The Rise of ctDNA, Part Two
Circulating tumor DNA profiling can yield new insights into early-stage lung cancer evolution
Michael Schubert |
What do we know about the early stages of lung cancer? Not much, because most cases are only diagnosed in late stages, once the symptoms have become unmistakable – and even relapses are often missed at first. Given that lung cancer is both the most common cancer worldwide and the leading cause of cancer death, it’s vital that we learn as much as we can about how the disease evolves – and what we may be able to do to detect and stop it early.
To that end, a group of researchers have performed circulating tumor DNA (ctDNA) profiling on the first 100 participants in the TRACERx (Tracking non-small cell lung Cancer Evolution through therapy) study, taking a tumor-specific, phylogenetic approach (1). What does that mean? The team were able to spot early predictors of ctDNA release, detect resistance to adjuvant chemotherapy, and identify patients likely to experience a relapse. But the method’s power doesn’t stop there – researchers were even able to keep track of the molecular profiles of recurrent and metastatic tumors, allowing them to observe the cancer’s evolution and potentially opening the door to future personalized treatments.
The science isn’t quite ready for prime time yet. Its sensitivity is constrained by tumor volume; the smallest tumors visible by standard imaging correlate with plasma ctDNA levels at the very extreme of current detection limits – and the cost of targeted ctDNA profiling is still a significant burden. But there’s a clear need to improve current treatments, whose success rates are low and toxicities high. If ctDNA profiling can provide insights into which patients are most likely to relapse and which cancers are most susceptible to chemotherapy, then as technologies improve and costs drop, we may one day be able to offer every lung cancer patient the treatment most likely to yield a cure.
- C Abbosh et al., “Phylogenetic ctDNA analysis depicts early stage lung cancer evolution”, Nature, [Epub ahead of print] (2017). PMID: 28445469.