This study evaluates the suitability of ovarian cancer cell lines as in vitro models by comparing their genomic profiles with those of ovarian tumors. The authors analyze 47 ovarian cancer cell lines and identify those that are genetically most similar to ovarian tumors, particularly high-grade serous ovarian cancer (HGSOC). They find significant differences in molecular profiles between commonly used ovarian cancer cell lines and HGSOC tumor samples, highlighting the need for more accurate cell line models. Several rarely used cell lines are identified as better models of HGSOC due to their closer resemblance to tumor profiles. The study also discusses the limitations of popular cell line models, such as SK-OV-3, A2780, OVCAR-3, CAOV3, and IGROV1, which lack key characteristics of HGSOC. The authors propose a set of criteria to evaluate the suitability of cell lines as models for HGSOC, emphasizing the importance of correlation with tumor copy-number profiles, low mutation rates, and absence of mutations in genes typically altered in other ovarian cancer subtypes. The findings suggest that genomic profiling can help bridge the gap between cell lines and tumors, improving the reliability of preclinical studies.This study evaluates the suitability of ovarian cancer cell lines as in vitro models by comparing their genomic profiles with those of ovarian tumors. The authors analyze 47 ovarian cancer cell lines and identify those that are genetically most similar to ovarian tumors, particularly high-grade serous ovarian cancer (HGSOC). They find significant differences in molecular profiles between commonly used ovarian cancer cell lines and HGSOC tumor samples, highlighting the need for more accurate cell line models. Several rarely used cell lines are identified as better models of HGSOC due to their closer resemblance to tumor profiles. The study also discusses the limitations of popular cell line models, such as SK-OV-3, A2780, OVCAR-3, CAOV3, and IGROV1, which lack key characteristics of HGSOC. The authors propose a set of criteria to evaluate the suitability of cell lines as models for HGSOC, emphasizing the importance of correlation with tumor copy-number profiles, low mutation rates, and absence of mutations in genes typically altered in other ovarian cancer subtypes. The findings suggest that genomic profiling can help bridge the gap between cell lines and tumors, improving the reliability of preclinical studies.