“These tumors actually becoming something that’s very, very different in response to therapy. And this allows them then to survive and adapt,” says David Goode, regarding current studies he’s leading on cancer, specifically prostate.
He adds that by changing cell type, these cancer cells evade treatment by altering what they need. He describes intricacies in cancer progression he’s learned through computational biology work that could inform better treatment.
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David Goode is group leader and faculty in the Computational Biology Program with the Peter MacCallum Cancer Center in Australia. His work engages the importance of genetics and evolution in cancer through bioinformatics, genomics, molecular evolution, and population genetics.
He and colleagues are trying to better understand the results of cancer evolution. They use mathematical models where they can stimulate tumor growth in simulations. This allows them to follow progressions and different mutations and clonal populations over changes in tumors at different points in time of therapy.
He gets specific about some of their cutting-edge techniques and research.
While they use whole genome sequencing or exome sequencing, he adds that, “single cell technologies are really powerful, and that’s something we are looking to move into where you can actually profile individual cells.” For now, they also utilize tools and analyses in their computational work to understand how tumors become resistant to therapies. He adds, “if we know that, then perhaps we can come up with better ways to treat patients that will prevent the tumors from becoming resistant in the first place.”
Listen in for more about this promising research.
Episode also available on Apple Podcasts: apple.co/30PvU9C