Höfundar:
Kristrún Ýr Holm, Magnús Gauti Úlfarsson, Kari Arnarson, Finnur Freyr Eiríksson, Yassene Mohammed, Christoph H Borchers, Sigríður Klara Böðvarsdóttir, Margrét Þorsteinsdóttir
Introduction: Breast cancer (BC) is the most prevalent cancer among women worldwide and the second leading cause of cancer deaths. The x-ray mammography is the most common screening method for early detection of BC. However, often in the early stages of BC development the tumor is not visible on these mammographs. It is therefore a need for more sensitive diagnostic tool for early detection of BC. The aim of this study is to search for novel biomarkers in human plasma by targeted proteomics to improve early BC diagnosis.
Methods: 131 proteins were quantified in 394 bio-bank plasma samples, 197 samples from BC cases and 197 samples from healthy controls, using PeptiQuant protein human plasma assay kit with UPLC-MRM-MS/MS analysis. Prior to analysis the plasma samples were proteolytically cleaved and concentrated by solid-phase extraction using liquid handling robot. Data analysis was conducted using Skyline Quantitative Analysis software, R studio and SIMCA Pro-17 for multivariate data analyzing.
Results: The targeted MRM proteomic assay was successfully implemented for quantification of 131 proteins in 394 human plasma samples. Out of the 131 proteins 105 proteins were quantifiable in the bio-bank plasma samples with acceptable precision and accuracy. Preliminary results indicate a potential difference in protein composition between plasma samples from BC patients and controls. Further data analysis is being conducted using computational methods such as machine learning for interpretation of the data.
Conclusions: Preliminary results using multivariate data analysis indicate a difference in protein composition between plasma samples from BC patients and controls.
