Kristrún Ýr Holm, Finnur Eiriksson, Yassene Mohammed, Christoph H Borchers, Sigridur Klara Boðvarsdottir and Margret Thorsteinsdottir
Introduction: Breast cancer (BC) is the most common cancer among women worldwide and ranks as the second leading cause of cancer-related deaths. Fortunately, the prognosis of BC is good when detected at an early stage, however, sensitive diagnostic tools for early detection of BC are vital for improving survival rates. This study aims to determine protein biomarkers with diagnostic and prognostic value in human plasma to improve early BC diagnosis.
Methods:
An absolute quantification of 131 proteins was performed on 279 well-defined Icelandic biobank plasma samples from 135 BC patients and 144 healthy controls using a PeptiQuant™ protein human kit and an UPLC-MRM-MS assay. Among the BC patients, 45 were BRCA2 mutation carriers. Prior to the UPLC-MRM-MS analysis, sample preparation was performed using a liquid-handling robot. Data analyses were conducted using Skyline Quantitative Analysis software for pre-processing of the data. SIMCA Pro-17, R studio, and Python were used for statistical analysis, multivariate data analysis, and machine learning.
Results: In the Icelandic study cohort, 99 proteins were quantified in the plasma samples with acceptable precision and accuracy. Results show a difference in protein composition between patients with sporadic BC and BRCA2 mutation carriers, with twenty proteins lower in concentration in plasma from BRCA2 mutation carriers. Furthermore, seven proteins showed the potential to discriminate BC patients with the luminal B subtype from controls.
Conclusions: Targeted proteomics using UPLC-MRM-MS shows potential for identifying and quantifying biomarkers in human plasma for diagnosis of BC in BRCA2 mutation carriers and for the luminal B subtype.
