Presented at the American Association for Cancer Research (AACR) Meeting 2026
Presented by Matthieu Spriet, Scientist, Inventia Life Science
Ali McCorkindale1*, Elahe Minaei2, Peilin Tian3, Joanna Wasielewska1, Sean Porazinski1†
1. Inventia Life Science, Alexandria, NSW Australia
2. Illawarra Health and Medical Research Institute, University of Wollongong, NSW Australia
3. School of Chemistry and Australian Centre of NanoMedicine, UNSW Sydney, NSW Australia
* Primary presenting author.
† Corresponding author: sean.porazinski@inventia.life
Precision oncology workflows often rely on sequencing to identify potential treatment options. However, molecular data alone may not fully explain treatment resistance or indicate how a patient-derived tumor model will respond functionally.
In this video poster presentation, Matthieu Spriet walks through a workflow combining patient-derived colorectal cancer tumoroids, 3D drug response testing, RNA sequencing, proteomics, and quantitative imaging.
Using the RASTRUM Allegro platform, the team generated two patient-derived colorectal cancer tumoroid models in defined synthetic matrices. The models were characterized for growth and subtype-associated biology, then used to investigate response to selected therapies and explore potential resistance mechanisms.
Follow the study from model generation and characterization through functional drug response testing and multi-omics analysis.
The presentation covers:
Poster
Prefer to review the workflow, figures, and results in detail?
Download the AACR 2026 scientific poster for the complete study overview, including model characterization, molecular profiling, and treatment response data.