• July 26, 2022

Making sense of big data to cure childhood cancers

Our computational biology program is using massive super computers to help make sense of big data to improve the lives of children with cancer.

Our investment in computational biology is contributing to better treatments for children with high-risk cancers. 

The team brings together data from the genome and other biological measurements and compares these data to healthy children and other children who have had similar cancers before. This helps to work out where possible problems might be — and what treatments have worked in the past.

 

The team has developed the first precision medicine data platform that brings together a range of analytical and statistical tools to enhance the treatment of children with high-risk cancers.  

Huge data sets, including known genetic variations, drug responses, and clinical information from thousands of patients, can be analysed. and interpreted to provide recommendations for individual patients – with the potential to provide more accurate diagnosis and treatment options. 

Over several days, the computers compare the normal genome of a patient, derived from analysing a blood sample, with that of the tumour from the patient, derived from a biopsy.

Using a database of patients who have had this type of cancer previously, the software then identifies the genetic changes most likely to be implicated in the cancer — and what the best treatment approach is likely to be.

 

The results of our Paediatric Precision Medicine Computational Biology Program will have global implications for the management of children’s cancers. As an integral part of the Zero Childhood Cancer Program (ZERO) — a trial that combines medicine, technology, and research to provide personalised medicine for children and young people with cancer —the team is analysing the genomic data of all children with high-risk cancer across Australia. 

This work has underpinned ZERO’s success in identifying the genetic basis of disease in more than 90 per cent of cases. 

 

“The dream is that every patient gets optimal treatment informed by every patient that’s been before them. We’ve developed innovative analysis tools and an online data portal which lets cancer experts identify the medically relevant pieces so that we can inform precision medicine recommendations” says Associate Professor Mark Cowley, Lead of Computational Biology Group at the Children’s Cancer Institute.

Luminesce Alliance has catalyzed the creation of Australia’s largest computational biology group solely focused on paediatric cancer It has allowed us to set up the ability to analyse precision medicine data at national-scale for every Australian child with cancer.