Sometimes powerful scientific discoveries can be explained in very simple terms. In some cases, the process resembles detective work: searching through vast amounts of information to find an almost perfect match, while carefully ruling out anything that looks similar but does not quite fit.
This was the approach taken by Associate Professor Fernando Guimaraes and his team of researchers at the Frazer Institute at University of Queensland (UQ), as they worked to develop a new antibody that recognises a unique part of the cancer- associated protein ROR1 that could help destroy hard-to-treat tumours, such as triple-negative breast cancer.
Dr Magda Antczak, Bioinformatician at QCIF, played an important role in this discovery.
Using advanced bioinformatics tools, she helped the team identify which parts of the ROR1 protein could be safely and effectively targeted by an antibody, leading to the development of safer cancer therapies.
Why ROR1 matters
ROR1, found on the surface of many tumour cells, is associated with aggressive cancers, making it a strong candidate for targeted cancer therapies. The challenge, however, is precision.
Some regions of ROR1 resemble regions of other proteins found in normal tissues. Targeting those regions increases the risk of targeting wrong cells and therefore, the risk of side effects, something patients with aggressive cancers can least afford.
The key question for the research team was how to identify which parts of ROR1 were truly unique to cancer cells.
Like Sherlock Holmes, but for protein analysis
The majority of current anti-ROR1 monoclonal antibodies target the Ig-like domain of the extracellular region of ROR1. To assess whether this region was safe to target, Dr Antczak used BLAST searchers to compare the ROR1 sequence against normally expressed human proteins.
This analysis identified a total of 55 proteins with similarities to ROR1, including VEGRFR2, with significant homology to the Ig-like domain of ROR1.
As Dr Antczak explains, the goal was to be absolutely confident about what made ROR1 different.
“It was really rewarding to support the team by pinpointing the parts of the protein that were truly unique to cancer cells,” she said. “Those distinctions are critical when you’re designing therapies that need to be both effective and safe.”
Seeing proteins in 3D
To deepen the analysis, Dr Antczak used the Australian Alphafold 2 Service on Galaxy Australia, a service provided by Australian BioCommons and its partners, to study detailed 3D models of ROR1 and VEGFR2.
This process is similar to comparing the digital blueprints of different machines, examining where their shapes overlap and where they clearly diverge.
This step-by-step approach revealed which similarities posed a higher risk and confirmed a region of ROR1 that stood out as distinct and an ideal target for an antibody designed to attack cancer cells while sparing healthy tissue.
“It’s great to see those insights contribute to a therapy with real potential to help patients,” Dr Antczak said.
A new hope for cancer treatment
These findings supported the UQ researchers in designing a new antibody that binds specifically to the unique region of ROR1.
In laboratory and animal studies, this antibody was paired with engineered natural killer (NK) cells - immune cells modified to better resist tumour-suppressing signals. Together, they showed significantly improved tumour control, opening a pathway toward future clinical evaluation and a new hope for patients with limited treatment options.
Dr Antczak’s contribution highlights how advanced bioinformatics and cross-institutional partnerships can accelerate discovery and enable safer, more targeted therapies that could benefit cancer treatment patients.
Developed with co-funding from a Therapeutic Innovation (TIA) Pipeline Accelerator Voucher, in collaboration with the National Biologics Facility (NBF), and further advanced through the BASE mRNA Facility, this multi-disciplinary and translational collaboration brought together researchers from UQ, QCIF Digital Research, Mater Research Institute, Peter MacCallum Cancer Centre, Olivia Newton-John Cancer Research Institute, and the Pontifical Catholic University of Paraná (PUCPR) in Brazil.
QCIF Digital Research and NCRIS partners Therapeutic Innovation Australia (TIA) and Australian BioCommons are proud to have supported this work.
To learn more about this collaboration, visit our project page and the QCIF Bioinformatics website, where you can explore how our team helps scale analyses, refine computational pipelines, and tackle complex biological questions.