ArticleCommunications biology2024
Identifying cell lines across pan-cancer to be used in preclinical research as a proxy for patient tumor samples.
Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- DiM2-DRP: Dual-Input Multi-View Dynamic Contrastive Learning Framework for Drug Response Prediction.Interdisciplinary sciences, computational life sciences · 2026Article
- Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.iScience · 2026Article
- Multi-omics evaluation of cell lines as models for metastatic prostate cancer.Communications biology · 2026Article
- A network model for patient-derived drug response in breast cancer integrating multi-omics datasets.bioRxiv : the preprint server for biology · 2025Article
- A Truncated Mutation of TP53 Promotes Chemoresistance in Tongue Squamous Cell Carcinoma.International journal of molecular sciences · 2025Article
- Intraline genomic heterogeneity of the triple-negative breast cancer MDA-MB-231-luc-GFP cell line.Computational and structural biotechnology journal · 2025Article
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Authors and funding
2 authors.
Funding
Abstract
In pre-clinical trials of anti-cancer drugs, cell lines are utilized as a model for patient tumor samples to understand the response of drugs. However, in vitro culture of cell lines, in general, alters the biology of the cell lines and likely gives rise to systematic differences from the tumor samples' genomic profiles; hence the drug response of cell lines may deviate from actual patients' drug response. In this study, we computed a similarity score for the selection of cell lines depicting the close and far resemblance to patient tumor samples in twenty-two different cancer types at genetic, genomic, and epigenetic levels integrating multi-omics datasets. We also considered the presence of immune cells in tumor samples and cancer-related biological pathways in this score which aids personalized medicine research in cancer. We showed that based on these similarity scores, cell lines were able to recapitulate the drug response of patient tumor samples for several FDA-approved cancer drugs in multiple cancer types. Based on these scores, several of the high-rank cell lines were shown to have a close likeness to the corresponding tumor type in previously reported in vitro experiments.
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