Integration of genomics, high throughput drug screening, and personalized xenograft models as a novel precision medicine paradigm for high risk pediatric cancer
Journal Title
Cancer Biology & Therapeutics
Publication Type
Journal Article
Abstract
Pediatric high grade gliomas (HGG) are primary brain malignancies that result in significant morbidity and mortality. One of the challenges in their treatment is inter- and intra-tumoral heterogeneity. Precision medicine approaches have the potential to enhance diagnostic, prognostic and/or therapeutic information. In this case study we describe the molecular characterization of a pediatric HGG and the use of an integrated approach based on genomic, in vitro and in vivo testing to identify actionable targets and treatment options. Molecular analysis based on WGS performed on initial and recurrent tumor biopsies revealed mutations in TP53, TSC1 and CIC genes, focal amplification of MYCN, and copy number gains in SMO and c-MET. Transcriptomic analysis identified increased expression of MYCN, and genes involved in sonic hedgehog signaling proteins (SHH, SMO, GLI1, GLI2) and receptor tyrosine kinase pathways (PLK, AURKA, c-MET). HTS revealed no cytotoxic efficacy of SHH pathway inhibitors while sensitivity was observed to the mTOR inhibitor temsirolimus, the ALK inhibitor ceritinib, and the PLK1 inhibitor BI2536. Based on the integrated approach, temsirolimus, ceritinib, BI2536 and standard therapy temozolomide were selected for further in vivo evaluation. Using the PDX animal model (median survival 28 days) we showed significant in vivo activity for mTOR inhibition by temsirolimus and BI2536 (median survival 109 and 115.5 days respectively) while ceritinib and temozolomide had only a moderate effect (43 and 75.5 days median survival respectively). This case study demonstrates that an integrated approach based on genomic, in vitro and in vivo drug efficacy testing in a PDX model may be useful to guide the management of high risk pediatric brain tumor in a clinically meaningful timeframe.
Publisher
Taylor and Francis Inc.
Research Division(s)
Bioinformatics
PubMed ID
30299205
Open Access at Publisher's Site
https://doi.org/10.1080/15384047.2018.1491498
Terms of Use/Rights Notice
Refer to copyright notice on published article.


Creation Date: 2018-10-11 04:23:20
Last Modified: 2018-10-12 04:00:04
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