A thorough ‘catalogue’ of an aggressive type of childhood cancer

Improving cancer precision therapy requires a greater ability to identify and describe groups of patients who share the same molecular and clinical particularities. An SIB Swiss Institute of Bioinformatics group recently played a pivotal role in building the most thorough ‘catalogue’ of an aggressive type of childhood cancer – thus providing a basis for novel therapeutic treatments.

In a recent study, an international team of scientists led by Chris Jones from the Institute of Cancer Research (ICR Sutton, U.K.) harnessed the information contained in over 1,000 cases of rare – albeit frequently lethal – brain tumours in children, including 157 unpublished cases.

“With this information at hand, we can now begin to understand which treatment works best for which subtype of the disease”, says SIB Group Leader Michael Baudis. “And by making the data freely accessible, researchers and clinicians can expand on this knowledge by integrating it with their own results, thereby reaching a scale of data which would not be possible in single studies, especially when exploring rare diseases.”

Together with Chris Jones and André von Büren (now University of Geneva), Michael Baudis conceived the original study, based on the concept of cancer genome data aggregation and meta-analysis. Additionally, his group at the University of Zurich assembled data from previous research efforts, an essential step in the analysis of rare tumour entities. Finally, the group developed an online interface to the study’s genome cancer data, which is accessible at dipg.progenetix.org.

The results, published in the journal Cancer Cell, are providing a framework for a better classification of these childhood cancers, therefore opening venues for biologically-driven treatment stratification.

Reference
Mackay A et al. Integrated molecular meta-analysis of 1,000 pediatric high-grade and diffuse intrinsic pontine glioma. Cancer Cell, online on September 28, 2017. doi: http://dx.doi.org/10.1016/j.ccell.2017.08.017

PET image
By Jens Maus (Own work) [Public domain], via Wikimedia Commons