Personalis (Nasdaq: PSNL) has published the PREDICT-DNA study in the Journal of Clinical Oncology, showing that its NeXT Personal test – an ultrasensitive circulating tumor DNA (ctDNA) blood test – outperforms current standard metrics in predicting patient outcomes following neoadjuvant therapy (NAT) for breast cancer.

The prospective study followed 227 patients with triple-negative (TNBC) and HER2+ breast cancer across more than 24 leading U.S. cancer centers. The headline findings: detectable ctDNA after neoadjuvant therapy was associated with a 4 to 9 times higher likelihood of relapse, and patients with detectable ctDNA up to 12 months post-surgery were more than 100 times more likely to experience disease recurrence.

Critically, ctDNA status was a stronger independent predictor of recurrence than pathologic complete response (pCR), nodal status, or tumor grade – the metrics clinicians currently rely on. Patients who cleared their ctDNA after treatment showed excellent outcomes regardless of whether residual disease was found at surgery.

“The PREDICT-DNA results show that if a patient clears their ctDNA, their outcomes are excellent even if residual disease is found at surgery,” said Dr. Ben Park, director of the Vanderbilt-Ingram Cancer Center. “Conversely, detectable ctDNA signals a very high risk. These insights allow us to more precisely risk-stratify breast cancer patients in future trials and clinical practice.”

A key technical detail: 55% of all ctDNA detections after neoadjuvant therapy occurred at levels below 100 parts per million – detections that would be missed by less sensitive tests. The NeXT Personal test tracks up to approximately 1,800 tumor-specific variants unique to each patient’s tumor, achieving sensitivity down to 1 to 3 parts per million.

For breast cancer patients this kind of precision in residual disease monitoring could meaningfully change how treatment decisions are made after neoadjuvant therapy, potentially sparing some patients from unnecessary additional treatment while flagging high-risk patients for earlier intervention.

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