Using ctDNA to Predict Cancer Recurrence and Guide Therapy Selection

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A ctDNA testing method has the capability to predict cancer recurrence, which could help guide therapy selections and uncover new drug development opportunities.
A ctDNA testing method has the capability to predict cancer recurrence, which could help guide therapy selections and uncover new drug development opportunities.

An innovative new means of identifying circulating tumor DNA (ctDNA) targets in plasma is offering the promise of custom-designed, patient-specific cancer detection, taking liquid biopsy testing into a new era of personalized medicine with the potential for recognizing disease recurrence months ahead of radiographic imaging.

The capability of the new ctDNA detection method has been demonstrated in a variety of cancers including breast, bladder, colorectal, and non-small cell lung cancers, and a study of its efficacy to predict recurrence in patients diagnosed with kidney cancer is currently underway.1

Data presented at the American Association for Cancer Research Annual Meeting 2018 in Chicago, Illinois, showed that the ctDNA analyses can “inform on treatment response and identify disease recurrences up to 265 days earlier than radiographic imaging” in patients with bladder cancer.2

A separate study of 130 colorectal cancer patients detected molecular relapse a median of 7.9 months ahead of clinical relapse.3

Developed by the genetic testing company Natera and released for research use only under the brand name Signatera™, the technology uses whole-exome next-generation sequencing data from a patient's tumor to create multiplex-polymerase chain reaction (PCR) assay panels tailored to that individual, which, as the authors of a 2017 study wrote, targets “clonal and subclonal single-nucleotide variants (SNVs) selected to track phylogenetic tumour branches in plasma.”4

The method increases the likelihood of detection by targeting 16 or more mutations in the tumor tissue. Researchers can specify as many as several hundred additional tumor signatures to track.

The 2017 study, published in Nature, analyzed postoperative plasma in 100 non-small cell lung cancer patients to detect residual disease and tumor response to treatment, with the goal of identifying patients who were most likely to experience relapse. Patient follow-ups occurred every 3 months for the first 2 years after surgery, and then every 6 months after that.

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