This level of insight derived from understanding the genomic basis of metastatic tumors is crucial to moving toward a future where personalized medicine is the norm.

To this end, one of the most surprising things about the study was the high volume of patients that were eligible for this type of personalized medicine. “We were surprised that a large subset of patients — 42% — might be eligible for more personalized treatment based on tumor DNA characteristics,” Angus said.

Another surprise was that previous treatments can have a genetic impact. The study found that an earlier exposure to chemotherapy can leave behind a genetic scar that contributes significantly to the subsequent mutations found at metastasis.

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Dr Nik-Zainal said that in the days before WGS was as accessible a tool as it is today, the best they could do was rely on sequencing single mutations, which ultimately lent itself to an incomplete picture. “That single mutation does not operate on its own. It exists in a sea of other mutations that could also play a role in each individual’s tumor,” she said. But, “if you have the complete profile [from WGS], it’s like having a complete map, which will be able to get you to where you want to be, more efficiently. That is, to treat the patient most effectively from the start.”


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She also added that, on the flip side, it can help identify patients who won’t benefit from certain treatments because of their specific tumor genetics.

“It’s just as important to not waste resources,” she said. “And to not put patients through a ‘therapeutic’ process that may not help them at all.”

Disclosure: Three of the authors of the TNBC letter are inventors on a patent encompassing the code and intellectual principle of the HRDetect algorithm. HRDetect is a technology meant for the detection and analysis of homologous recombination deficiency signatures.

References

  1. Angus L, Smid M, Wilting SM, et al. The genomic landscape of metastatic breast cancer highlights changes in mutation and signature frequencies. Nat Genet. 2019;51(10):1450-1458.
  2. Staaf J, Glodzik D, Bosch A, et al. Whole-genome sequencing of triple-negative breast cancers in a population-based clinical study. Nat Med. 2019;25(10):1526-1533.