July 23, 2018 – Resistant Cancer
Podcast: Download (Duration: 1:02 — 1.4MB)
Anchor lead: Modeling cancers over time may help predict resistance to treatment, Elizabeth Tracey reports
Using cells from head and neck cancers in conjunction with a mathematical model, Johns Hopkins researchers are able to develop a timeline over which cancer cells acquire resistance to therapy, a very important clinical milestone. Elana Fertig, senior author, explains.
Fertig: We created an experimental model where we monitored cells every single week as they acquired resistance to therapy. We did this by looking at which genes were changing over time, we coupled this with a new mathematical technique to visualize what’s going on in these very, very large datasets because you’re not measuring just one gene, you’re actually measuring tens of thousands of genes. So by merging those together we were able to figure out what were the molecular associations in this experimental model. :32
Fertig says such a system may help clinicians anticipate the development of resistance in patients and change therapies pre-emptively. She says a better understanding of the biology of resistance will result in new therapeutic targets. At Johns Hopkins, I’m Elizabeth Tracey.