Development of a sequential workflow based on LC-PRM for the verification of endometrial cancer protein biomarkers in uterine aspirate samples

Oncotarget. 2016 Aug 16;7(33):53102-53115. doi: 10.18632/oncotarget.10632.


About 30% of endometrial cancer (EC) patients are diagnosed at an advanced stage of the disease, which is associated with a drastic decrease in the 5-year survival rate. The identification of biomarkers in uterine aspirate samples, which are collected by a minimally invasive procedure, would improve early diagnosis of EC. We present a sequential workflow to select from a list of potential EC biomarkers, those which are the most promising to enter a validation study. After the elimination of confounding contributions by residual blood proteins, 52 potential biomarkers were analyzed in uterine aspirates from 20 EC patients and 18 non-EC controls by a high-resolution accurate mass spectrometer operated in parallel reaction monitoring mode. The differential abundance of 26 biomarkers was observed, and among them ten proteins showed a high sensitivity and specificity (AUC > 0.9). The study demonstrates that uterine aspirates are valuable samples for EC protein biomarkers screening. It also illustrates the importance of a biomarker verification phase to fill the gap between discovery and validation studies and highlights the benefits of high resolution mass spectrometry for this purpose. The proteins verified in this study have an increased likelihood to become a clinical assay after a subsequent validation phase.

Keywords: biomarker verification; endometrial cancer; high resolution accurate mass spectrometry; parallel reaction monitoring; uterine aspirate.

MeSH terms

  • Base Sequence
  • Biomarkers, Tumor / metabolism*
  • Biopsy, Needle
  • Endometrial Neoplasms / metabolism*
  • Endometrial Neoplasms / pathology
  • Endometrium / metabolism*
  • Endometrium / pathology
  • Female
  • Humans
  • Mass Spectrometry / methods*
  • Proteomics / methods
  • Reproducibility of Results
  • Research Design*
  • Uterus / pathology


  • Biomarkers, Tumor