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Photo of Patrik Edén

Patrik Edén

Senior lecturer

Photo of Patrik Edén

Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors


  • Martin Sjöström
  • Johan Staaf
  • Patrik Edén
  • Fredrik Wärnberg
  • Jonas Bergh
  • Per Malmström
  • Mårten Fernö
  • Emma Niméus
  • Irma Fredriksson

Summary, in English

Background: Adjuvant radiotherapy is the standard of care after breast-conserving surgery for primary breast cancer, despite a majority of patients being over- or under-treated. In contrast to adjuvant endocrine therapy and chemotherapy, no diagnostic tests are in clinical use that can stratify patients for adjuvant radiotherapy. This study presents the development and validation of a targeted gene expression assay to predict the risk of ipsilateral breast tumor recurrence and response to adjuvant radiotherapy after breast-conserving surgery in primary breast cancer. Methods: Fresh-frozen primary tumors from 336 patients radically (clear margins) operated on with breast-conserving surgery with or without radiotherapy were collected. Patients were split into a discovery cohort (N = 172) and a validation cohort (N = 164). Genes predicting ipsilateral breast tumor recurrence in an Illumina HT12 v4 whole transcriptome analysis were combined with genes identified in the literature (248 genes in total) to develop a targeted radiosensitivity assay on the Nanostring nCounter platform. Single-sample predictors for ipsilateral breast tumor recurrence based on a k-top scoring pairs algorithm were trained, stratified for estrogen receptor (ER) status and radiotherapy. Two previously published profiles, the radiosensitivity signature of Speers et al., and the 10-gene signature of Eschrich et al., were also included in the targeted panel. Results: Derived single-sample predictors were prognostic for ipsilateral breast tumor recurrence in radiotherapy-treated ER+ patients (AUC 0.67, p = 0.01), ER+ patients without radiotherapy (AUC = 0.89, p = 0.02), and radiotherapy-treated ER- patients (AUC = 0.78, p < 0.001). Among ER+ patients, radiotherapy had an excellent effect on tumors classified as radiosensitive (p < 0.001), while radiotherapy had no effect on tumors classified as radioresistant (p = 0.36) and there was a high risk of ipsilateral breast tumor recurrence (55% at 10 years). Our single-sample predictors developed in ER+ tumors and the radiosensitivity signature correlated with proliferation, while single-sample predictors developed in ER- tumors correlated with immune response. The 10-gene signature negatively correlated with both proliferation and immune response. Conclusions: Our targeted single-sample predictors were prognostic for ipsilateral breast tumor recurrence and have the potential to stratify patients for adjuvant radiotherapy. The correlation of models with biology may explain the different performance in subgroups of breast cancer.


  • Breastcancer-genetics
  • BioCARE: Biomarkers in Cancer Medicine improving Health Care, Education and Innovation
  • Computational Biology and Biological Physics - Undergoing reorganization
  • Breast Cancer Surgery

Publishing year





Breast Cancer Research





Document type

Journal article


BioMed Central (BMC)


  • Cancer and Oncology
  • Radiology, Nuclear Medicine and Medical Imaging


  • Breast cancer
  • Gene expression
  • Ipsilateral breast tumor recurrence
  • Local recurrence
  • Nanostring
  • NCounter
  • Radioresistance
  • Radiosensitivity
  • Radiotherapy



Research group

  • Breast Cancer Surgery


  • ISSN: 1465-5411