Cancers · 2021 · 24 citations · 57 references
MedicineMolecular BiologyOncologyCancer GeneticsMolecular OncologyTumor PathologyCancer GenomicsCancer Molecular PathologyMalignant NeoplasmsMolecular Classification Of TumorsMolecular Tumor ProfilingOvarian CancerCancer Cell Line ModelsCell Line-derived Xenograft ModelsGenetic Drift DetectionGenetic Drift EffectsGenetic Drift ModelingHigh-grade Serous Ovarian CarcinomaOvarian Cancer HistopathologySerous Ovarian Tumors
(1) Background. PDX models have become the preferred tool in research laboratories seeking to improve development and pre-clinical testing of new drugs. PDXs have been shown to capture the cellular and molecular characteristics of human tumors better than simpler cell line-based models. More recently, however, hints that PDXs may change their characteristics over time have begun to emerge, emphasizing the need for comprehensive analysis of PDX evolution. (2) Methods. We established a panel of high-grade serous ovarian carcinoma (HGSOC) PDXs and developed and validated a 300-SNP signature that can be successfully utilized to assess genetic drift across PDX passages and detect PDX contamination with lymphoproliferative tissues. In addition, we performed a detailed histological characterization and functional assessment of multiple PDX passages. (3) Results. Our data show that the PDXs remain largely stable throughout propagation, with marginal genetic drift at the time of PDX initiation and adaptation to mouse host. Importantly, our PDX lines retained the major histological characteristics of the original patients' tumors even after multiple passages in mice, demonstrating a strong concordance with the clinical responses of their corresponding patients. (4) Conclusions. Our data underline the value of defined HGSOC PDXs as a pre-clinical tumor model.
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