Computational immunology
Dr Kelvin Tuong is a Senior Research Fellow/Group Leader at the IFCCIR. He was originally trained as a cell biologist/immunologist and has since developed key expertise in bioinformatics. He is also co-chair of the ASI Systems Immmunology Special Interest Group (2023-2025).
The Tuong lab is interested in harnessing the adaptive immune receptors expressed by T and B cells for understanding immune cell development and function in health and in cancer.
We have developed bioinformatics tools and packages to achieve this, for example, a bespoke software tailored for single-cell T/B Cell Receptor sequencing analysis, Dandelion, which was used in one of the largest combined single-cell transcriptomic, surface proteomic and TCR/BCR sequencing dataset in the world, published in Nature Medicine. We also introduced a new concept for performing trajectory analysis using immune repertoires in a recent publication in Nature Biotechnology.
Ongoing work is exploring different ways to combine the adaptive immune receptors with the gene expression of the immune cells at a single-cell level to track the T and B cell response to cancer, infection and therapy.
Based at the Child Health Research Centre, we are working together with the IFCCIR team to focus on how pediatric immunity is perturbed during cancer at the cellular level and how this information can be used for creating novel warning systems for children with cancer.
A cancer diagnosis at any age is upsetting, but felt more harshly when the patient is a young child who has only started out in life. Compared to adult cancer patients, the window of opportunity to help child cancer patients is especially short. We need to create an early warning system for paediatric cancers. Specialized immune cells known as T-cells and B-cells use specific receptors to recognize tumour antigens and fight cancerous cells. My lab's vision is to harness these cells and their receptors to enable early cancer detection and disease monitoring. These specific adaptive immune receptors are essential for all aspects of the T- and B-cell’s life cycle, serving as natural ‘time-keepers’ of the immune response against cancer progression. We will create bespoke computational algorithms to explore the properties that define how effective these immune cells are in childhood cancer, perform high resolution gene expression profiling at the single-cell level and develop highly advanced computer models that can be used to detect adaptive immune receptors that are targeted towards cancer. The projects will be largely dry-lab based and the candidates should expect to be working as part of a team together with leading groups in Australia as well as international collaborative networks (Cambridge, Sanger, UK).
Available projects
Evaluating machine learning models classifying cancer-specific pattern in children with cancer.
- Profiling the expression of active genes and adaptive immune receptors on cancer cells to develop a deeper understanding of paediatric hematopoietic cancer
- Developing single-cell trajectory analysis methods for adaptive immune cells
The projects will suit either an immunologist wanting to learn bioinformatics and/or a computer scientist who wants to apply their skills onto biological problems. MD students/clinicians who are keen to learn programming are also welcomed.
We have ongoing collaborations with researchers based in the region (UQ), national (WEHI, Melbourne) and internationally (e.g. UK – Cambridge, Sanger, Newcastle, Birmingham; US – UTHSA, WU St. Louis).