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Stanford Medicine Scope - June 14th, 2016 - by Krista Conger
I’ve written here before about advances made by Stanford researchers in detecting and sequencing tumor DNA circulating in the blood of cancer patients. It’s a revolutionary way to non-invasively determine how a solid cancer hiding deep within the body is responding to chemotherapy and to identify emerging mutations that may affect the course of therapy.
Now hematologist and oncologist Ash Alizadeh, MD, PhD, and radiation oncologist Maximilian Diehn, MD, PhD, have taken their technique, called CAPP-Seq, into the clinic to investigate how non-small cell lung cancers (the most common type of lung cancer) respond to drugs designed to inhibit the activity of the epidermal growth factor receptor, or EGFR. They published their study of 43 patients on Friday in Nature Communications.
As Diehn explained to me in an email:
In this study we use our CAPP-Seq ctDNA detection technology to study the clinically important problem of treatment resistance to personalized cancer therapy. Specifically, we found that lung cancer patients who become resistant to drugs that inhibit the epidermal growth factor receptor often harbor multiple resistance mechanisms, and that these patients do worse than others with only one such mechanism. Furthermore, we discovered a novel resistance mutation in EGFR that has never been described before.
Tracking the rise and fall of resistance mutations in real time provides a series of snapshots of tumor evolution and can help physicians decide whether a course of treatment is likely to be successful or if it would be better to switch to another medication to which the tumor is more likely to be sensitive. In studies in laboratory mice, the researchers found that attacking the tumor on multiple fronts simultaneously may be a good way to limit the development of further resistance and shrink tumor size.
As Alizadeh explained:
We show in animal models that simultaneous targeting of multiple resistance mechanisms is a promising strategy for overcoming the effect of tumor heterogeneity. This implies that, in the future, doctors could monitor mutations in a patient’s blood and personalize cocktails of medications to overcome resistance as it arises. Our findings underscore the clinical importance of tumor heterogeneity as well as the power of ctDNA analysis to address this problem.
