ArticleNeoplasia (New York, N.Y.)2013
Molecular characterization of patient-derived human pancreatic tumor xenograft models for preclinical and translational development of cancer therapeutics.
Article in Neoplasia (New York, N.Y.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 1 of them a synthesis that pooled it.
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
60 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Patient-Derived Xenograft Models in Cervical Cancer: A Systematic Review.International journal of molecular sciences · 2021Pooled it
- Can Complex 3D Models Effectively Replace 2D and Animal Models to Investigate the Microbe-Tumor-Immune Axis in Pancreatic Cancer Studies?Nutrients · 2026Review
- Harnessing PDX and PDX 2.0: the next-generation paradigm for precision oncology and translational breakthroughs.Molecular cancer · 2026Review
- Orthotopic and metastatic tumour models in preclinical cancer research.Pharmacology & therapeutics · 2024Review
- Metabolic difference between patient-derived xenograft model of pancreatic ductal adenocarcinoma and corresponding primary tumor.BMC cancer · 2024Article
- Structure-Activity Relationship of FL118 Platform Position 7 Versus Position 9-Derived Compounds and Their Mechanism of Action and Antitumor Activity.Journal of medicinal chemistry · 2023Article
- Article
- New Therapeutic Perspectives in Prostate Cancer: Patient-Derived Organoids and Patient-Derived Xenograft Models in Precision Medicine.Biomedicines · 2023Review
- Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice.Cancer cell international · 2023Review
- Alteration in Levels of Specific miRNAs and Their Potential Protein Targets between Human Pancreatic Cancer Samples, Adjacent Normal Tissue, and Xenografts Derived from These Tumors.Life (Basel, Switzerland) · 2023Article
- Experimental mouse models for translational human cancer research.Frontiers in immunology · 2023Review
- Review on Advanced Cancer Modeling for a Cancer Study.Current issues in molecular biology · 2022Article
- Preclinical Solid Tumor Models to Study Novel Therapeutics in Brain Metastases.Current protocols · 2021Article
- A pancreas tumor derived organoid study: from drug screen to precision medicine.Cancer cell international · 2021Review
- Patient-derived tumor xenograft and organoid models established from resected pancreatic, duodenal and biliary cancers.Scientific reports · 2021Article
- The Essential Factors of Establishing Patient-derived Tumor Model.Journal of Cancer · 2021Review
- Organoids in Lung Cancer Management.Frontiers in surgery · 2021Review
- Patient-derived cell line, xenograft and organoid models in lung cancer therapy.Translational lung cancer research · 2020Review
- A fast, simple, and cost-effective method of expanding patient-derived xenograft mouse models of pancreatic ductal adenocarcinoma.Journal of translational medicine · 2020Article
- Patient-Derived Xenograft Models of Pancreatic Cancer: Overview and Comparison with Other Types of Models.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
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Preclinical evaluation of novel cancer agents requires models that accurately reflect the biology and molecular characteristics of human tumors. Molecular profiles of eight pancreatic ductal adenocarcinoma patient tumors were compared to corresponding passages of xenografts obtained by grafting tumor fragments into immunocompromised mice. Molecular characterization was performed by copy number analysis, gene expression and microRNA microarrays, mutation analysis, short tandem repeat (STR) profiling, and immunohistochemistry. Xenografts were found to be highly representative of their respective tumors, with a high degree of genetic stability observed by STR profiling and mutation analysis. Copy number variation (CNV) profiles of early and late xenograft passages were similar, with recurrent losses on chromosomes 1p, 3p, 4q, 6, 8p, 9, 10, 11q, 12p, 15q, 17, 18, 20p, and 21 and gains on 1q, 5p, 8q, 11q, 12q, 13q, 19q, and 20q. Pearson correlations of gene expression profiles of tumors and xenograft passages were above 0.88 for all models. Gene expression patterns between early and late passage xenografts were highly stable for each individual model. Changes observed in xenograft passages largely corresponded to human stromal compartment genes and inflammatory processes. While some differences exist between the primary tumors and corresponding xenografts, the molecular profiles remain stable after extensive passaging. Evidence for stability in molecular characteristics after several rounds of passaging lends confidence to clinical relevance and allows for expansion of models to generate the requisite number of animals required for cohorts used in drug screening and development studies.
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.