Biography

Tiannan Guo received training of clinical medicine (1999-2006) in Tongji Medical College, Huazhong University of Science and Technology, and learned biology (2001-2005) in Wuhan University, before he moved to Singapore for PhD training in cancer proteomics (2008-2012) in the laboratories of Dr. Newman Sze in Nanyang Technological University and Dr. Oi Lian Kon in National Cancer Centre Singapore. In 2012, Tiannan started his postdoctoral training in the laboratory of Dr. Ruedi Aebersold in ETH Zurich. Tiannan moved to Sydney as the Scientific Director of ProCan, group leader of Cancer Proteome, Children’s Medical Research Institute, and the conjoint senior lecturer in The University of Sydney Medical School, in March 2017.

Tiannan joined the Westlake Institute for Advanced Studies, Westlake University in August 2017 as a Tenure Track Assistant Professor, and promoted to Associate Professor with tenure in Jan 2023. He is the director of iMarker lab at Westlake Laboratory in 2020, and an associate faculty member of Research Center for Industries of the Future at Westlake University. He also serves as a council member of Human Proteome Organization (HUPO), the chair of Education and Training Committee, co-chair of HPP Cancer Committee, and a member of Marketing and Outreach Committee, as well as the Secretary General of Chinese Proteome Organization (CN-HUPO). He also serves as an associate editor in Molecular & Cellular Proteomics, an associate editor in Clinical Proteomics, an Executive Advisory Board member in Proteomics and Proteomics Clinical Applications, an advisory board member in Cell Reports Medicine, and an editorial board member in Scientific Data, and an editorial board member in Genomics Proteomics Bioinformatics.

His research focuses on proteomic technological development and applications in precision medicine. He and colleagues developed pressure-cycling technology coupled with SWATH/DIA mass spectrometry to enable effective proteomic analysis of biopsy tissues (Nature Medicine, 2015; Nature Protocols, 2022). His team reported the first proteomic and metabolic profiles of COVDI-19 sera (Cell, 2020), and the first proteomic landscape for COVID-19 autopsies (Cell, 2021a), offering novel approaches and insights to the diagnosis and treatment of COVID-19. With a focus on clinical proteomics technologies (Cell, 2021b), his team is exploring AI-empowered proteomic big data for precision medicine with a focus on thyroid nodule diagnosis (Cell Discovery, 2022).

More in www.guomics.com and www.imarkerlab.com.

Research

Proteins are gears of life activities by interacting with each other. Our group is interested in developing advanced proteomics technologies to precisely quantify maximum number of proteins (in thousands) from the minimum amount of biological or clinical samples with the maximum sample throughput. We aim to apply the techniques to uncover the mathematical rules beneath proteome expression, and to assist precision medicine.

The group leader Tiannan Guo’s research topics cover various aspects of mass spectrometry-based proteomics over the past 10 years. His work during PhD training helped him win the Ray Wu Prize. During his postdoctoral training in Professor Ruedi Aebersold’s laboratory, Tiannan developed a unique methodology, namely pressure-cycling technology coupled with SWATH mass spectrometry (PCT-SWATH), to analyze very small amount of biopsy samples in a high throughput manner. This technique currently has been the base technology for the first batch of industrial clinical proteomics facility like ProCan in Sydney. With colleagues, Tiannan has applied this method to study the proteome of 1000s tumors including prostate cancers and renal cancers. In unpublished works, Tiannan and colleagues have studied intra-tumor heterogeneity at proteome level and multiple omics level, as well as developed predictive protein markers for drug sensitivity.

Selected publications

1. Xiu Nie#, Liujia Qian#, Rui Sun#, Bo Huang#, et al, Yi Zhu*, Jiahong Xia*, Yu Hu*, Tiannan Guo*. Multi-organ Proteomic Landscape of COVID-19 Autopsies. Cell. 2021.184(3): 775-791.

2. Bo Shen #, Xiao Yi #, Yaoting Sun #, Xiaojie Bi #, Juping Du #, Chao Zhang #, Sheng Quan #, et al, Yi Zhu *, Huafen Liu *, Haixiao Chen *, Tiannan Guo *. Proteomic and Metabolomic Characterization of COVID-19 Patient Sera. Cell. 2020.182(1): 59-72. 

3. Fangfei Zhang #, Shaoyang Yu #, Lirong Wu #, Zelin Zang, Xiao Yi, Jiang Zhu, Cong Lu, Ping Sun, Yaoting Sun, Sathiyamoorthy Selvarajan, Lirong Chen, Xiaodong Teng, Yongfu Zhao, Guangzhi Wang, Junhong Xiao, Shiang Huang, Oi Lian Kon, Gopalakrishna N. Iyer, Stan Z. Li*, Zhongzhi Luan*, Tiannan Guo*. Phenotype classification using proteome data in a data-independent acquisition Tensor format. Journal of American Society of Mass Spectrometry. 2020 Oct.31(11):2296-2304. 

4. Yaoting Sun#, Sathiyamoorthy Selvarajan#, Zelin Zang#, Wei Liu#, Yi Zhu#, Hao Zhang#, et al, Stan Z. Li*, Oi Lian Kon*, N. Gopalakrishna Iyer*, Tiannan Guo*. Artificial intelligence defines protein-based classification of thyroid nodules. Cell Discovery. 2022. 8:85.

5. Tiannan Guo, Petri Kouvonen, Ching Chiek Koh, Ludovic C Gillet, Witold E Wolski, Hannes L Röst, George Rosenberger, Ben C Collins, Lorenz C Blum, Silke Gillessen, Markus Joerger, Wolfram Jochum, Ruedi Aebersold*. Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps. Nature Medicine. 2015.21(4):407–413.