• Biomarkers correlated to tumoral sensitivity to AsiDNA™, supporting personalized medicine approaches
  • A selection tool to screen patients in future clinical development of AsiDNA™ based on these predictive biomarkers of response


Paris (France), January 3, 2019 – 6.00 pm CET – Onxeo S.A. (Euronext Paris, NASDAQ Copenhagen: ONXEO), (“Onxeo” or “the Company”), a clinical-stage biotechnology company specializing in the development of innovative drugs in oncology, in particular against rare or resistant cancers, today announces the identification of predictive biomarkers for AsiDNA™, its first-in-class non-targeted DNA Damage Response (DDR) inhibitor, which enables personalized medicine approaches.


Judith Greciet, Chief Executive Officer of Onxeosaid“The development of AsiDNA™ is undergoing a strong momentum both in terms of preclinical and clinical activities. Identifying predictive biomarkers is an important step forward that will assist in the design of the next phases of the clinical development of AsiDNA™. Indeed, these biomarkers will make possible an upstream selection of the patients with a better sensitivity to treatment with AsiDNA™, which will maximize the likelihood of success for upcoming clinical studies as well as enable a personalized medicine approach for these patients over time. We now have a robust and state-of-the-art set of preclinical and clinical data for this particularly promising drug candidate in the field of DDR. The identified biomarkers are important components in the design of future studies and will be included as soon as the next phase 1b/2 combination study that we expect to initiate in the coming weeks, thanks to the favorable intermediate results of activity and tolerance in the ongoing DRIIV-1 study. Each of these advances in our developments significantly enhances the value of AsiDNA™ and our R&D assets.”

Preclinical studies identified predictive biomarkers for patient selection in upcoming studies of AsiDNA™

Extensive tests investigated AsiDNA™ sensitivity signature using bioinformatics analysis from transcriptomic experiments, validated this signature in vitro on multiple cell lines and then analyzed the genes presenting an expression profile highly correlated with sensitivity to AsiDNA™.

These studies showed that sensitivity to AsiDNA™ is correlated with the level of DNA repair gene expression in the tumor and identified several tumor genes for which the level of expression is the most correlated to AsiDNA™ sensitivity. A low level of these genes expression in a patient’s tumor greatly increases the likelihood that the patient will respond to treatment with AsiDNA™. As a result, analysis of these genes will be used to select the patients with the highest sensitivity to treatment and thus the greater probability of response in upcoming trials.

Use of such predictive biomarkers is part of the best practices in clinical trial design and in treatment (personalized medicine) today. During clinical development, their use greatly reduces risks and maximizes the chances of success. In clinical practice, prior assessment via predictive biomarkers allows for personalized care that optimizes the patient’s chances by selecting the most appropriate treatment for a given patient.