ArticleAmerican journal of translational research2019
Establishment of the PDTX model of gynecological tumors.
Article in American journal of translational research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Patient-Derived Xenograft Models in Cervical Cancer: A Systematic Review.International journal of molecular sciences · 2021Pooled it
- The mouse resource at National Resource Center for Mutant Mice of China.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Review
- Innovative insights into extrachromosomal circular DNAs in gynecologic tumors and reproduction.Protein & cell · 2024Review
- Validation of a Patient-Derived Xenograft Model for Cervical Cancer Based on Genomic and Phenotypic Characterization.Cancers · 2022Article
- A multicenter clinical study: personalized medication for advanced gastrointestinal carcinomas with the guidance of patient-derived tumor xenograft (PDTX).Journal of cancer research and clinical oncology · 2022Article
- The mouse resource at National Resource Center for Mutant Mice.Mammalian genome : official journal of the International Mammalian Genome Society · 2022Review
- Opportunities and challenges of patient-derived models in cancer research: patient-derived xenografts, patient-derived organoid and patient-derived cells.World journal of surgical oncology · 2022Review
- Identification of Prognostic Markers of Gynecologic Cancers Utilizing Patient-Derived Xenograft Mouse Models.Cancers · 2022Article
- Patient-Derived Xenografts Are a Reliable Preclinical Model for the Personalized Treatment of Epithelial Ovarian Cancer.Frontiers in oncology · 2021Article
- The Application of Patient-Derived Xenograft Models in Gynecologic Cancers.Journal of Cancer · 2020Review
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveFresh tumor tissues from patients with gynecological tumors were obtained by surgery or biopsy, and transplanted into NOD-Prkdcem26ll2rgem26Nju (NCG) mice to establish a patient-derived tumor xenograft (PDTX). MATERIALS AND
methodsA total of 15 patients with gynecologic tumors were enrolled into the present study. Among these patients, 12 patients had epithelial fallopian tube/ovarian/peritoneal cancer, one patient had metastatic ovarian cancer, and two patients had cervical cancer. Furthermore, among these patients, three patients were treated with puncture or microscopy biopsy, six patients underwent laparoscopic surgery, and six patients underwent robotic surgery. The tumor formation latency, tumor formation rate, tumor volume, tumor invasion and metastasis of the transplanted tumor were observed, the consistency of the PDTX model tumor tissue and patient's primary tumor tissue was compared by pathological H&E staining, and pharmacodynamics testing was performed.
resultsSeven of 15 PDTX models were successfully established, with a success rate of 46.7%. The tumor formation time ranged within 21-130 days, with a median tumor formation time of 73 days. The PDTX model maintained the differentiation, morphological and structural characteristics of tumor cells, and the pharmacodynamic test was completed in five patients.
conclusionThe PDTX model is highly consistent with the pathology of the patient's tumor, and can be used as a substitute for clinical patients to guide the accurate treatment and scientific research of gynecological tumors.
Indexed as
Identifiers
31312388PMC6614644W2988257179What 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.