Abstract 4256: Functional analysis for cancer precision medicine using patient-derived 2D and 3D cell models

Background: Preclinical models provide an essential tool to study both cancer biology with particular relevance to identifying appropriate therapies and new targets. Both Patient-derived xenografts and 3D methods require significant time for the necessary amplification of the tumor cells, which limits clinical utility. Even classical 2D cultures suffer from their long time requirements for establishing a cell line with a low efficiency (1-30%). Conventional cancer cell lines usually fail to reflect the complex genotypes and phenotypes of the corresponding primary tumor. Recently, we described the use feeder cells and a ROCK inhibitor to induce the conditional reprogramming (CR) of adult epithelial cells into a basal or stem-like state. The induction of these CR cells is reversible, and the removal of feeders and ROCK inhibitor, coupled with their placement in environments that mimick their native environment (Matrigel, air-liquid interface (ALI), and the renal capsule in mice) allows cells to differentiate normally. Importantly, the CR technology can generate 2×106 cells in a week from small biopsies, and can generate cultures from cryopreserved tissue and from fewer than four viable cells. A recent study utilized the CR method to initiate cultures from CT-guided lung biopsies and identify combination of therapies (Science 2014). Three recent reviews in Nature series highlighted CR method as one of the next-generation patient-derived cancer models (Nat Rev Clin Oncol, 2014, Nat Rev Genetics and Nat Rev Cancer 2015). Primary goal: The clinical utility and standard protocols for generating patient CR cultures. We therefore initiated study to examine whether CR cultures reflected the biology and genotype of the original tumor and whether cultures might be used to predict clinical responses. Procedures and Results: We first worked out standard protocols for clinical sampling, storage, shipping, freezing and the preparation of conditioned medium. CR methods were then used to generate matched cultures from both tumor cells and adjacent normal cells from patients with prostate cancer or lung cancer. CR cultures were established efficiently from these tumors (>95% for prostate and lung cancer CRCs). Following the rapid establishment of CR cultures, they were then transferred 3D cultures. The data with Matrigel 3D and (ALI) demonstrated that CR cells reexpressed cell specific markers and were well-differentiated. We also characterized them for their growth properties, induction of tumors in immunodeficient mice, karyotype, and their exome and transcriptome profile. Conclusion: CR cells, coupled with sequential 3D culture conditions, appears to provide optimal conditions for inducing the differentiation of normal cells and for differentiating normal from tumor cells. Finally, this cell-based approach should be useful for defining the functional heterogeneity of the respective primary tumors and for evaluating appropriate therapies. Citation Format: Xuefeng Liu, Ewa Krawczyk, Ogla Timofeeva, Nancy Palechor-Ceron, Aleksandra Dakic, Vera Simic, Bhaskar Kallakury, Anatoly Dritschilo, Richard Schlegel. Functional analysis for cancer precision medicine using patient-derived 2D and 3D cell models. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4256.