Description:
<jats:title>Abstract</jats:title>
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<jats:title>BACKGROUND</jats:title>
<jats:p>Central nervous system (CNS) tumors are the second most common childhood cancer. Despite innovations in surgery and chemo-/radiotherapy, CNS tumors remain the major cause of cancer-related death in children. Previous sequencing analyses in a pediatric cancer cohort identified BRCA and DSB repair signatures as potentially targetable events. Based on these findings, we propose the use of PARP inhibitors (PARPi) for aggressive CNS tumor subtypes, including high-grade glioma (HGG), medulloblastoma (MB) and ependymoma (EPN).</jats:p>
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<jats:title>METHODS</jats:title>
<jats:p>We tested multiple PARPi in tumor cell lines (n=8) as well as primary patient-derived models (n=11) of pediatric HGG, MB, EPN and atypical teratoid/rhabdoid tumors (ATRTs). Based on PARPi sensitivity, selected models were further exposed to a combination of PARPi and DNA-damaging/modifying agents. The mode of action was investigated using Western blot and flow cytometry.</jats:p>
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<jats:title>RESULTS</jats:title>
<jats:p>We show that a fraction of pediatric MB, EPN and ATRT demonstrate sensitivity towards PARP inhibition, which is paralleled by susceptibility to the DNA damaging drugs cisplatin and irinotecan. Interestingly, talazoparib, the most potent PARPi, showed synergistic cytotoxicity with DNA-damaging/modifying drugs. In addition, cell cycle blockade and increased DNA damage combined with reduced DNA repair signaling, such as activation of the ATR/Chk1 pathway were observed. Corroboratively, talazoparib exhibited a synergistic anti-cancer effect in combination with inhibitors of ATR, a major regulator of DNA damage response.</jats:p>
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<jats:title>CONCLUSION/OUTLOOK</jats:title>
<jats:p>To sum up, we demonstrate that PARP inhibition synergizes with DNA damaging anti-cancer compounds or DNA repair inhibitors and, thus, represents a promising therapeutic strategy for a defined subgroup of pediatric high-risk CNS tumors patients. More in depth characterization of the underlying molecular events will most likely allow the identification of predictive biomarkers for most efficient implementation of this strategy into clinical application.</jats:p>
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