ORCID iD: 0000-0003-4849-4903
Scopus Author ID: 15766803800
ResearcherID: B-2917-2011
Google Scholar Profile: -A6D46UAAAAJ

Metrics for Academic and Research Impact

PhD (Karolinska)

Prof. Zheng received his PhD degree with distinction in medical epidemiology from Karolinska Institutet in 2011. He then completed his postdoctoral training at Massachusetts General Hospital and Harvard Medical School, supported by the Swedish Research Council International Postdoc Fellowship. In July 2015, he joined the Department of Biomedical Sciences at City University of Hong Kong.

We are looking for motivated individuals who are passionate about genomic medicine to join our lab as research assistants, PhD students and postdocs.

We are interested in genomic medicine and biotechnology innovation to advance our understanding, diagnosis and treatment of diseases. We invented the AMP technology, which has significantly accelerated gene fusion discovery. Initially implemented in top U.S. hospitals, the AMP technology has since been adopted globally in molecular diagnosis assays to guide targeted therapy for cancer patients. We co-developed the GUIDE-seq method, a widely used reference for genome-wide unbiased profiling of CRISPR edits. GUIDE-seq has supported the first CRISPR therapy approved by FDA in December 2023 that utilises the precise genome targeting technology CRISPR/Cas9.

Recently, we revealed gene rearrangement or fusion heterogeneity-associated therapy resistance in non-small cell lung cancer patients, suggesting that tailored/precision targeting approaches are needed for treating these cancer patients. We observed in patient tumors, under the ground, numerous “futile” rearrangements involving genes that are in close proximity within a cell nucleus, leading us to introduce the concept “passenger fusion”. To address the “passenger fusion” issue before targeted therapy, we recommend using orthogonal diagnosis methods beyond DNA-based approaches. Subsequently, we developed an ultra-sensitive clinical-grade RNA-seq-based rearrangement calling algorithm SplitFusion. On genome editing, we developed GenomePAM, a novel tool enabling direct identification of PAM sequences in mammalian cells. This approach achieves greater than 10,000-fold higher efficiency while being simpler than previous in-cell methods. Additionally, we have discovered new CRISPR/Cas nucleases from nature and, leveraging AI models, engineered variants with desired PAM preferences for therapeutics.

Currently, our research employs multi-disciplinary approaches, including genomics, AI-powered protein engineering, and molecular epidemiology, centering on:

• Lung Cancer: to understand the molecular heterogeneity that underpins resistances to targeted therapy and immunotherapy in lung cancer patients.
• Precision Genome Editing: to advance precision genome editing and delivery technologies for the development of safe and curative treatments.
• Liquid Biopsy: to identify molecular determinants and circulating signatures that can be used for cancer monitoring, diagnosis, and early detection.