National Centre for Spatial Tissue and AI Research - NCSTAR
The National Centre for Spatial Tissue and AI Research brings together researchers in academia, medicine and industry with the common goal of discovering novel drug targets and improving clinical decision making through the development of spatially-defined, tissue biomarkers.
Identifying the right therapy for the right patients at the right time
Vision
Improve diagnosis, prognosis and treatment strategies for patients through spatial tissue analysis.
Purpose
Advance clinical and basic research through the employment of cutting-edge spatial technologies and innovative machine learning analytics.
Outcomes
Establish impactful clinical collaborations, identify novel biomarkers and drug targets, and improve patient outcomes.
Contact us
For further information or questions please contact the NCSTAR team.
Advancing spatial biology through machine learning to drive better outcomes for patients
Studying disease mechanisms via the elucidation of spatial relationships between different cell types and their gene expression patterns within diseased tissues.
- Provides insights into the underlying pathological mechanisms of disease.
Identify disease-specific biomarkers that are localized to particular regions or cell types within a tissue sample.
- These biomarkers could then be used for diagnosis, prognosis, or treatment selection in clinical trials.
Spatial biology can be used to evaluate drug responses.
- This can provide valuable information about the mechanism of action and efficacy of investigational therapies.
Guiding targeted therapies.
- The spatial mapping of gene expression and cell types within a tumor or other tissue can help guide the development and application of targeted therapies that aim to selectively act on specific cell populations or spatial regions.
Meet the team
Associate Professor Quan Nguyen
Associate Professor Nguyen acquired multidisciplinary expertise at the world’s top innovative institutions in Australia (UQ, CSIRO) and internationally (RIKEN Institute and Stanford School of Medicine). With supports from multiple prestigious fellowships, including ARC DECRA and NHMRC (EL2), he established his leadership in addressing cancer complexity at single cell and tissue levels. Associate Professor Nguyen has led multiple large-scale projects/programs, funded nationally (e.g., ARC, NHMRC, MRFF) and internationally (e.g., DoD, NCI, Wellcome Trust).
Dr Bill Dougall
Dr William Dougall has authored more than 80 peer-reviewed publications (>12,000 citations) and holds seven patents. Prior to his appointment at QIMRB, he worked in industry and led multiple oncology drug development programs through IND and Phase I testing, including world-wide registration of denosumab, an agent widely used in oncology. He was the first to clone the novel TNF ligand/TNF receptor pair RANKL/RANK and demonstrate an obligate role for this pathway in development of lymph nodes, mammary glands and osteoclasts. More recently, he has provided new insights into RANKL biology relevant to cancer immunotherapy as well as characterized two other novel targets for cancer immunotherapy. Dr Dougall has extensive experience with preclinical tumor immunology models, clinical biomarker development (including IHC and transcriptomics) and has contributed to the translational design of over 20 oncology clinical trials (PI-III).
Jason Madore
Senior Science Officer – Spatial Biology
Joey Li
Machine learning researcher.
Ashandeep Kaur
Research Assistant – Spatial Biology
Selected publications
- Pham, Duy, Tan, Xiao, Balderson, Brad, […], Ruitenberg, Marc J. & Nguyen, Quan H. 2023, ‘Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues’, Nature Communications, vol. 14, no. 1, doi:10.1038/s41467-023-43120-6
- Tan, Xiao, Grice, Laura F., Tran, Minh, Mulay, Onkar, Monkman,[…], Kulasinghe A and Nguyen Q. ‘A robust platform for integrative spatial multi‐omics analysis to map immune responses to SARS‐CoV-2 infection in lung tissues’, Immunology, 2023, 170(3) PMID:37605469
- Tran, S. Yoon, M. Teoh, S. Andersen, PY. Lam, B. W. Purdue, A. Raghubar, SJ. Hanson, K. Devitt, K. Jones, S. Walters, J. Monkman, A. Kulasinghe, ZK. Tuong, HP. Soyer, I. H. Frazer & Q. Nguyen 2022, ‘A robust experimental and computational analysis framework at multiple resolutions, modalities and coverages’, Frontiers in Immunology, vol. 13, doi:10.3389/fimmu.2022.911873
- Andrew Su, HoJoon Lee, Xiao Tan, Carlos J. Suarez, Noemi Andor, Quan Nguyen* & Hanlee P. Ji* 2022, ‘A deep learning model for molecular label transfer that enables cancer cell identification from histopathology images’, npj Precision Oncology, [*co-corresponding authors], vol. 6, no. 1, doi:10.1038/s41698-022-00252-0
- Lewis SM, Asselin-Labat ML, NGUYEN Q, Berthelet J., Tan X, Wimmer VC, Merino D, Roger K, Naik SH. (2021). Spatial omics and multiplexed imaging to explore cancer biology. NATURE METHODS, 18, 9.
- Xiao Tan, Andrew Su, Minh Tran & Quan Nguyen 2019, ‘{SpaCell}: integrating tissue morphology and spatial gene expression to predict disease cells’, Bioinformatics, vol. 36, no. 7, pp. 2293–2294, doi:10.1093/bioinformatics/btz914