ReviewFrontiers in molecular biosciences2024
Advances and challenges in gene therapy strategies for pediatric cancer: a comprehensive update.
Review in Frontiers in molecular biosciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Transforming tumor microenvironments: nanotechnology and gene therapy in cellular signaling and epigenetic insight into chemo-resistance.Journal of experimental & clinical cancer research : CR · 2026Review
- Engraftment Outcome of CRISPR/Cas9-Edited Hematopoietic Stem Cells for Genetic Diseases: A Systematic Review and Meta-Analysis of Preclinical Evidence.Journal of hematology · 2026Article
- Cross-border access to clinical trials: participation of pediatric patients and language inclusion.Pediatric research · 2026Article
- Next-generation sequencing in cancer diagnosis and treatment: clinical applications and future directions.Discover oncology · 2025Review
- The promise of gene therapy in common types of dementia.BioImpacts : BI · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pediatric cancers represent a tragic but also promising area for gene therapy. Although conventional treatments have improved survival rates, there is still a need for targeted and less toxic interventions. This article critically analyzes recent advances in gene therapy for pediatric malignancies and discusses the challenges that remain. We explore the innovative vectors and delivery systems that have emerged, such as adeno-associated viruses and non-viral platforms, which show promise in addressing the unique pathophysiology of pediatric tumors. Specifically, we examine the field of chimeric antigen receptor (CAR) T-cell therapies and their adaptation for solid tumors, which historically have been more challenging to treat than hematologic malignancies. We also discuss the genetic and epigenetic complexities inherent to pediatric cancers, such as tumor heterogeneity and the dynamic tumor microenvironment, which pose significant hurdles for gene therapy. Ethical considerations specific to pediatric populations, including consent and long-term follow-up, are also analyzed. Additionally, we scrutinize the translation of research from preclinical models that often fail to mimic pediatric cancer biology to the regulatory landscapes that can either support or hinder innovation. In summary, this article provides an up-to-date overview of gene therapy in pediatric oncology, highlighting both the rapid scientific progress and the substantial obstacles that need to be addressed. Through this lens, we propose a roadmap for future research that prioritizes the safety, efficacy, and complex ethical considerations involved in treating pediatric patients. Our ultimate goal is to move from incremental advancements to transformative therapies.
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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.