MSACL 2025 Abstract

Integrating Targeted Proteomics and Clinical Data for Early-Stage Breast Cancer Biomarker Discovery in Human Plasma

Kristrun Yr Holm (1, 2), Yassene Mohammed (6), Valdis Gunnarsdottir Þormar (2, 5), Finnur F. Eiriksson (3, 4), Christoph H Borchers (6), Sigridur Klara Bodvarsdottir (2, 5), Margret Thorsteinsdottir (1, 2, 3, 4)
(1) Faculty of Pharmaceutical Sciences, University of Iceland, Reykjavik, Iceland, (2) BioMedical Center, University of Iceland, Reykjavik, Iceland, (3) MassHei Core Facility, University of Iceland, Reykjavik, Iceland, (4) ArcticMass, Reykjavik, Iceland, (5) Faculty of Medicine, University of Iceland, Reykjavik, Iceland, (6) Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands, (7) Segal Cancer Proteomics Centre, Lady Davis Institute for Medical Research, McGill University, Montreal, Quebec, Canada

Kristrun Yr Holm, B.Sc. and M.Sc. (Presenter) University of Iceland

Presenter Bio: Ph.D. student in Health Sciences at the University of Iceland. My PhD research aims to discover early-stage biomarkers for breast cancer in human plasma samples using targeted quantitative proteomics and non-targeted metabolomic and lipidomic analysis. The PhD project is under the supervision of Prof. Margret Thorsteinsdottir, the leading authority on MS analysis in Iceland, and Dr. Sigridur Klara Bodvarsdottir, senior researcher at the Biomedical Center at the University of Iceland.

In 2020, I graduated with an M.Sc. degree in Medical Life Sciences at the University of Iceland. The M.Sc. program consisted of a 2-year project. The aim of my master’s project was to characterize the function of a mammalian-specific region of the essential autophagy gene, ATG7, utilizing human hepatocellular carcinoma cell lines. My master’s project was under the supervision of Dr. Margrét Helga Ögmundsdóttir.

In 2018, I graduated with a B.Sc. degree in molecular biology from the University of Iceland. During my bachelor studies, I did a 6-month bachelor project on assessing the phenotypic and functional effects of DLK1 overexpression in MDA-MB-231 cells and elucidate what role differential expression levels of DLK1 play for their oncogenic potential. This study was under the supervision of Dr. Gunnhildur Ásta Traustadóttir.

Relevant Financial Disclosures (within past 24 months, reported on Apr 22, 2026) No relevant financial relationship(s) to disclose. Conflict mitigation NOT REQUIRED.

INTRODUCTION:
Breast cancer (BC) is the most prevalent cancer in women 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. Blood-based biomarkers may offer an alternative minimally invasive strategy to improve BC screening, with better sensitivity than the routinely used X-ray mammography.

OBJECTIVES:
The objective of this study is to discover protein biomarkers in human plasma samples for early breast cancer diagnosis, with an emphasis on clinical variables.

METHODS:
An absolute quantification of 131 proteins was performed on 270 well-defined Icelandic biobank-based plasma samples, 135 BC patients, and 135 healthy controls by UPLC-MRM-MS assay. This Icelandic study cohort is well-defined with respect to BC subtypes, clinicopathological variables and BRCA germline mutations. Among the BC patients, 33% were from BRAC2 999del5 mutation carriers. The absolute quantification of the proteins was conducted using a PeptiQuantTM protein human kit, which contains synthetic light peptides and matching heavy peptides as an internal standard for each protein. Sample preparation prior to analysis was fully automated using the liquid handling robot coupled with a solid-phase extraction (SPE) unit, where plasma samples were proteolytically cleaved with trypsin, internal standards were added, and the samples concentrated by SPE. Peak area data was generated using Skyline Quantitative Analysis software (v22.2.0.351). Further data analysis was conducted using RStudio (v4.2.2), and SIMCA Pro 17 software was used for statistical analysis, multivariate data analysis, and machine learning.

RESULTS:
The targeted proteomics assay was successfully implemented for the absolute quantification of 131 proteins in human plasma samples with precision and accuracy for calibration standards and quality controls within 20% relative standard deviation. Out of the 131 proteins, 98 were quantifiable in the Icelandic bio-bank plasma samples, surpassing the lower limit of quantification. The samples were analyzed in eight batches, each containing matched pairs of cases and controls. Following data acquisition, the data was normalized, and minimal batch effects were corrected, ensuring accurate comparisons across all samples in downstream analysis. Considering the heterogeneous nature of BC, incorporating BC subtype, BRCA status, and clinicopathological variables such as tumor size, histological grade, and age appear to be important for assessing variations in protein concentrations. We detected several proteins that were significantly upregulated in BC cases, particularly in those with positive nodal metastasis, large tumors, and high histological grade. Other plasma proteins were found to be significantly downregulated in the Luminal B, triple-negative BC, HER-2 subtypes. Notably, two proteins were significantly downregulated in BRCA2 BC cases compared to both paired healthy controls and paired non-carrier BC patients, suggesting their potential as biomarkers for this specific mutation.

CONCLUSIONS:
Targeted proteomics using UPLC-MRM-MS demonstrates the potential for discovering and quantifying protein biomarkers in human plasma that could aid in the early detection of breast cancer, particularly in BRCA2 mutation carriers and subtypes such as Luminal B, triple-negative, and HER-2.