2024 World Conference on Lung Cancer (WCLC) - ePosters-EP.03G.04 High SLFN11 Expression Predicts Response but is not Required to Confer Sensitivity to Lurbinectedin

EP.03G.04 High SLFN11 Expression Predicts Response but is not Required to Confer Sensitivity to Lurbinectedin

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This study by Kedar Vaidya and colleagues from Jazz Pharmaceuticals investigates the role of Schlafen 11 (SLFN11) expression in predicting the efficacy of lurbinectedin, a chemotherapy drug approved for small cell lung cancer (SCLC) treatment. Lurbinectedin is a selective inhibitor of oncogenic transcription, leading to DNA damage and cancer cell apoptosis.<br /><br />The research aimed to determine if SLFN11 expression can predict the responsiveness of different cancer cell lines to lurbinectedin and if SLFN11 is needed for the drug's effectiveness. Findings showed that higher SLFN11 expression in cancer cell lines and patient-derived organoids correlates with increased sensitivity to lurbinectedin, evidenced by lower IC50 values. SLFN11 expression can be assessed through RNA and protein levels, which are significantly correlated.<br /><br />However, knocking down SLFN11 did not reduce sensitivity to lurbinectedin, suggesting SLFN11 is a predictive biomarker but not essential for drug action, indicating that other factors may influence drug response. While some low SLFN11-expressing models responded well to the drug, further investigations are required to identify additional biomarkers that can predict therapeutic responses.<br /><br />In vivo experiments with SCLC xenografts showed that tumors with high SLFN11 expression had a greater response to lurbinectedin treatment, affirming the data from in vitro studies. The study concludes the necessity for more comprehensive proteomic and genomic studies to understand the molecular determinants of lurbinectedin sensitivity better.<br /><br />Supported by Jazz Pharmaceuticals, this research suggests the potential of SLFN11 as a biomarker for treatment planning, emphasizing the need for more extensive biomarker discovery to guide personalized therapy for cancer patients.

Asset Subtitle

Kedar Vaidya

Meta Tag

Speaker Kedar Vaidya

Topic Tumor Biology – Translational Biology

Keywords

SLFN11

lurbinectedin

small cell lung cancer

biomarker

oncogenic transcription

cancer cell lines

xenografts

proteomic studies

genomic studies

personalized therapy