Evidence map›Paper›PMID 42003077›Full record

ArticleCurrent drug targets2026

(E)-Labda dial-Loaded Nanoparticles for Triple Negative Breast Cancer.

Anum Munir, Muhammad Rizwan, Alan Janbey

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Article in Current drug targets, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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0 citing papers in PubMed.

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4 · The record

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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

3 authors.

Anum MunirDivision of Natural Sciences, University of Kent, Canterbury, Kent, England.ORCID 0000-0002-8411-0236
Muhammad RizwanDepartment of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Alan JanbeyDepartment of Health and Applied Biology, The London College UCK, Cranford, London, England.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTriple-negative breast cancer (TNBC) is the most aggressive kind of breast cancer, with no hormone receptors and resistance to targeted therapy. Chemotherapy is the current standard; however, it is limited by toxicity, poor response, and high recurrence, emphasising the need for innovative methods.

methodsThis study investigates the therapeutic potential of (E)-labda-8(17), 12-diene-15,16-dial ((E)-labda dial), a bioactive chemical found in Curcuma amada (mango ginger) that was formulated into nanoparticles to increase transport and effectiveness. Whole-genome sequencing of TNBC cell lines was used to detect protein-altering mutations, which were then assessed using molecular docking and dynamics simulations to assess (E)-labda dial interactions with key mutant proteins (BRCA1, BRCA2, BARD1, PALB2, TP53, CHEK2). Lipid-based nanoparticles (LNPs) and polymeric nanoparticles (PNPs) were developed and tested for drug encapsulation, release kinetics, and stability. MTT and other functional tests were used to assess cytotoxic effects, and in silico pharmacokinetic models were carried out to anticipate treatment results.

resultsResults showed that PNPs outperformed LNPs in terms of encapsulation efficiency, sustained drug release, and tumour inhibition. Docking investigations demonstrated that mutant CHEK2, BARD1, and PALB2 bind to (E)-labda dial more strongly, indicating that carcinogenic pathways may be disrupted. DISCUSSION: These data, taken together, emphasise the abilities of (E)-labda dial-loaded nanoparticles as a targeted treatment method for TNBC, with potential effectiveness and toxicity benefits over traditional chemotherapy.

conclusionThis work lays the basis for precision and personalised treatment for TNBC patients. However, future optimisation and clinical validation of these nanoparticles can be done in future to determine their translational potential for use in practice.

Indexed as

NanoparticlesSesquiterpenesTriple Negative Breast NeoplasmsCell Line, TumorCurcumaDrug LiberationFemaleHumansMolecular Docking SimulationMolecular Dynamics SimulationSesquiterpenesCurcuma Amada(E)-labda dialmango gingernanoparticlesprecision medicinetargeted therapy

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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.