Studying genetics and cancer cell behaviour

Professor John Mattick

Professor John Mattick

Garvan Institute of Medical ResearchFunding duration: 2014 - 2018

Professor John Mattick and his team are using cutting-edge sequencing technologies to uncover various components of DNA and how they differ in cancer cells.

Background

The number of Australians living with or beyond cancer is expected to increase by a staggering 72% by 2040. Standard cancer treatments take a heavy toll on patients as they don’t account for the many unique characteristics of individual cancers. Personalised treatment approaches offer new hope for improving treatment effectiveness while minimising side effects.

The research

In this project, the researchers have been using cutting edge next-generation sequencing technologies to reveal the genetic structures underlying the development and progression of cancer. Cancer is a complex disease characterised by abnormal gene behaviours and unstable DNA.

The team have focussed on characterising a subset of genes called non-protein coding RNAs, the most diverse class of molecules in cells, which have abnormal activity in cancer. Since a large amount of RNAs have no known function, discovering their molecular features and how these are linked to certain biological functions is essential to further our understanding of the molecular transactions underlying cancer development.

Specifically, the group aimed to systematically investigate the structure and function of non-coding RNA molecules, which interfere with chromosome organisation in breast cancer cells.

The impact

The team’s work produced new methods to study RNA molecules through the structures they form in a cell. The group developed a way to link biological functions to specific RNA molecules by identifying structural patterns in the RNAs that bind to proteins with known functions in the cell. These RNA structures can then be mapped in the human genome to provide a function to regions of previously unknown function.

The findings from this provide a toolkit to accurately classify and assess the genetic mutations that can lead to cancer. With the ability to identify these unique genetic abnormalities and link them to biological functions, researchers and clinicians will be able to develop personalised treatment approaches to optimise patient outcomes.

Lead ResearcherResearch Team

Professor John Mattick
Garvan Institute of Medical Research

Dr Martin Smith
Dr Sandro Ataide


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