ReviewInternational journal of molecular sciences2022
Application of Perinatal Derivatives on Oncological Preclinical Models: A Review of Animal Studies.
Review in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Article
- Evaluation of the Anti-Cancer Potential of Extracellular Vesicles Derived from Human Amniotic Fluid Stem Cells: Focus on Effective miRNAs in the Treatment of Melanoma Progression.International journal of molecular sciences · 2024Article
- Guidelines to Analyze Preclinical Studies Using Perinatal Derivatives.Methods and protocols · 2023Article
- Preparation of human amniotic membrane for transplantation in different application areas.Frontiers in transplantation · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
The increasing cancer incidence has certified oncological management as one of the most critical challenges for the coming decades. New anticancer strategies are still needed, despite the significant advances brought to the forefront in the last decades. The most recent, promising therapeutic approaches have benefitted from the application of human perinatal derivatives (PnD), biological mediators with proven benefits in several fields beyond oncology. To elucidate preclinical results and clinic outcomes achieved in the oncological field, we present a narrative review of the studies resorting to animal models to assess specific outcomes of PnD products. Recent preclinical evidence points to promising anticancer effects offered by PnD mediators isolated from the placenta, amniotic membrane, amniotic fluid, and umbilical cord. Described effects include tumorigenesis prevention, uncontrolled growth or regrowth inhibition, tumor homing ability, and adequate cell-based delivery capacity. Furthermore, PnD treatments have been described as supportive of chemotherapy and radiological therapies, particularly when resistance has been reported. However, opposite effects of PnD products have also been observed, offering support and trophic effect to malignant cells. Such paradoxical and dichotomous roles need to be intensively investigated. Current hypotheses identify as explanatory some critical factors, such as the type of the PnD biological products used or the manufacturing procedure to prepare the tissue/cellular treatment, the experimental design (including human-relevant animal models), and intrinsic pathophysiological characteristics. The effective and safe translation of PnD treatments to clinical practice relies on the collaborative efforts of all researchers working with human-relevant oncological preclinical models. However, it requires proper guidelines and consensus compiled by experts and health workers who accurately describe the methodology of tissue collection, PnD isolation, manufacturing, preservation, and delivery to the final user.
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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.