ReviewCancer research2015
Preclinical Models Provide Scientific Justification and Translational Relevance for Moving Novel Therapeutics into Clinical Trials for Pediatric Cancer.
Review in Cancer research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Orthotopic Implants in Mice.Methods in molecular biology (Clifton, N.J.) · 2027Article
- A White Paper on Advancing Long-Acting Therapeutics for Maternal and Pediatric Health by Bridging Gaps in Clinical Research, Access and Regulation.Clinical pharmacology and therapeutics · 2026Review
- Prioritization of novel agents for further investigation in pediatric non-rhabdomyosarcoma soft tissue sarcomas: A report from the Children's Oncology Group.European journal of cancer (Oxford, England : 1990) · 2025Review
- Insights from veterinary models for advancing oncolytic virotherapy through comparative oncology.Frontiers in molecular biosciences · 2025Review
- Navigating the Regulatory Landscape to Develop Pediatric Oncology Drugs: Expert Opinion Recommendations.Paediatric drugs · 2021Review
- Preclinical In Vivo Modeling of Pediatric Sarcoma-Promises and Limitations.Journal of clinical medicine · 2021Review
- Article
- Predictors of Success of Phase II Pediatric Oncology Clinical Trials.The oncologist · 2019Review
- Emerging novel agents for patients with advanced Ewing sarcoma: a report from the Children's Oncology Group (COG) New Agents for Ewing Sarcoma Task Force.F1000Research · 2019Review
- Patient-derived xenografts as preclinical neuroblastoma models.Cell and tissue research · 2018Review
- Article
- Lessons from Retinoblastoma: Implications for Cancer, Development, Evolution, and Regenerative Medicine.Trends in molecular medicine · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Despite improvements in survival rates for children with cancer since the 1960s, progress for many pediatric malignancies has slowed over the past two decades. With the recent advances in our understanding of the genomic landscape of pediatric cancer, there is now enthusiasm for individualized cancer therapy based on genomic profiling of patients' tumors. However, several obstacles to effective personalized cancer therapy remain. For example, relatively little data from prospective clinical trials demonstrate the selective efficacy of molecular-targeted therapeutics based on somatic mutations in the patient's tumor. In this commentary, we discuss recent advances in preclinical testing for pediatric cancer and provide recommendations for providing scientific justification and translational relevance for novel therapeutic combinations for childhood cancer. Establishing rigorous criteria for defining and validating druggable mutations will be essential for the success of ongoing and future clinical genomic trials for pediatric malignancies.
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.