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Predicting breast cancer metastasis from whole-blood transcriptomic measurements

Permanent link
https://hdl.handle.net/10037/20356
DOI
https://doi.org/10.1186/s13104-020-05088-0
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Date
2020-05-20
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Holsbø, Einar; Perduca, Vittorio; Bongo, Lars Ailo; Lund, Eiliv; Birmelé, Etienne
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.

Publisher
BMC
Citation
Holsbø, Perduca, Bongo, Lund, Birmelé. Predicting breast cancer metastasis from whole-blood transcriptomic measurements. BMC Research Notes. 2020;13(1)
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