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Predicting breast cancer metastasis from whole-blood transcriptomic measurements.
Holsbø, Einar; Perduca, Vittorio; Bongo, Lars Ailo; Lund, Eiliv; Birmelé, Etienne.
Afiliação
  • Holsbø E; Department of Computer Science, UiT - The Arctic University of Norway, Tromsø, Norway. einar.j.holsbo@uit.no.
  • Perduca V; Laboratoire MAP5 (UMR CNRS 8145), Université Paris Descartes, Université de Paris, Paris, France.
  • Bongo LA; Department of Computer Science, UiT - The Arctic University of Norway, Tromsø, Norway.
  • Lund E; Cancer Registry of Norway, Oslo, Norway.
  • Birmelé E; Department of Community Medicine, UiT - The Arctic University of Norway, Tromsø, Norway.
BMC Res Notes ; 13(1): 248, 2020 May 20.
Article em En | MEDLINE | ID: mdl-32434554
ABSTRACT

OBJECTIVE:

In this exploratory work we investigate whether blood gene expression measurements predict breast cancer metastasis. Early detection of increased metastatic risk could potentially be life-saving. Our data comes from the Norwegian Women and Cancer epidemiological cohort study. The women who contributed to these data provided a blood sample up to a year before receiving a breast cancer diagnosis. We estimate a penalized maximum likelihood logistic regression. We evaluate this in terms of calibration, concordance probability, and stability, all of which we estimate by the bootstrap.

RESULTS:

We identify a set of 108 candidate predictor genes that exhibit a fold change in average metastasized observation where there is none for the average non-metastasized observation.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Perfilação da Expressão Gênica / Metástase Neoplásica Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Perfilação da Expressão Gênica / Metástase Neoplásica Idioma: En Ano de publicação: 2020 Tipo de documento: Article