Predicting breast cancer metastasis from whole-blood transcriptomic measurements

BMC Res Notes. 2020 May 20;13(1):248. doi: 10.1186/s13104-020-05088-0.

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.

Keywords: Breast cancer; Epidemiology; Metastasis; Predictive models; Transcriptomics.

MeSH terms

  • Breast Neoplasms / blood
  • Breast Neoplasms / diagnosis*
  • Breast Neoplasms / genetics*
  • Breast Neoplasms / pathology
  • Case-Control Studies
  • Female
  • Gene Expression Profiling*
  • Humans
  • Middle Aged
  • Neoplasm Metastasis / diagnosis*
  • Norway
  • Prognosis