A practical approach to aid physician interpretation of clinically actionable predictive biomarker results in a multi-platform tumor profiling service.
Patients in whom the standard of care has failed or who have uncommon tumors for which no standard of care exists are often treated with drugs selected based on the physician's best guess. The rate of success for this method is generally low. With the advent of fast, affordable tumor profiling technologies, and a growth in the understanding of predictive biomarkers, it is now possible to identify drugs potentially associated with clinical benefit for such patients. We present the Caris approach to evidence-based tumor profiling and two patients with advanced ovarian and prostate cancer in whom standard of care had failed and tumor profiling identified an effective treatment schedule. To establish Caris Molecular Intelligence(TM) (CMI), over 120,000 clinical publications were screened and graded to characterize the predictive value of biomarkers that form the panel of tests. CMI includes multiple technologies to measure changes in proteins, ribonucleic acid, and deoxyribonucleic acid and proprietary software that matches the test results with the published evidence. The CMI results enable physicians to select drugs that are more likely to benefit the patients, avoid drugs that are not likely to work, and find treatment options that otherwise would not be considered. Worldwide, over 60,000 cancer patients have undergone evidence-based tumor profiling with CMI. In the cases reported in this article, CMI identified treatments that would not have been routinely used in the respective clinical setting. The clinical outcomes observed help to illustrate the utility of this approach.
Caris Life Sciences Basel, Switzerland.
Kenneth
K
Russell
Central Care Cancer Center Bolivar, MO, USA.
Leonid
L
Shunyakov
Arlington Cancer Center Arlington, TX, USA.
Karel A
KA
Dicke
Caris Life Sciences Phoenix, AZ, USA.
Todd
T
Maney
Caris Life Sciences Basel, Switzerland.
Andreas
A
Voss
biomarkers; evidence-guided; oncology; personalized medicine