Evidence map›Paper›PMID 38730647›Full record

ArticleCancers2024

Synergistic Action of Benzyl Isothiocyanate and Sorafenib in a Nanoparticle Delivery System for Enhanced Triple-Negative Breast Cancer Treatment.

Qi Wang, Nan Cheng, Wei Wang, Yongping Bao

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
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

4 authors.

Qi WangNorwich Medical School, University of East Anglia, Norwich NR4 7UQ, UK.ORCID 0000-0002-1822-995X
Nan ChengNorwich Medical School, University of East Anglia, Norwich NR4 7UQ, UK.
Wei WangNorwich Medical School, University of East Anglia, Norwich NR4 7UQ, UK.
Yongping BaoNorwich Medical School, University of East Anglia, Norwich NR4 7UQ, UK.ORCID 0000-0002-6425-0370

Funding

Cancer Prevention Research Trust UK R206861MED
6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) presents a therapeutic challenge due to its complex pathology and limited treatment options. Addressing this challenge, our study focuses on the effectiveness of combination therapy, which has recently become a critical strategy in cancer treatment, improving therapeutic outcomes and combating drug resistance and metastasis. We explored a novel combination therapy employing Benzyl isothiocyanate (BITC) and Sorafenib (SOR) and their nanoformulation, aiming to enhance therapeutic outcomes against TNBC. Through a series of in vitro assays, we assessed the cytotoxic effects of BITC and SOR, both free and encapsulated. The BITC-SOR-loaded nanoparticles (NPs) were synthesized using an amphiphilic copolymer, which demonstrated a uniform spherical morphology and favorable size distribution. The encapsulation efficiencies, as well as the sustained release profiles at varied pH levels, were quantified, revealing distinct kinetics that were well-modeled by the Korsmeyer-Peppas equation. The NP delivery system showed a marked dose-dependent cytotoxicity towards TNBC cells, with an IC50 of 7.8 μM for MDA-MB-231 cells, indicating improved efficacy over free drugs, while exhibiting minimal toxicity toward normal breast cells. Furthermore, the NPs significantly inhibited cell migration and invasion in TNBC models, surpassing the effects of free drugs. These findings underscore the potential of BITC-SOR-NPs as a promising therapeutic approach for TNBC, offering targeted delivery while minimizing systemic toxicity.

Indexed as

benzyl isothiocyanatebreast cancernanoencapsulationSorafenib

Identifiers

PMID38730647
PMCPMC11083210

What OpenQuestion holds

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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.