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Åke Borg

Åke Borg

Principal investigator

Åke Borg

Clinical Value of RNA Sequencing–Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network—Breast Initiative


  • Christian Brueffer
  • Johan Vallon-Christersson
  • Dorthe Grabau
  • Anna Ehinger
  • Jari Häkkinen
  • Cecilia Hegardt
  • Janne Malina
  • Yilun Chen
  • Pär-Ola Bendahl
  • Jonas Manjer
  • Martin Malmberg
  • Christer Larsson
  • Niklas Loman
  • Lisa Rydén
  • Åke Borg
  • Lao H. Saal

Summary, in English

In early breast cancer (BC), five conventional biomarkers—estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), Ki67, and Nottingham histologic grade (NHG)—are used to determine prognosis and treatment. We aimed to develop classifiers for these biomarkers that were based on tumor mRNA sequencing (RNA-seq), compare classification performance, and test whether such predictors could add value for risk stratification.

In total, 3,678 patients with BC were studied. For 405 tumors, a comprehensive multi-rater histopathologic evaluation was performed. Using RNA-seq data, single-gene classifiers and multigene classifiers (MGCs) were trained on consensus histopathology labels. Trained classifiers were tested on a prospective population-based series of 3,273 BCs that included a median follow-up of 52 months (Sweden Cancerome Analysis Network—Breast [SCAN-B], identifier: NCT02306096), and results were evaluated by agreement statistics and Kaplan-Meier and Cox survival analyses.

Pathologist concordance was high for ER, PgR, and HER2 (average κ, 0.920, 0.891, and 0.899, respectively) but moderate for Ki67 and NHG (average κ, 0.734 and 0.581). Concordance between RNA-seq classifiers and histopathology for the independent cohort of 3,273 was similar to interpathologist concordance. Patients with discordant classifications, predicted as hormone responsive by histopathology but non–hormone responsive by MGC, had significantly inferior overall survival compared with patients who had concordant results. This extended to patients who received no adjuvant therapy (hazard ratio [HR], 3.19; 95% CI, 1.19 to 8.57), or endocrine therapy alone (HR, 2.64; 95% CI, 1.55 to 4.51). For cases identified as hormone responsive by histopathology and who received endocrine therapy alone, the MGC hormone-responsive classifier remained significant after multivariable adjustment (HR, 2.45; 95% CI, 1.39 to 4.34).

Classification error rates for RNA-seq–based classifiers for the five key BC biomarkers generally were equivalent to conventional histopathology. However, RNA-seq classifiers provided added clinical value in particular for tumors determined by histopathology to be hormone responsive but by RNA-seq to be hormone insensitive.


  • Breastcancer-genetics
  • Translational Oncogenomics
  • Personalized Breast Cancer Treatment
  • The Liquid Biopsy and Tumor Progression in Breast Cancer
  • Surgery
  • Division of Translational Cancer Research
  • Tumor Cell Biology
  • BioCARE: Biomarkers in Cancer Medicine improving Health Care, Education and Innovation
  • Tumor microenvironment
  • Surgery (Lund)
  • Breast Cancer Surgery
  • Familial Breast Cancer
  • EpiHealth: Epidemiology for Health

Publishing year







JCO Precision Oncology



Document type

Journal article


American Society of Clinical Oncology


  • Cancer and Oncology
  • Bioinformatics (Computational Biology)
  • Bioinformatics and Systems Biology


  • breast cancer
  • biomarker
  • prediction
  • machine learning




  • RNA sequencing for molecular diagnostics in breast cancer
  • Sweden Cancerome Analysis Network - Breast (SCAN-B): a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine

Research group

  • Translational Oncogenomics
  • Personalized Breast Cancer Treatment
  • The Liquid Biopsy and Tumor Progression in Breast Cancer
  • Surgery
  • Tumor Cell Biology
  • Breast Cancer Surgery
  • Familial Breast Cancer


  • ISSN: 2473-4284