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Plasma-derived extracellular vesicle analysis and deconvolution enable prediction and tracking of melanoma checkpoint blockade outcome.
Shi, Alvin; Kasumova, Gyulnara G; Michaud, William A; Cintolo-Gonzalez, Jessica; Díaz-Martínez, Marta; Ohmura, Jacqueline; Mehta, Arnav; Chien, Isabel; Frederick, Dennie T; Cohen, Sonia; Plana, Deborah; Johnson, Douglas; Flaherty, Keith T; Sullivan, Ryan J; Kellis, Manolis; Boland, Genevieve M.
Afiliação
  • Shi A; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
  • Kasumova GG; Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Michaud WA; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
  • Cintolo-Gonzalez J; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
  • Díaz-Martínez M; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
  • Ohmura J; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
  • Mehta A; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
  • Chien I; Cancer Center, Massachusetts General Hospital, Boston, MA, USA.
  • Frederick DT; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
  • Cohen S; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
  • Plana D; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
  • Johnson D; Cancer Center, Massachusetts General Hospital, Boston, MA, USA.
  • Flaherty KT; Department of Medicine, Vanderbilt University, Nashville, TN, USA.
  • Sullivan RJ; Cancer Center, Massachusetts General Hospital, Boston, MA, USA.
  • Kellis M; Cancer Center, Massachusetts General Hospital, Boston, MA, USA.
  • Boland GM; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA. gmboland@partners.org manoli@mit.edu.
Sci Adv ; 6(46)2020 11.
Article em En | MEDLINE | ID: mdl-33188016

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Adv Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Adv Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos