Patrizii Michele, Bartucci Monica, Pine Sharon R, Sabaawy Hatem E
Graduate Program in Cellular and Molecular Pharmacology, RBHS-Robert Wood Johnson Medical School, Piscataway, NJ, United States.
Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, United States.
Front Oncol. 2018 Feb 12;8:23. doi: 10.3389/fonc.2018.00023. eCollection 2018.
Despite substantial effort and resources dedicated to drug discovery and development, new anticancer agents often fail in clinical trials. Among many reasons, the lack of reliable predictive preclinical cancer models is a fundamental one. For decades, immortalized cancer cell cultures have been used to lay the groundwork for cancer biology and the quest for therapeutic responses. However, cell lines do not usually recapitulate cancer heterogeneity or reveal therapeutic resistance cues. With the rapidly evolving exploration of cancer "omics," the scientific community is increasingly investigating whether the employment of short-term patient-derived tumor cell cultures (two- and three-dimensional) and/or patient-derived xenograft models might provide a more representative delineation of the cancer core and its therapeutic response. Patient-derived cancer models allow the integration of genomic with drug sensitivity data on a personalized basis and currently represent the ultimate approach for preclinical drug development and biomarker discovery. The proper use of these patient-derived cancer models might soon influence clinical outcomes and allow the implementation of tailored personalized therapy. When assessing drug efficacy for the treatment of glioblastoma multiforme (GBM), currently, the most reliable models are generated through direct injection of patient-derived cells or more frequently the isolation of glioblastoma cells endowed with stem-like features and orthotopically injecting these cells into the cerebrum of immunodeficient mice. Herein, we present the key strengths, weaknesses, and potential applications of cell- and animal-based models of GBM, highlighting our experience with the glioblastoma stem-like patient cell-derived xenograft model and its utility in drug discovery.
尽管在药物研发方面投入了大量的精力和资源,但新型抗癌药物在临床试验中常常失败。在诸多原因中,缺乏可靠的临床前癌症预测模型是一个根本原因。几十年来,永生化癌细胞培养一直被用于为癌症生物学和探索治疗反应奠定基础。然而,细胞系通常无法概括癌症的异质性,也无法揭示治疗耐药线索。随着癌症“组学”研究的迅速发展,科学界越来越多地研究使用短期患者来源的肿瘤细胞培养物(二维和三维)和/或患者来源的异种移植模型是否能更具代表性地描绘癌症核心及其治疗反应。患者来源的癌症模型允许在个性化基础上整合基因组数据和药物敏感性数据,目前代表了临床前药物开发和生物标志物发现的终极方法。正确使用这些患者来源的癌症模型可能很快会影响临床结果,并允许实施量身定制的个性化治疗。在评估多形性胶质母细胞瘤(GBM)治疗的药物疗效时,目前,最可靠的模型是通过直接注射患者来源的细胞或更常见的是分离具有干细胞样特征的胶质母细胞瘤细胞并将这些细胞原位注射到免疫缺陷小鼠的大脑中产生的。在此,我们介绍了基于细胞和动物的GBM模型的关键优势、劣势和潜在应用,重点介绍了我们在胶质母细胞瘤干细胞样患者细胞来源的异种移植模型方面的经验及其在药物发现中的效用。