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ATRT-02. MEK/ERK SIGNALLING DEPENDENCY IN ATYPICAL TERATOID RHABDOID TUMOURS

Atypical teratoid rhabdoid tumours (ATRTs) are high-grade malignant paediatric brain tumours with a less than one-year survival rate after diagnosis. Current treatment for ATRT, which includes high-intensive radiotherapy and chemotherapy, results in long-term side effects on ATRT patients. Hence, th...

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Detalles Bibliográficos
Autores principales: Shi, Hui (Claire), Sooraj, Dhanya, Sun, Claire, Daniel, Paul, Bradshaw, Gabrielle, Cain, Jason, Firestein, Ron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7715215/
http://dx.doi.org/10.1093/neuonc/noaa222.002
Descripción
Sumario:Atypical teratoid rhabdoid tumours (ATRTs) are high-grade malignant paediatric brain tumours with a less than one-year survival rate after diagnosis. Current treatment for ATRT, which includes high-intensive radiotherapy and chemotherapy, results in long-term side effects on ATRT patients. Hence, there is an urgent need to discover targeted therapies that could be used to treat patients with ATRT. As part of the Hudson Monash Paediatric Precision Medicine Program, we have collected 23 ATRT cell lines which we used to performed high-throughput small molecule and genetic (CRISPR) screening to identify new therapies and therapeutic targets. In parallel, we characterised the ATRT cell lines based on transcriptomic (RNA-seq) and epigenetic (methylation) signatures. An integrative multi-omic approach was then used to uncover discrete vulnerabilities in specific subsets of ATRT patients. Strikingly, these include a number of druggable dependencies, such as MEK, CDK, HDAC, and Topoisomerase, that offer a promise of rapid clinical translation. In our study, we focus on MEK dependency in a subtype of ATRT lines to further define the underlying mechanisms and biomarkers. While future studies validating the MEK/ERK signalling dependency in a wider cohort of patient models and in in vivo models are required, these data provide a framework for applying an integrative multi-omic approach in paediatric cancer precision medicine.