van der Graaff Denise, Seghers Sofie, Vanclooster Pieterjan, Deben Christophe, Vandamme Timon, Prenen Hans
Department of Medical Oncology, University Hospital Antwerp, 2650 Edegem, Belgium.
Center for Oncological Research (CORE), University of Antwerp, 2610 Wilrijk, Belgium.
Cancers (Basel). 2024 Jul 26;16(15):2671. doi: 10.3390/cancers16152671.
Colorectal cancer (CRC) remains a significant health burden globally, being the second leading cause of cancer-related mortality. Despite significant therapeutic advancements, resistance to systemic antineoplastic agents remains an important obstacle, highlighting the need for innovative screening tools to tailor patient-specific treatment. This review explores the application of patient-derived tumor organoids (PDTOs), three-dimensional, self-organizing models derived from patient tumor samples, as screening tools for drug resistance in CRC. PDTOs offer unique advantages over traditional models by recapitulating the tumor architecture, cellular heterogeneity, and genomic landscape and are a valuable ex vivo predictive drug screening tool. This review provides an overview of the current literature surrounding the use of PDTOs as an instrument for predicting therapy responses in CRC. We also explore more complex models, such as co-cultures with important stromal cells, such as cancer-associated fibroblasts, and organ-on-a-chip models. Furthermore, we discuss the use of PDTOs for drug repurposing, offering a new approach to identify the existing drugs effective against drug-resistant CRC. Additionally, we explore how PDTOs serve as models to gain insights into drug resistance mechanisms, using newer techniques, such as single-cell RNA sequencing and CRISPR-Cas9 genome editing. Through this review, we aim to highlight the potential of PDTOs in advancing our understanding of predicting therapy responses, drug resistance, and biomarker identification in CRC management.
结直肠癌（CRC）仍是全球一项重大的健康负担，是癌症相关死亡的第二大主要原因。尽管在治疗方面取得了重大进展，但对全身抗肿瘤药物的耐药性仍然是一个重要障碍，这凸显了需要创新的筛查工具来定制针对患者的治疗方案。本综述探讨了患者来源的肿瘤类器官（PDTO）的应用，这是一种从患者肿瘤样本中获得的三维自组织模型，作为CRC耐药性的筛查工具。与传统模型相比，PDTO具有独特的优势，它能够重现肿瘤结构、细胞异质性和基因组格局，是一种有价值的体外预测性药物筛选工具。本综述概述了围绕使用PDTO作为预测CRC治疗反应的工具的当前文献。我们还探讨了更复杂的模型，例如与重要的基质细胞（如癌症相关成纤维细胞）的共培养模型以及芯片器官模型。此外，我们讨论了将PDTO用于药物重新定位，为识别对耐药性CRC有效的现有药物提供了一种新方法。此外，我们探讨了PDTO如何作为模型，利用单细胞RNA测序和CRISPR-Cas9基因组编辑等新技术深入了解耐药机制。通过本综述，我们旨在突出PDTO在推进我们对CRC管理中预测治疗反应、耐药性和生物标志物识别的理解方面的潜力。
