabrafenibLet-7aMelanomaSynergismTrametinib

Identifiers

PMID40063190
PMCPMC12276103

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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.