Since the first human cancer cell line, HeLa, was established in the early 1950s, there has been a steady increase in the number and tumor type of available cancer cell line models. Cancer cell lines have made significant contributions to the development of various chemotherapeutic agents. Recent advances in multi-omics technologies have facilitated detailed characterizations of the genomic, transcriptomic, proteomic, and epigenomic profiles of these cancer cell lines. An increasing number of studies employ the power of a cancer cell line panel to provide predictive biomarkers for targeted and cytotoxic agents, including those that are already used in clinical practice. Different types of statistical and machine learning algorithms have been developed to analyze the large-scale data sets that have been produced. However, much work remains to address the discrepancies in drug assay results from different platforms and the frequent failures to translate discoveries from cell line models to the clinic. Nevertheless, continuous expansion of cancer cell line panels should provide unprecedented opportunities to identify new candidate targeted therapies, particularly for the so-called "dark matter" group of cancers, for which pharmacologically tractable driver mutations have not been identified.
Keywords: Targeted therapy; biomarker; cancer genomics; personalized medicine.