Scientists at the University of South Australia have developed an AI-powered method that reveals how groups of genes work together to drive cancer progression, offering a path toward earlier and more precise treatments. Published in Royal Society Open Science, the study shows that cancer advancement is fuelled by cooperating gene networks rather than single mutated genes acting independently.
Lead researcher Dr. Andres Cifuentes-Bernal explains that the system analyses how genes influence each other over time, providing a clearer picture of the biological processes that allow tumours to grow, spread, and resist therapy. Traditional cancer studies focus mainly on common mutations, but this overlooks rare changes and the complex interactions that give malignant cells momentum. The new framework fills this gap by capturing the dynamic nature of cancer.
Using large breast cancer datasets, the AI method identified both well-known cancer genes and previously hidden ones that while not mutated still affect other genes and shape tumour progression. It accurately detected many cancer drivers listed in the Cancer Gene Census, confirming its reliability. Several newly discovered gene candidates are linked to cell signalling, immune response, and metastasis.
Associate Professor Thuc Le says the approach highlights cooperative networks rather than isolated genes, offering deeper insight into tumour evolution. The adaptable method may also assist in understanding other diseases involving shifting gene regulation, including neurodegeneration and autoimmune disorders.
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