Patient-Derived Xenograft Models for Cancer Stem Cell Research
Received: 01-Jan-2025 / Manuscript No. acp-25-162434 / Editor assigned: 03-Jan-2025 / PreQC No. acp-25-162434 / Reviewed: 17-Jan-2025 / QC No. acp-25-162434 / Revised: 24-Jan-2025 / Manuscript No. acp-25-162434 / Published Date: 31-Jan-2025 DOI: 10.4172/2472-0429.1000266
Abstract
Patient-derived xenograft (PDX) models have emerged as a powerful tool in cancer research, providing a clinically relevant platform for studying cancer stem cells (CSCs). These models retain the histological and genetic characteristics of the original tumors, allowing researchers to investigate tumor heterogeneity, treatment resistance, and metastasis. PDX models enable the identification of CSC-specific markers and pathways, facilitating the development of targeted therapies. Furthermore, they serve as an essential preclinical model for evaluating novel therapeutics and predicting patient responses. This review discusses the significance of PDX models in CSC research, their advantages and limitations, and their potential in advancing precision oncology.
Keywords
Cancer stem cells; CSCs; Tumor heterogeneity; Treatment resistance; Metastasis; Preclinical models; Targeted therapy; Precision oncology.
Introduction
Cancer stem cells (CSCs) are a subpopulation of tumor cells with self-renewal, differentiation, and tumor-initiating capabilities, playing a critical role in tumor progression, metastasis, and therapy resistance [1]. Understanding CSC biology is essential for developing effective therapeutic strategies that target these resilient cells. However, studying CSCs in conventional in vitro models and standard cell line-based xenografts often fails to capture the complexity and heterogeneity of patient tumors [2].
Patient-derived xenograft (PDX) models have emerged as a powerful preclinical tool in cancer research, offering a more clinically relevant system for studying CSCs. These models are established by implanting primary patient tumor samples into immunodeficient mice, preserving the histological architecture, genetic profile, and tumor microenvironment of the original malignancy [3]. Unlike traditional cell lines, PDX models closely mimic the patient’s tumor biology, making them highly valuable for investigating CSC-driven tumor growth, resistance mechanisms, and potential therapeutic targets. In this paper, we discuss the role of PDX models in CSC research, their advantages and limitations, and their contribution to advancing precision oncology. By leveraging PDX models, researchers can gain deeper insights into CSC biology and develop more effective treatments aimed at eradicating these tumor-initiating cells [4].
Discussion
Patient-derived xenograft (PDX) models have significantly advanced cancer stem cell (CSC) research by providing a biologically relevant platform that retains key characteristics of human tumors [5]. These models allow for the study of CSC heterogeneity, tumor evolution, and resistance mechanisms, which are critical challenges in cancer treatment [6]. One of the major advantages of PDX models in CSC research is their ability to maintain the tumor’s original histopathological and genetic features across multiple passages. This fidelity makes them highly valuable for studying CSC-specific markers and pathways that contribute to tumor initiation and progression. Additionally, PDX models enable researchers to test novel CSC-targeted therapies in a setting that closely mirrors clinical conditions, improving the predictive value of preclinical studies [7].
Despite these advantages, PDX models also present certain limitations. The requirement for immunodeficient mice restricts the ability to study interactions between CSCs and the immune system, which plays a crucial role in tumor progression. Furthermore, establishing and maintaining PDX models is time-consuming and costly, limiting their widespread application in high-throughput drug screening [8]. Additionally, some tumors fail to engraft successfully, which may introduce selection bias in CSC studies. Nevertheless, emerging advancements such as humanized mouse models and patient-derived organoid cultures are addressing some of these limitations, making PDX models even more relevant in CSC research [9]. By integrating PDX models with advanced genomic, transcriptomic, and single-cell analysis techniques, researchers can gain a more comprehensive understanding of CSC biology and therapeutic resistance. Overall, PDX models continue to serve as an indispensable tool for CSC research, providing new insights into tumor initiation, progression, and drug resistance. Their role in preclinical testing is crucial for developing precision oncology strategies aimed at eradicating CSCs and improving patient outcomes [10].
Conclusion
Patient-derived xenograft (PDX) models have revolutionized cancer stem cell (CSC) research by providing a biologically relevant and clinically representative platform for studying tumor heterogeneity, therapy resistance, and metastasis. These models preserve the genetic and histological integrity of patient tumors, making them invaluable for identifying CSC-specific markers and evaluating novel therapeutic approaches. Despite their limitations, including the lack of an intact immune system and the challenges associated with cost and engraftment efficiency, PDX models remain a gold standard for preclinical cancer research. Advances such as humanized mouse models and patient-derived organoid systems are helping to overcome these challenges, further enhancing the utility of PDX models in CSC studies. By integrating PDX models with cutting-edge molecular and computational approaches, researchers can gain deeper insights into CSC biology, ultimately leading to the development of more effective, targeted therapies. As precision oncology continues to evolve, PDX models will remain instrumental in bridging the gap between basic cancer research and clinical applications, improving treatment strategies and patient outcomes.
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Citation: Nag H (2025) Patient-Derived Xenograft Models for Cancer Stem Cell Research Adv Cancer Prev 9: 266. DOI: 10.4172/2472-0429.1000266
Copyright: © 2025 Nag H. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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