Tiannan GUO, Ph.D.

Guomics Laboratory of Proteomic Big Data


Email: guotiannan@westlake.edu.cn

Website: http://www.guomics.com

tiannan guo
tiannan guo

Tiannan GUO, Ph.D.

Guomics Laboratory of Proteomic Big Data


Email: guotiannan@westlake.edu.cn

Website: http://www.guomics.com


Tiannan 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, China, 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, conjoint senior lecturer in Sydney Medical School, The University of Sydney, in March 2017. Tiannan joined the Westlake Institute for Advanced Studies in August 2017 as a Tenure Track Assistant Professor.


Dr. Yi Zhu, Judy, Research Associate Investigator

Mr. Tiansheng Zhu, Senior Research Assistant

Mr. Zhicheng Wu, Senior Research Assistant

Mr. Guan Ruan, Research Assistant

Mr. Qiushi Zhang, Research Assistant

Ms. Xue Cai, Research Assistant

Ms. Huanhuan Gao, Research Assistant

Ms. Xiao Yi, Research Assistant

Ms. Nan Xiang, Research Assistant

Ms. Liang Yue, Carrie, PhD candidate

Ms. Yaoting Sun, Teagan, PhD candidate

Mr. Xiao Liang, PhD candidate

Ms. Rui Sun, PhD candidate

Ms. Tian Lu, PhD candidate


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.

Representative Publications

1. Protein Classifier for Thyroid Nodules Learned from Rapidly Acquired Proteotypes.MedRxived: June 17, 202010.1101/2020.06.14.20131078

2. Proteomic and Metabolomic Characterization of COVID-19 Patient Sera. Cell. 2020, 182(1): 59-72 e15 10.1016/j.cell.2020.05.032

3. Phenotype Prediction using a Tensor Representation and Deep Learning from Data Independent Acquisition Mass Spectrometry.bioRxiv: 10.1101/2020.03.05.978635v1

4. Accelerated Lysis and Proteolytic Digestion of Biopsy-level Fresh Frozen and FFPE Tissue Samples Using Pressure Cycling Technology. Journal of Proteome Research. 2020, 19(5), 1982-1990. 10.1021/acs.jproteome.9b00790

5. DPHL: A DIA pan-human protein mass spectrometry library for robust biomarker discovery.

Genomics, Proteomics and Bioinformatics.online 2020 Aug 12 10.1016/j.gpb.2019.11.008

6. High-throughput Proteomics analysis of FFPE tissue samples facilitates tumor stratification.Molecular Oncology. 2019. 13 (11) :2305-2328. 10.1002/1878-0261.12570

7. PulseDIA: in-depth data independent acquisition mass spectrometry using enhanced gas phase fractionation. bioRxiv: 10.1101/787705v1 In revision.

8. Quantitative proteome landscape of the NCI-60 cancer cell lines. iScience. 2019, 21:664-680. 10.1016/j.isci.2019.10.059

9. Multi-region proteome analysis quantifies spatial heterogeneity of prostate tissue biomarkers. Life Science Alliance. Published 29 May 2018. 10.26508/lsa.201800042

10. Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps. Nature Medicine. 2015. 21, 407-413. 10.1038/nm.3807

Allpublication, please go to:http://www.guomics.com/PUBLICATIONS.html