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Sensitive Detection of Minimal Residual Disease in Patients Treated for Early-Stage Breast Cancer.
Parsons, Heather A; Rhoades, Justin; Reed, Sarah C; Gydush, Gregory; Ram, Priyanka; Exman, Pedro; Xiong, Kan; Lo, Christopher C; Li, Tianyu; Fleharty, Mark; Kirkner, Gregory J; Rotem, Denisse; Cohen, Ofir; Yu, Fangyan; Fitarelli-Kiehl, Mariana; Leong, Ka Wai; Hughes, Melissa E; Rosenberg, Shoshana M; Collins, Laura C; Miller, Kathy D; Blumenstiel, Brendan; Trippa, Lorenzo; Cibulskis, Carrie; Neuberg, Donna S; DeFelice, Matthew; Freeman, Samuel S; Lennon, Niall J; Wagle, Nikhil; Ha, Gavin; Stover, Daniel G; Choudhury, Atish D; Getz, Gad; Winer, Eric P; Meyerson, Matthew; Lin, Nancy U; Krop, Ian; Love, J Christopher; Makrigiorgos, G Mike; Partridge, Ann H; Mayer, Erica L; Golub, Todd R; Adalsteinsson, Viktor A.
Afiliação
  • Parsons HA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts. viktor@broadinstitute.org HeatherA_Parsons@DFCI.HARVARD.EDU.
  • Rhoades J; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Reed SC; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Gydush G; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Ram P; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Exman P; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Xiong K; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Lo CC; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Li T; Boston University School of Public Health, Boston, Massachusetts.
  • Fleharty M; Division of Biostatistics, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Kirkner GJ; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Rotem D; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Cohen O; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Yu F; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Fitarelli-Kiehl M; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Leong KW; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Massachusetts.
  • Hughes ME; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Massachusetts.
  • Rosenberg SM; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Massachusetts.
  • Collins LC; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Miller KD; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Blumenstiel B; Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts.
  • Trippa L; Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, Indiana.
  • Cibulskis C; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Neuberg DS; Division of Biostatistics, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • DeFelice M; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Freeman SS; Division of Biostatistics, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Lennon NJ; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Wagle N; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Ha G; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Stover DG; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Choudhury AD; Division of Public Health Services, Fred Hutchinson Cancer Research Center, Seattle, Washington.
  • Getz G; Medical Oncology, Ohio State University Comprehensive Cancer Center, Columbus, Ohio.
  • Winer EP; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Meyerson M; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Lin NU; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Krop I; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Love JC; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Makrigiorgos GM; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Partridge AH; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.
  • Mayer EL; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
  • Golub TR; Koch Institute for Integrative Cancer Research at MIT, Cambridge, Massachusetts.
  • Adalsteinsson VA; Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
Clin Cancer Res ; 26(11): 2556-2564, 2020 06 01.
Article em En | MEDLINE | ID: mdl-32170028
ABSTRACT

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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Neoplasia Residual / Receptor alfa de Estrogênio / DNA Tumoral Circulante / Recidiva Local de Neoplasia Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans Idioma: En Revista: Clin Cancer Res Assunto da revista: NEOPLASIAS Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Neoplasia Residual / Receptor alfa de Estrogênio / DNA Tumoral Circulante / Recidiva Local de Neoplasia Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans Idioma: En Revista: Clin Cancer Res Assunto da revista: NEOPLASIAS Ano de publicação: 2020 Tipo de documento: Article