Genetic influence on cancer mapped

A new method to map cancer genes and improve personalised cancer treatment has been built by Swedish researchers.

The Pathology Atlas was built using a systems-based analysis of 17 main cancer types collected from 8,000 patients. A supercomputer analysed more than 2.5 petabytes of publicly available data from the Cancer Genome Atlas (TCGA) to create it.

Professor Mathias Uhlen, leader of the Pathology Atlas programme and director of the Human Protein Atlas consortium, said: “We show, for the first time, the influence of the gene expression levels demonstrating the power of “big data” to change how medical research is performed. It also shows the advantage of open access policies in science in which researchers share data with each other to allow integration of huge amounts of data from different sources.”

Cancer coding-genes

The researchers discovered that a large fraction of cancer protein-coding genes respond to signals or triggers, and in a large number of cases, have an impact on patient survival. Shorter patient survival was associated with an increase of genes involved in mitosis and cell growth, and a decrease in genes involved in cellular differentiation.

The data collected by the researchers has allowed them to generate personalised genome-scale metabolic models for cancer patients to identify key genes involved in tumour growth. In addition, there are five million pathology based images that have been generated from the Human Protein Atlas consortium.

Dr Adil Mardinoglu, SciLifeLab Fellow and leader of the systems biology effort in the project, said: "We are now in possession of incredibly powerful systems biology tools for medical research, allowing, for the first time, genome-wide analysis of individual patients with regards to the consequence of their expression profiles for clinical survival."

The Pathology Atlas can be accessed in an interactive open access database at http://www.proteinatlas.org/pathology. The paper was published in Science.