Periodic Reporting for period 3 - TOPAS (Exploiting the Tumor Proteome Activity Status for Future Cancer Therapies)
Reporting period: 2022-09-01 to 2024-02-29
Today, precision oncology makes use of genomic and transcriptomic profiling of cancer patients. Physicians and scientists come together in interdisciplinary molecular tumor boards to evaluate the druggability of any genetic abnormalities in order to recommend a treatment. However, the majority of genomic aberrations detected in cancer patients are functionally not understood so they do not lend themselves as biomarkers for treatment. In addition, the measurement of transcriptomes is a poor proxy for the activity of proteins. As the malignant activity of most cancers is driven by malfunctioning proteins, and the fact that most targeted cancer drugs act on proteins by modulating so-called post-translational modifications, notably phosphorylation, a logical next step is to add a proteomic component to the molecular profiling data. Hence, the overall goal of this project is to establish the tumor proteome activity status (TOPAS) of individual patients as an evidence-based criterion for treatment recommendations by molecular tumor boards. For this idea to work out, it is important to understand what patient proteomes look like, what cancer drugs do to patient proteomes and how this information can be put together to guide treatment recommendations.
To achieve this, the overall objectives of TOPAS are: 1) To show that modulating the TOPAS of cancer models by kinase inhibitors functionalizes the phosphoproteome and reveals the cellular mechanisms of action of these important medicines. 2) To develop and validate drug-, protein- and pathway-centric TOPAS scores able to make treatment suggestions based on the proteomes and phosphoproteomes of cancer cell lines and patients. 3) To demonstrate that phosphoproteomic analysis and TOPAS scoring of sarcoma patients complements information from genomic profiling and aids in decision making by molecular tumor boards.
In parallel, we have quantitatively characterized the activity of about 130 cancer drugs on the phosphoproteomes of four cancer models, representing more than 10 million data points for mining and sharing with the scientific community and the general public via https://www.proteomicsdb.org/. Based on patient proteome profiles, we have developed scoring schemes that reduce the enormous quantities of data to what is clinically actionable and implemented the use of the proteomic data as well the scores in a molecular tumor board. More than 100 patients have already been analysed this way and the results show that adding the proteomic angle provides more confidence for treatment recommendations.