In:
Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 26, No. 11 ( 2020-06-01), p. 2556-2564
Kurzfassung:
Existing cell-free DNA (cfDNA) methods lack the sensitivity needed for detecting minimal residual disease (MRD) following therapy. We developed a test for tracking hundreds of patient-specific mutations to detect MRD with a 1,000-fold lower error rate than conventional sequencing. Experimental Design: We compared the sensitivity of our approach to digital droplet PCR (ddPCR) in a dilution series, then retrospectively identified two cohorts of patients who had undergone prospective plasma sampling and clinical data collection: 16 patients with ER+/HER2− metastatic breast cancer (MBC) sampled within 6 months following metastatic diagnosis and 142 patients with stage 0 to III breast cancer who received curative-intent treatment with most sampled at surgery and 1 year postoperative. We performed whole-exome sequencing of tumors and designed individualized MRD tests, which we applied to serial cfDNA samples. Results: Our approach was 100-fold more sensitive than ddPCR when tracking 488 mutations, but most patients had fewer identifiable tumor mutations to track in cfDNA (median = 57; range = 2–346). Clinical sensitivity was 81% (n = 13/16) in newly diagnosed MBC, 23% (n = 7/30) at postoperative and 19% (n = 6/32) at 1 year in early-stage disease, and highest in patients with the most tumor mutations available to track. MRD detection at 1 year was strongly associated with distant recurrence [HR = 20.8; 95% confidence interval, 7.3–58.9]. Median lead time from first positive sample to recurrence was 18.9 months (range = 3.4–39.2 months). Conclusions: Tracking large numbers of individualized tumor mutations in cfDNA can improve MRD detection, but its sensitivity is driven by the number of tumor mutations available to track.
Materialart:
Online-Ressource
ISSN:
1078-0432
,
1557-3265
DOI:
10.1158/1078-0432.CCR-19-3005
Sprache:
Englisch
Verlag:
American Association for Cancer Research (AACR)
Publikationsdatum:
2020
ZDB Id:
1225457-5
ZDB Id:
2036787-9
