Mini-brain systems to identify novel treatments for brain cancer

A multitude of brain cancer (glioma) mutations, identified by large-scale next generation sequencing (NGS), are predicted to drive disease through computational algorithms in silico.

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This project is open for Honours and PhD students
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Professor Leonie Quinn
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About

A multitude of brain cancer (glioma) mutations, identified by large-scale next generation sequencing (NGS), are predicted to drive disease through computational algorithms in silico. To investigate whether predicted glioma mutations alter neural stem and/or progenitor cell fate cell (alone or in combination) in intact tissues or organisms, the Brain Cancer Discovery Group uses a combination of Drosophila and human functional genetic models.

Mini-brain systems to identify novel treatments for brain cancer

To identify drugs targeting brain cancer sub-types, we are using  human brain organoid “mini-brain” models to recreate the heterogenous cellular composition of brain tumours. Through a combination of CRISPR gene editing and bioprinting technologies, these next-generation three-dimensional cell systems enable us to model progression of specific genetic sub-types and patient-derived glioma to, ultimately, identify new therapies capable of killing cancer cells while leaving the patient’s healthy neural cells intact. Our drug discovery research program is enabled by the ACT Brain Cancer Biobank (ABCB), which represents consenting patients treated at The Canberra Hospital (TCH).

Importantly, extensive genomic analysis of each patient’s brain tumour cells provides the molecular classification based on genetic profiles and gene expression signatures. Thus, we can match molecular signatures with outcomes from our drug studies to determine sensitivity of glioma sub-types to a given drug therapy. We will ensure promising candidates from our drug discovery research are fast-tracked to clinic through our clinical collaborations at The Canberra Hospital (TCH). Thus, we will identify new therapeutic candidates that can be fast-tracked to the clinic to improve patient outcomes.

Members

Supervisor

Head, Division of Genome Sciences and Cancer