ReviewCancers2020
Cell-Mediated Release of Nanoparticles as a Preferential Option for Future Treatment of Melanoma.
Review in Cancers, 2020. 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, 9 citations in OpenAlex.
- Antitumoral Efficacy of AuNRs-Laden ECFCs In Vitro and In Vivo: Decoding the Heat and Rays Combo Treatment in Breast Cancer and Melanoma Cells.Advanced healthcare materials · 2025Article
- Suicide-Gene-Modified Extracellular Vesicles of Human Primary Uveal Melanoma in Future Therapies.International journal of molecular sciences · 2023Article
- Editorial on Special Issue "Advances and Novel Treatment Options in Metastatic Melanoma".Cancers · 2022Article
- Nanotechnology Addressing Cutaneous Melanoma: The Italian Landscape.Pharmaceutics · 2021Review
- Combined Toxicity of Gas Plasma Treatment and Nanoparticles Exposure in Melanoma Cells In Vitro.Nanomaterials (Basel, Switzerland) · 2021Article
- Advances in Natural or Synthetic Nanoparticles for Metastatic Melanoma Therapy and Diagnosis.Cancers · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Targeted and immune therapies have unquestionably improved the prognosis of melanoma patients. However the treatment of this neoplasm still requires approaches with a higher therapeutic index, in order to reduce shortcomings related to toxic effects and aspecific targeting. This means developing therapeutic tools derived with high affinity molecules for tumor components differentially expressed in melanoma cells with respect to their normal counterpart. Nanomedicine has sought to address this problem owing to the high modulability of nanoparticles. This approach exploits not only the enhanced permeability and retention effect typical of the tumor microenvironment (passive targeting), but also the use of specific "molecular antennas" that recognize some tumor-overexpressed molecules (active targeting). This line of research has given rise to the so-called "smart nanoparticles," some of which have already passed the preclinical phase and are under clinical trials in melanoma patients. To further improve nanoparticles partition within tumors, for some years now a line of thought is exploiting the molecular systems that regulate the innate tumor-homing activity of platelets, granulocytes, monocytes/macrophages, stem cells, endothelial-colony-forming cells, and red blood cells loaded with nanoparticles. This new vision springs from the results obtained with some of these cells in regenerative medicine, an approach called "cell therapy." This review takes into consideration the advantages of cell therapy as the only one capable of overcoming the limits of targeting imposed by the increased interstitial pressure of tumors.
Indexed as
Identifiers
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.