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Abstract The preclinical platform landscape in oncology has radically changed in the last 15 years, mainly due to an increased ability to generate patient-derived models. Multiple 3D tumor cell cultures methods, either from established cell lines or from primary cultures, have been developed to assess the activity of therapeutic agents in vitro. These methods are strongly influenced by the experimental conditions, such as cell culture conditions, the presence of 3D supports like Matrigel, and the experimental design of the assay, such as the choice of the dose and the duration of the assay. The ability of these methods to predict drug efficacy in the patient relies not only in the optimization of the experimental settings, but also on the representativeness of the patient population, and on the prevention of model drifts due to clonal selection and/or tumor cell adaptation to culture conditions with passages. In this project, we aimed to develop an innovative 3D cell model platform that addresses all these experimental challenges. To do so, we took advantage of our low passage Tumorgraft platform, a bank of more than 1500 patient-derived xenografts (PDXs) well characterized at molecular and pharmacological level and highly representative of the patient population, to generate the Tumorgraft3D platform. We derived TumorGraft3D models from low passage PDXs, by using proprietary, indication-specific culture conditions. By keeping these models at low passage, we were able to avoid clonal drifts. Moreover, the use of indication specific media allowed the preservation of patient’s and PDX’s tumor histology, molecular traits at genetic, gene expression and proteomic level, and displayed proliferation rates that recapitulate those observed in the parental PDXs. So far, we have successfully developed over 100 models from breast, ovarian, prostate, NSCLC, colorectal and gastric indications, with success rates up to 90%. Ex-vivo testing of standard of care highlighted different response profiles in accordance with the molecular feature of these models. The tumor dissociation process and culture conditions optimized with PDXs were also used for the development of 3D cultures derived from patients’ samples. These data demonstrated that our 3D platform can integrate the complementarity of our PDX and patient-derived 3D platform, which lies in the possibility of evaluating test agent activity in the repeatable and reproducible setting provided by the patient-derived 3D models, as well as in models directly derived from patients with more heterogeneous and indication-specific establishment success rate, and throughput dependent on the amount of primary tumor material. Citation Format: Samaneh Kamali, Stefano Cairo, Fu-Ju Chou, Taylor Light, Mara Gilardi, Brandon Walling, Christine Baer, Hsiu-Wen Tsai, Abhay Andar, Karin Abarca-Heidemann, Maria Mancini. An innovative PDX and patient-derived 3D platform for improved translatability of new medical entities abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 4258.
Kamali et al. (Fri,) studied this question.