A qualitative transcriptional signature to reclassify estrogen receptor status of breast cancer patients

Breast Cancer Res Treat. 2018 Jul;170(2):271-277. doi: 10.1007/s10549-018-4758-2. Epub 2018 Mar 23.

Abstract

Purpose: Immunohistochemistry (IHC) assessment of the estrogen receptor (ER) status has low consensus among pathologists. Quantitative transcriptional signatures are highly sensitive to the measurement variation and sample quality. Here, we developed a robust qualitative signature, based on within-sample relative expression orderings (REOs) of genes, to reclassify ER status.

Methods: From the gene pairs with significantly stable REOs in ER+ samples and reversely stable REOs in ER- samples, concordantly identified from four datasets, we extracted a signature to determine a sample's ER status through evaluating whether the REOs within the sample significantly match with the ER+ REOs or the ER- REOs.

Results: A signature with 112 gene pairs was extracted. It was validated through evaluating whether the reclassified ER+ or ER- patients could benefit from tamoxifen therapy or neoadjuvant chemotherapy. In three datasets for IHC-determined ER+ patients treated with post-operative tamoxifen therapy, 11.6-12.4% patients were reclassified as ER- by the signature and, as expected, they had significantly worse recurrence-free survival than the ER+ patients confirmed by the signature. On another hand, in two datasets for IHC-determined ER- patients treated with neoadjuvant chemotherapy, 18.8 and 7.8% patients were reclassified as ER+ and, as expected, their pathological complete response rate was significantly lower than that of the other ER- patients confirmed by the signature.

Conclusions: The REO-based signature can provide an objective assessment of ER status of breast cancer patients and effectively reduce misjudgments of ER status by IHC.

Keywords: Breast cancer; Estrogen receptor; Immunohistochemistry; Relative expression orderings.

MeSH terms

  • Algorithms
  • Biomarkers, Tumor*
  • Breast Neoplasms / genetics*
  • Breast Neoplasms / metabolism
  • Breast Neoplasms / mortality
  • Computational Biology* / methods
  • Databases, Genetic
  • Female
  • Gene Expression Profiling* / methods
  • Humans
  • Immunohistochemistry
  • Kaplan-Meier Estimate
  • Receptors, Estrogen / genetics*
  • Receptors, Estrogen / metabolism
  • Reproducibility of Results
  • Transcriptome*

Substances

  • Biomarkers, Tumor
  • Receptors, Estrogen