AUTHOR=Fu Yatian , Khoo Bee Luan , Lim Chwee Teck TITLE=Advancements and challenges in culturing patient-derived cancer cells for personalized therapeutics JOURNAL=Frontiers in Lab on a Chip Technologies VOLUME=Volume 4 - 2025 YEAR=2025 URL=https://www.frontiersin.org/journals/lab-on-a-chip-technologies/articles/10.3389/frlct.2025.1663420 DOI=10.3389/frlct.2025.1663420 ISSN=2813-3862 ABSTRACT=Patient-derived cancer cells (PDCCs) have emerged as a key strategy for advancing personalized cancer treatment. Unlike traditional cancer cell lines, PDCCs retain the genetic and phenotypic characteristics of the patient’s original tumor and can more accurately reflect tumor biology. This review explores recent advances in methods for culturing PDCCs, highlighting the role of these models in drug discovery and high-throughput screening of personalized therapeutic options. By establishing living models directly from patient tumors, PDCCs can more faithfully recapitulate tumor heterogeneity and microenvironmental features than traditional cell lines. These cultures bridge laboratory research and clinical reality, allowing functional testing of patients' cancer cells. Despite the promise of PDCCs, their culture remains fraught with challenges, including the extremely low number of cancer cells that can be obtained, difficulty maintaining tumor heterogeneity, low culture initiation success rates, and ethical considerations for using patient tissues. In addition, controversy remains regarding the reproducibility of results between different laboratories and patient samples. By examining the field’s current state, this review identifies gaps in the application of PDCCs, such as limited modeling capabilities for specific tumor types and the lack of comprehensive, scalable protocols for broad clinical use. This article discusses future directions, including integration with advanced microengineering and AI-driven analysis, which have the potential to overcome existing limitations and optimize PDCCs-based therapeutic strategies. PDCCs are expected to transform the future of cancer treatment as they ultimately provide more accurate drug testing and personalized medicine models.