Project title
Tailoring precision immunotherapy to age and sex differences through digital tissue A.I. models
Collaborators and funding
Funding: SAiGENCI startup funds, CZI Essential Open Source Software for Science.
Contact(s)
- Stefano Mangiola, SAiGENCI stefano.mangiola@adelaide.edu.au
Project description and aims
Demographic factors such as age and sex critically influence disease outcomes and response to treatment, including cancer immunotherapy1,2. Emerging evidence suggests that immune checkpoint inhibitors targeting PD-1, LAG3, and CTLA-4 exhibit sex-dependent efficacy in colorectal cancer, breast cancer, non-small cell lung cancer, and melanoma, with females having poorer overall survival outcomes compared to males3. Age is a well-recognised factor influencing differential immunotherapy efficacy2. Overall, the diversity of the immune system across organs and demographic groups limits universally effective immune therapies. The mechanisms underlying demographic effects are undercharacterised, relying on model organisms or bulk tissue data, such as The Cancer Genome Atlas7,8. The lack of single-cell resolution obscures cell-type-specific signals, restricting mechanistic understanding of immunotherapy-response diversity across the population. A body-level single-cell immune map encompassing a wide demographic spectrum is crucial for characterising this diversity mechanistically and at scale, ultimately boosting clinical translation.
The recently released Human Cell and Tumour Atlases make this possible for the first time. We aim to perform population and organ-level investigations of the healthy immune system using the 50-million-cell Human Cell Atlas compendium, which is distributed across 7,981 healthy individuals and 30 organs. We aim to create a compositional, gene expression and cell-communication map and uncover significant diversity in immunotherapy targets (e.g. LAG3, VSIR, and TIM3) across ages and sex. This first-of-its-kind map will allow for testing the deviance from the healthy state across the population, organs, cells, and molecular pathways.
How is ABLeS supporting this work?
This work is supported through the production bioinformatics scheme provided by ABLeS. The supports includes unlimited temporary storage on scratch, 5 TB long-term storage and 50 KSUs allocation per quarter.
Expected outputs enabled by participation in ABLeS
A deep-learning map of the immune system across the human population, in health and disease.
These details have been provided by project members at project initiation. For more information on the project, please consult the contact(s) or project links above.