The integration of multi-omics technologies and precision oncology has transformed cancer research in the twenty-first century, demanding model systems that are both experimentally tractable and molecularly representative. Despite the emergence of complex models such as organoids and patient-derived xenografts (PDXs), cancer cell lines remain indispensable due to their scalability, genetic accessibility, and compatibility with high-throughput applications. Cell lines have played a central role in the functional interpretation of omics data, the identification of therapeutic vulnerabilities, and the development of pharmacogenomic resources such as the Cancer Dependency Map (DepMap) and ProCan-DepMapSanger. Recent advances in pharmaco-proteogenomics have further leveraged large, annotated cell line panels to uncover molecular correlates of drug response and nominate candidate biomarkers. Nonetheless, long-established cell lines suffer from limitations including genomic drift, lack of clinical annotation, and underrepresentation of rare cancer subtypes—factors that compromise reproducibility and translational utility. To address these challenges, a new generation of patient-derived cancer cell lines must be genomically validated, clinically annotated, and deposited in curated biorepositories with standardized metadata. Such efforts will reinforce the role of cell lines as foundational tools in data-driven cancer biology, ensuring their continued relevance in an era of systems oncology and precision therapeutics.