Systematic Analysis of Genetic and Pathway Determinants of Eribulin Sensitivity across 100 Human Cancer Cell Lines from the Cancer Cell Line Encyclopedia (CCLE)

• Published in: Cancers Vol. 14; no. 18; p. 4532
• Main Authors: Sachdev, Pallavi, Ronen, Roy, Dutkowski, Janusz, Littlefield, Bruce A
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2022; MDPI
• Subjects: Binding sites; Biomarkers; Breast cancer; Cancer; Cancer cells; CD70 antigen; Cell lines; Cytotoxicity; Dosage and administration; Drug dosages; EphA2 protein; eribulin; Eribulin mesylate; Gene expression; Genetic analysis; Genetic aspects; Health aspects; Hypotheses; Hypothesis testing; Iroquois protein; Laboratories; Liposarcoma; Natural products; Paclitaxel; predictive biomarkers; Propagation; Ratios; Regression analysis; Statistical analysis; Tumor cell lines; Vinorelbine; United States; Beijing China; United States > US; China
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers14184532

Eribulin, a natural product-based microtubule targeting agent with cytotoxic and noncytotoxic mechanisms, is FDA approved for certain patients with advanced breast cancer and liposarcoma. To investigate the feasibility of developing drug-specific predictive biomarkers, we quantified antiproliferative activities of eribulin versus paclitaxel and vinorelbine against 100 human cancer cell lines from the Cancer Cell Line Encyclopedia, and correlated results with publicly available databases to identify genes and pathways associated with eribulin response, either uniquely or shared with paclitaxel or vinorelbine. Mean expression ratios of 11,985 genes between the most and least sensitive cell line quartiles were sorted by p-values and drug overlaps, yielding 52, 29 and 80 genes uniquely associated with eribulin, paclitaxel and vinorelbine, respectively. Further restriction to minimum 2-fold ratios followed by reintroducing data from the middle two quartiles identified 9 and 13 drug-specific unique fingerprint genes for eribulin and vinorelbine, respectively; surprisingly, no gene met all criteria for paclitaxel. Interactome and Reactome pathway analyses showed that unique fingerprint genes of both drugs were primarily associated with cellular signaling, not microtubule-related pathways, although considerable differences existed in individual pathways identified. Finally, four-gene (C5ORF38, DAAM1, IRX2, CD70) and five-gene (EPHA2, NGEF, SEPTIN10, TRIP10, VSIG10) multivariate regression models for eribulin and vinorelbine showed high statistical correlation with drug-specific responses across the 100 cell lines and accurately calculated predicted mean IC50s for the most and least sensitive cell line quartiles as surrogates for responders and nonresponders, respectively. Collectively, these results provide a foundation for developing drug-specific predictive biomarkers for eribulin and vinorelbine.