Phosphoproteomics for precision oncology

 

Connie R. Jimenez

 

OncoProteomics Laboratory, Dept. Medical Oncology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands.

 

The general goal of our clinical cancer proteomics efforts is to disclose tumor biology and drive improved diagnostics, treatment and management of cancer (Jimenez et al., Clin. Prot. 2018). To this end, we use label-free mass spectrometry-based proteomics that is optimally suited for large-scale clinical sample profiling. I will highlight our work in colorectal and triple negative breast cancer with a focus on cancer phosphoproteomics for response prediction.

 

More specifically, I will discuss our newly developed Integrative inferred kinase activity (INKA) scoring (preprint in Biorxiv). This multipronged, stringent analysis combines label-free kinase-centric and substrate-centric information and enables ranking of kinase activity and visualization of kinase-substrate networks in a single biological sample. To demonstrate utility, we analyzed 1) cancer cell lines with known oncogenes, 2) cell lines in a differential setting (wild-type versus mutant, +/- drug), 3) pre- and on-treatment tumor needle biopsies, 4) cancer cell panel with available drug sensitivity data, and 5) patient-derived tumor xenografts with INKA-guided drug selection and testing. These analyses show superior performance of INKA over its components and substrate-based single-sample tool KARP, and underscore target potential of high-ranking kinases, encouraging further exploration of INKA’s functional and clinical value. Ultimately cancer proteomics powered by precise measurements and dedicated analysis will realize the full potential of multi-parameter diagnostics and personalized medicine.