Personalized genetic treatments for metastatic breast cancer improve treatment outcomes for a subset of genomic alterations, according to a phase two clinical trial presented in Nature. The findings could help to guide treatment decisions based on genomics.
DNA sequencing techniques are widely used to assess specific genetic mutations that may have contributed to an individual developing cancer, with the aim of matching treatment to the individual. It is still unclear, however, how screening results might translate into daily clinical practice, notably when it comes to determining whether a patient might benefit from targeted therapy.
In a phase two clinical trial, Fabrice Andre and colleagues screened the genomes of 1,462 patients with metastatic breast cancer before randomizing 238 of them into two groups; patients who received maintenance therapy (ongoing treatment after a response to initial treatment; 81 individuals) and those who received therapy that was targeted to the specific genetic alterations with which they presented (157 individuals). The authors reveal that improved outcomes, as measured by progression-free survival, were seen in patients who received the targeted therapy if their genetic alterations were classified as level I or II (for which a drug matching the target alteration is ready for clinical use or has proven effective in preliminary studies, respectively) on the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT). Patients who presented with genomic alterations that led to a classification beyond level II (for which the efficacy of matched drugs has not yet been proven), on average, did not benefit from targeted treatment.
The authors conclude that this trial provides evidence for the benefits of using the ESCAT framework to guide treatment decisions for metastatic breast cancer based on patient-specific genetic data. However, they emphasize caution in interpreting the results, as many of the benefits seen in patients who received targeted therapy may have been the result of them presenting with BRCA1/2 mutations. A small sample size, they state, may also have limited considerations of other types of mutation.
Evolution: Group-living mammals may live the longestNature Communications
Education: Over one third of a year’s learning lost to COVID-19 pandemicNature Human Behaviour
Astronomy: Machine learning combs radio signals from spaceNature Astronomy
Animals: Cat-egorising play and genuine fighting in catsScientific Reports