Obj1: We tested a series of small molecules as well as 5 different matrices to grow tumor cells in a 3D environment. Using these culture conditions, we could achieve a high success rate for neuroblastoma organoid culture. As anticipated in the research proposal, we have retrieved and worked up primary and relapse tumor materials from 102 neuroblastoma tumors. We have expanded and stored these samples. A selected set of 73 models were eventually growing successful. This repository represents the diversity of neuroblastoma primary and relapse tumors, which has been used for subsequent analysis in objective 2, 3 and 4.
Obj 2: We perform profiling on several platforms that were state of the art. Initially we used WGS on the ilumina HiSeq platform. When the Princes Maxima Center established the NovaSeq we decided to change our methodology to WES on the Novaseq with the Maxima bioinformatic processing pipeline. RNA seq was performed using our inhouse RNAseq platform on the Novaseq. All samples were analyzed using this set-up to allow uniform analysis and easy correlative analysis with corresponding patient derived samples that were profiled on this same platform. The data was uploaded in the bio informatic platform R2 (
http://r2.amc.nl(öffnet in neuem Fenster)) under a restricted account. For all genomic events and expression data genes are indicated that are potentially actionable or have been reported before to be mutated in the cosmic database. Thereby potential genomic events for intervention can be easily identified per organoid sample. This part of the R2 bioinformatic platform will be public available and all raw data is available for the peadiatric cancer comunity
Obj 3: In 2018 we have initiated our own High Through-put Screening (HTS) robotics facility at the princess Maxima Center. This new robotics set-up which is operated by our group is now made available for our complete institute and for external academic collaborators. (
https://research.prinsesmaximacentrum.nl/en/core-facilities/high-throughput-screening(öffnet in neuem Fenster)). We have generated a compound library of 200 compounds containing al compounds used in pediatric cancer treatment, compounds in early phase clinical trials in paediatric cancer and a series of targeted compounds with promising preclinical data in pediatric cancer. In total we have generated over 500 individual compound screens using the library. A large amount of promising candidate interventions have been tested in combination by screening the complete compound library of 200 compounds in combination with a compound concentration serries of an effective compound. On neuroblastoma models the following inhibitors were tested in combination screens: RAS/MAPK inhibitor Trametinib. The BCL2 inhibitor Venetoclax, The CHK1 inhibitor Prexacertib, The EZH2 inhibitor Tazametostat, The PARP inhibitor Talazoparib. In addition several compound combination screens were perfomed on other tumor type organoids in a collaborative effort. Finally, we also used the compound screening facility to screen isogenic systems to identify compounds that were more effective in tumors with certain types of genomic aberrations.
Obj 4 and 5. Data from 3C has been used for selection of optimal combination options that have been further evaluated in vivo. We now have a repository of 15 neuroblastoma organoids for which also PDX models are available. These models will be made available through the ITCC-P4 consortium to the research community and industry. A business case is currently being generated within the ITCC-P4 consortium. Our models were used to validate the in vitro screening results for various combinations with Venetoclax, Lorlatinib, Prexacertib, Idasanutlin Cobimetinib and Abemaciclib.
The applicant has published 39 peer reviewed papers in the period of PREDICT research project.
Three PhD students that were supervised by the applicant have successfully defended their thesis during the PREDICT research project.
