​by Ine Koeken

Neuroblastoma is the most common solid tumor outside the brain of very young children. A substantial part of neuroblastoma patients presents with high-risk neuroblastoma disease. In fact, these children have a poor prognosis, do not respond to therapy or even relapse. Therefore, there is an urgent need to find novel treatment strategies. Our lab discovered a new approach to kill aggressive therapy-resistant neuroblastoma cells in mice by inducing ferroptosis. By using nanoparticles, the lab was able to minimize side effects and enhance tumor targeting. However, to deal with differential ferroptosis responsiveness in these heterogenous tumors, we aimed at reconditioning high-risk neuroblastoma cells to a ferroptosis-sensitive state using nanoparticles that can unleash the major ferroptotic brake(s). We successfully developed a sensitizing strategy targeting the lipid composition of the cancer cells using poly-unsaturated fatty acid (PUFA) containing lipid nanoparticles, which are similar to COVID-19 vaccines. To maximize PUFA incorporation in membrane phospholipids, we also identified lipid remodelling compounds that we are encapsulating in these lipid nanoparticles. These ferroptosis-sensitizing nanoparticles are currently tested in cell- and patient-derived high-risk neuroblastoma mouse models. Together, this will provide a steppingstone to precision oncology by increasing the success rate of ferroptosis targeting as a cancer therapy.

Ine Koeken¹, Magali Walravens¹, Bianka Golba², Iuliana Vintea¹, Ali Talebi³, Jonas Deshair³, Johan Swinnen³, Frank Speleman⁴, Bruno de Geest², Behrouz Hassannia^1,5,6, Tom Vanden Berghe^1,5,6,7

¹Department of Biomedical Sciences | University of Antwerp| Antwerp, Belgium
²Department of Pharmaceutics | Ghent University | Ghent, Belgium
³Department of Oncology | KU Leuven | Leuven, Belgium
⁴Department of Biomolecular Medicine |Ghent University |Ghent, Belgium
⁵VIB-UGent Center for Inflammation Research | Ghent, Belgium
⁶Department of Biomedical Molecular Biology | Ghent University |Ghent, Belgium
⁷Infla-Med, Centre of Excellence | University of Antwerp | Antwerp, Belgium

by Edgar Cardenas

ORGANOID models, taken from patient tissues and measured in live cell imaging platforms, are an emerging technology that creates numerous opportunities to improve cancer diagnosis and treatment. As with any new technology, challenges exist in making full use of these models. Including the ability to effectively quantify the growth and viability of 3D tissue cultures in a high throughput format. A key feature of our measurement methodology is the use of BRIGHTFIELD IMAGING; a low cost, nontoxic, highly repeatable and massively underutilized microscopic technique that offers the greater amount of information, but which requires advanced computer vision to make full use of.  Analysis implemented with convolutional neural networks and statistical pattern recognition, not only improve correlation to clinical responses but also uncover novel characteristics such as tumor heterogeneity and response uniformity for the next generation of THERAPY SCREENING.

by Marthe Van Overbeke

The current state-of-the art advocates for a biopsychosocial rehabilitation approach for persistent pain after breast cancer treatment. Within this approach pain science education is combined with promotion of an active lifestyle based on self-regulation techniques. We argue for testing an innovative eHealth selfmanagement support program for this purpose. The assumption is that this delivery mode reduces barriers to pain self-management support, through bringing timely support near to people, creating a safe environment as opposed to hospital settings, providing a multidimensional support model taking into account the biopsychosocial needs of patients, and lowering costs. This program can provide patients with the knowledge, proactive, cognitive and self-management skills to master their situation and journey towards less pain and pain-related disability and participation in normal life again. Therefore, the general aim of the proposed project is to investigate the effectiveness of an eHealth self-management support program for pain-related disability (I) in breast cancer survivors with persistent pain (P). The program makes use of an innovative chatbot format for delivering pain science education and motivating and monitoring physical activity. The eHealth program is automated and personalized using comprehensive decisiontree-based algorithms in order to promote pain self-management support. The primary scientific objective of the study is to determine the effectiveness of this eHealth self-management support program for persistent pain after breast cancer treatment compared to 1) usual care (i.e. superiority of the eHealth self-management support program) (C1) and 2) a comprehensive pain rehabilitation program delivered face-toface in a physical therapy setting (i.e. non-inferiority of the eHealth selfmanagement support program) (C2) on pain-related disability (O).