Noninvasive tumor burden screening

An ultrasensitive method measures circulating tumor DNA (ctDNA), which allows ctDNA to be used as a noninvasive biomarker to quantify cancer burden in patients. This method is more useful than existing techniques, as it is less expensive, provides both high sensitivity, and can be used for patients with various different tumor genotypes, as long as recurrent mutation data is known for their tumor type.

Previously reported methods for next-generation sequencing (NGS) have been limited by their modest sensitivity, ability to apply only to a minority of patients, and need to be optimized specifically for each patient, along with the cost of that optimization. This method used a “selector” that marked pieces of DNA that target regions of DNA in the cancer of interest that are known to be recurrently mutated.

The work was led by Maximilian Diehn, MD, PhD, of Stanford University School of Medicine in Palo Alto, California, and colleagues. They used data from more than 400 patients to develop a sequencing approach that covers recurrent gene mutations in lung cancer.

With this method, they detected ctDNA with high specificity in all samples from another set of patients with stage II and advanced disease and half of the samples from stage I cancer patients. The measured amounts of ctDNA correlated with tumor volume during the course of therapy, identified patients with residual disease after treatment, and better detected response to therapy compared to radiographic methods.

The researchers stated that their method “is the first NGS-based method for ctDNA analysis that achieves both an ultralow detection limit and broad patient coverage at a reasonable cost.” They explained that, though they focused on non-small cell lung cancer, their method would work for any cancer that has data available on recurrent mutations.

As this method may also allow cancer screening and genetic identification of locally advanced and metastatic tumors without a biopsy, it could be used in the clinic for personalized cancer treatment. This work was reported in Nature Medicine (2014; doi:10.1038/nm.3519).

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