ArticleJournal of pharmaceutical sciences2016
Development and Evaluation of Biodegradable Particles Coloaded With Antigen and the Toll-Like Receptor Agonist, Pentaerythritol Lipid A, as a Cancer Vaccine.
Article in Journal of pharmaceutical sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 21 citations in OpenAlex.
- Efficacy of Purified Borrelial Lipoproteins (PBL) as an oral formulation in reducing transmission of Lyme spirochetes from reservoir hosts tobioRxiv : the preprint server for biology · 2026Article
- Pentaerythritol-based lipid A bolsters the antitumor efficacy of a polyanhydride particle-based cancer vaccine.Nanomedicine : nanotechnology, biology, and medicine · 2019Article
- Sustained Release of Hydrogen Sulfide (HAnnals of biomedical engineering · 2019Article
- Polymeric micro- and nanoparticles for immune modulation.Biomaterials science · 2018Review
- Fabrication and Use of Poly(d,l-lactide-co-glycolide)-Based Formulations Designed for Modified Release of 5-Fluorouracil.Journal of pharmaceutical sciences · 2018Review
- Modifying Antigen-Encapsulating Liposomes with KALA Facilitates MHC Class I Antigen Presentation and Enhances Anti-tumor Effects.Molecular therapy : the journal of the American Society of Gene Therapy · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Immune adjuvants are important components of current and prospective cancer vaccines. In this study, we aimed at evaluating the use of a synthetic lipid A derivative, pentaerythritol lipid A (PET lipid A), loaded into poly(lactic-co-glycolic acid) particles, as a potential cancer vaccine adjuvant. Poly(lactic-co-glycolic acid) particles (size range: 250-600 nm) were successfully formulated to include PET lipid A and/or the model tumor antigen, chicken ovalbumin (OVA). It was shown that particulated PET lipid A had a distinct advantage at promoting secretion of the immune potentiating cytokine, IL-12p70, and upregulating key costimulatory surface proteins, CD86 and CD40, in murine dendritic cells in vitro. In a murine tumor model, involving prophylactic vaccination with various permutations of soluble versus particulated formulations of OVA with or without PET lipid A, modest benefit was observed in terms of OVA-specific cell-mediated immune responses when PET lipid A was delivered in particles. These findings translated into a corresponding trend toward increased survival of mice challenged with OVA-expressing tumor cells (E.G7). In terms of translation of safe adjuvants into the clinic, these results promote the concept of delivering toll-like receptor-4 agonists in particles because doing so improves their adjuvant properties, while decreasing the chances of adverse effects due to off-target uptake by nonphagocytic cells.
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What OpenQuestion holds
Registered trials
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.