RESPONSIFY Objectives

 RESPONSIFY intends to prove the hypothesis that a predictive biomarker approach will be able to distinguish responders from non-responders and will therefore spare patients from unnecessary toxicities. This will help to significantly reduce costs in the European healthcare system and improve prognosis and quality of life for women diagnosed with breast cancer. Using new genome-wide based techniques, we will select and validate candidate biomarkers which have the potential to predict response to therapy and affect clinical outcome. 

The RESPONSIFY approach is based on the following strategical issues:

A clearly defined marker discovery-training-validation-approach will be the backbone of RESPONSIFY to reach a high level of evidence in order to achieve clinical acceptance and commercial implementation by the SME partners. 

RESPONSIFY discovery phase and validation phase:

Two different strategies of biomarker discovery will be combined:

  • identification of new resistance pathways and biomarkers via whole genome siRNA screening as well as
  • in depth molecular characterization using established and innovative genome based methodologies such as genome-wide epigenetics, gene and exon expression analysis and also next generation sequencing, splice arrays, in-situ proteomics and kinome arrays.

 Biomarker validation is linked to established procedures for analysis of formalin-fixed paraffin-embedded (FFPE) tissue.
This type of tissue is available for each breast cancer patient, in contrast to fresh-frozen tissue that is currently not routine in many hospital settings and limited to mainly neoadjuvant studies.    

A simple, FFPE based diagnostic system for response prediction is preferred by clinicians. In the RESPONSIFY project, we will attempt to discover from biological information obtained concerning response prediction with respect to different breast cancer subtypes and two different targeted therapies into biomarker tests to facilitate individualised treatment tailoring in the clinical setting. These tests will be developed for commercialisation using the expertise of the involved SMEs and industrial partners.

A web-based EDC system for integration and processing data from the sites as well as the biomarker estimation laboratories and management of the individual study will be developed to reach the overall aim of a better definition of treatment populations for clinical trials by standardised integration of clinical trial data and biomarker results.

The identified biomarker IVD test will be finally implemented into clinical trial protocols using the expertise of the clinical study groups.

Health economic characteristics of combined testing and treatment strategies will be determined to inform decision makers, using state-of-the-art cost-utility analysis. Optimising the use of current therapy options and avoiding treatments, patients will predictably not respond to, may improve cost-utility parameters to levels acceptable for most health systems. In fact, a potential for substantial cost-savings through the use of predictive testing has already been demonstrated.