Researchers from the Wellcome Sanger Institute and the Children’s Medical Research Institute (CMRI) in Sydney, Australia, have completed a protein map for 949 cancer cell lines across over 40 cancer types, which have been tested with 650 different treatments. Advanced computational methods were then used to predict the response of cancer cells to treatment.
The paper, published in Cancer Cell, lays the foundation for ongoing efforts to predict the response of individual cancer to drugs based on the proteins cancer contains. These data will also inform the development of new treatments.
Every cell in the body contains thousands of proteins, collectively called the proteome. These proteins are responsible for most of the functions of life, including the behavior of cancer cells and how they respond to treatment. Clinical cancer specialists have known for many decades that measuring the quantities of a few specific proteins can help guide the choice of the most appropriate treatment for some types of cancer. But methods for measuring the thousands of other types of proteins have not been readily available for clinical use.
In this study, CMRI’s ProCan® team developed a high-throughput workflow using mass spectrometry to measure thousands of different proteins in huge numbers of cancers. Using this methodology and 10,000 hours of mass spectrometry instrument time, they generated a proteomic database for the 949 cancer cell lines grown by the Sanger team, who analysed the response of each cell line to up to 650 different drugs, and who have previously deeply analysed the genes and other key molecules in these cancer lines.
In contrast to clinical trials which can each test only one treatment or treatment combination, there is no limit to the number of drugs tested on cancer cell cultures in the laboratory. Generating data regarding the response of such a large number of cancer cell lines to 650 drugs, and their comprehensive molecular analysis, has required a significant investment of resources and effort over many years by the Wellcome Sanger Institute.
Data scientists from CMRI and Sanger worked together to analyse the results with advanced computational methods, developing a new deep learning technique to use proteomic data to predict the response of the cancer cells to treatment. The results also pinpoint vulnerabilities in cancer cells that provide opportunities for developing new treatments.
Source: Sanger Institute