People William Leenders Tumor targeting

Tumor targeting developing innovative nanomedicines

This research group's interest is to use information on the molecular cancer biology in individual patients that determines clinical behavior, response and non-response to therapies and contributes to the development of therapy resistance.

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Tumor targeting developing innovative nanomedicines

Our research interest is to use information on the molecular cancer biology in individual patients that determines clinical behavior, response and non-response to therapies and contributes to the development of therapy resistance. In our research group we use surgically-derived clinical tumor material, patient-derived cell lines and orthotopic xenograft models as tools. Using a novel technique of targeted RNA next generation sequencing, in combination with computational biology, we are able to establish a reliable molecular diagnosis and  a prognosis for individual patients. The aim is to translate the results of this test into better personalized cancer therapies/patient stratification.
 
A second line of preclinical research is based on targeted delivery of nanomedicines to cancer. We have developed site directed conjugation protocols for llama single domain antibodies (VHHs) with full retention of biological activity, and showed that VHHs, conjugated to photosensitizers allow targeted photodynamic therapy (tPDT). The great advantage of tPDT  as compared to conventional therapies is that it induces acute cell death via cell membrane peroxidation in a specific and selective fashion and therefore precludes development of treatment resistance.

Research group leader

William Leenders PhD

+31 (0)24 36 14 89
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Aims of this research group

The aim of the tumor targeting research group is two-fold:

  • to translate novel biomarkers, identified by RNA sequencing in clinical cancers, into novel treatment modalities that are tested in
  • to develop novel targeted nanomedicine-based treatment concepts that are tested in cell lines and preclinical cancer models

Social media research group leader

Team

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