Transcriptome signatures for the identification of bevacizumab responders in ovarian cancer.
- Open access
A specific gene expression signature predicts improved survival with bevacizumab in ovarian cancer patients, with overexpression linked to a hazard ratio of 0.41.
- Why it matters: Identifying reliable biomarkers for bevacizumab response is crucial because current clinical criteria do not guide patient selection, limiting personalized treatment options.
- What they did: Researchers analyzed 244 RNA-seq samples using machine learning to find expression signatures associated with treatment benefit, then validated findings across multiple datasets totaling over 1,000 samples.
- The result: The identified signature correlates with better overall survival in bevacizumab-treated patients and suggests biological links to stemness features, paving the way for improved predictive tools and understanding ovarian cancer heterogeneity.