Dr. Tiannan Guo
I learned medicine in Tongji Medical Colleage, mass spec and bioinformatics in Nanyang Technological University, genomics and translational research in National Cancer Centre Singapore. I joined Ruedi’s lab in April, 2012.
My current research focuses on measuring the proteomes of tissue specimens from the cancer population. The goal is to understand proteome dynamics in populations and explore the existence of protein signatures that deliver clinical benefits in terms of cancer diagnosis and therapy selection.
Since cancers are heterogeneous in space and evolving over time, a methodology enabling fast and reproducible acquisition of the acute state of a proteome, i.e. proteotype, from minimal amount of sample, is essential. We have developed the PCT-SWATH (pressure cycling technology coupled with SWATH mass spectrometry) methodology for rapid proteotype acquisition (PubMed: 25730263).
The PCT-SWATH workflow has been applied to generate SWATH maps for hundreds of tumor cell lines and tissue specimens over the past 3 years in Zurich. We foresee a surge of digital biobanks of (cancer) proteomes in the coming years across several continents.
New software infrastructure and data analysis strategy are required to manage the cancer proteome data with unprecedented volume. Part of my research is to explore new approaches for storing, interpreting, and presenting the big proteomic data.
All MS-measurable peptides are digitized in the SWATH maps, however, only a small portion has been annotated with existing database and statistical models. I am interested in applying deep learning technology to explain the unexplored signals.
The high degree of quantitative accuracy and reproducibility of PCT-SWATH data allows potential application of the thus established digital proteome biobank in clinical decision making. We are exploring this possibility by collaborating with the medical community.