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dc.date.accessioned2021-10-27T20:05:54Z
dc.date.available2021-10-27T20:05:54Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/134635
dc.description.abstract© 2020 American Association for Cancer Research. Purpose: 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.
dc.language.isoen
dc.publisherAmerican Association for Cancer Research (AACR)
dc.relation.isversionof10.1158/1078-0432.CCR-19-3005
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourcePMC
dc.titleSensitive Detection of Minimal Residual Disease in Patients Treated for Early-Stage Breast Cancer
dc.typeArticle
dc.relation.journalClinical Cancer Research
dc.eprint.versionAuthor's final manuscript
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/PeerReviewed
dc.date.updated2021-06-14T15:32:13Z
dspace.orderedauthorsParsons, HA; Rhoades, J; Reed, SC; Gydush, G; Ram, P; Exman, P; Xiong, K; Lo, CC; Li, T; Fleharty, M; Kirkner, GJ; Rotem, D; Cohen, O; Yu, F; Fitarelli-Kiehl, M; Leong, KW; Hughes, ME; Rosenberg, SM; Collins, LC; Miller, KD; Blumenstiel, B; Trippa, L; Cibulskis, C; Neuberg, DS; DeFelice, M; Freeman, SS; Lennon, NJ; Wagle, N; Ha, G; Stover, DG; Choudhury, AD; Getz, G; Winer, EP; Meyerson, M; Lin, NU; Krop, I; Love, JC; Makrigiorgos, GM; Partridge, AH; Mayer, EL; Golub, TR; Adalsteinsson, VA
dspace.date.submission2021-06-14T15:32:14Z
mit.journal.volume26
mit.journal.issue11
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Needed


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