Role of Patient-Derived Models of Cancer in Translational Oncology

SIMPLE SUMMARY: It was found that long-established tumor-derived cell lines do not adequately reproduce drug sensitivity and behavior of a real human cancers. Therefore, more reliable tumor models that recapitulate the heterogeneity and patho-physiology of patient tumors are under development. The aim of our review is to describe the current patient-derived models of cancer, discuss their advantages and disadvantages, and provide information about clinical trials and inventions in this field. This work provides a comprehensive overview of the strong and weak sides of patient-derived models, as well as the latest achievements in data collection, creation of repositories and biobanks. ABSTRACT: Cancer is a heterogeneous disease. Each individual tumor is unique and characterized by structural, cellular, genetic and molecular features. Therefore, patient-derived cancer models are indispensable tools in cancer research and have been actively introduced into the healthcare system. For instance, patient-derived models provide a good reproducibility of susceptibility and resistance of cancer cells against drugs, allowing personalized therapy for patients. In this article, we review the advantages and disadvantages of the following patient-derived models of cancer: (1) PDC—patient-derived cell culture, (2) PDS—patient-derived spheroids and PDO—patient-derived organoids, (3) PDTSC—patient-derived tissue slice cultures, (4) PDX—patient-derived xenografts, humanized PDX, as well as PDXC—PDX-derived cell cultures and PDXO—PDX-derived organoids. We also provide an overview of current clinical investigations and new developments in the area of patient-derived cancer models. Moreover, attention is paid to databases of patient-derived cancer models, which are collected in specialized repositories. We believe that the widespread use of patient-derived cancer models will improve our knowledge in cancer cell biology and contribute to the development of more effective personalized cancer treatment strategies.