1137-CTDPathSim2.0: Mapping of Cell Lines to Patient Tumors
This study introduces CTDPathSim2.0, a computational framework designed to identify which laboratory cell lines most accurately represent individual patient tumors. Researchers developed this tool because cell lines often undergo genetic changes in vitro, causing them to deviate from the biology of actual human cancers. By integrating multi-omics data—including gene expression, DNA methylation, and copy number aberrations—the pipeline calculates a similarity score that accounts for immune cell presence and biological pathway activities. Results demonstrate that this method effectively…
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