Longitudinal Serum Protein Analysis of Women with a High Risk of Developing Breast Cancer Reveals Large Interpatient Versus Small Intrapatient Variations:First Results from the TESTBREAST Study

The prospective, multicenter TESTBREAST study was initiated with the aim of identifying a novel panel of blood-based protein biomarkers to enable early breast cancer detection for moderate-to-high-risk women. Serum samples were collected every (half) year up until diagnosis. Protein levels were longitudinally measured to determine intrapatient and interpatient variabilities. To this end, protein cluster patterns were evaluated to form a conceptual basis for further clinical analyses. Using a mass spectrometry-based bottom-up proteomics strategy, the protein abundance of 30 samples was analyzed: five sequential serum samples from six high-risk women; three who developed a breast malignancy (cases) and three who did not (controls). Serum samples were chromatographically fractionated and an in-depth serum proteome was acquired. Cluster analyses were applied to indicate differences between and within protein levels in serum samples of individuals. Statistical analyses were performed using ANOVA to select proteins with a high level of clustering. Cluster analyses on 30 serum samples revealed unique patterns of protein clustering for each patient, indicating a greater interpatient than intrapatient variability in protein levels of the longitudinally acquired samples. Moreover, the most distinctive proteins in the cluster analysis were identified. Strong clustering patterns within longitudinal intrapatient samples have demonstrated the importance of identifying small changes in protein levels for individuals over time. This underlines the significance of longitudinal serum measurements, that patients can serve as their own controls, and the relevance of the current study set-up for early detection. The TESTBREAST study will continue its pursuit toward establishing a protein panel for early breast cancer detection

Quantifying Protein Measurands by Peptide Measurements: Where Do Errors Arise?

Clinically actionable quantification of protein biomarkers by mass spectrometry (MS) requires analytical performance in concordance with quality specifications for diagnostic tests. Laboratory-developed tests should, therefore, be validated in accordance with EN ISO 15189:2012 guidelines for medical laboratories to demonstrate competence and traceability along the entire workflow, including the selected standardization strategy and the phases before, during, and after proteolysis. In this study, bias and imprecision of a previously developed MS method for quantification of serum apolipoproteins A-I (Apo A-I) and B (Apo B) were thoroughly validated according to Clinical and Laboratory Standards Institute (CLSI) guidelines EP15-A2 and EP09-A3, using 100 patient sera and either stable-isotope labeled (SIL) peptides or SIL-Apo A-I as internal standard. The systematic overview of error components assigned sample preparation before the first 4 h of proteolysis as major source (∼85%) of within-sample imprecision without external calibration. No improvement in imprecision was observed with the use of SIL-Apo A-I instead of SIL-peptides. On the contrary, when the use of SIL-Apo A-I was combined with external calibration, imprecision improved significantly (from ∼9% to ∼6%) as a result of the normalization for matrix effects on linearity. A between-sample validation of bias in 100 patient sera further supported the presence of matrix effects on digestion completeness and additionally demonstrated specimen-specific biases associated with modified peptide sequences or alterations in protease activity. In conclusion, the presented overview of bias and imprecision components contributes to a better understanding of the sources of errors in MS-based protein quantification and provides valuable recommendations to assess and control analytical quality in concordance with the requirements for clinical use

Metrological traceability in mass spectrometry-based targeted protein quantitation: A proof-of-principle study for serum apolipoproteins A-I and B100

Proteomic

Quantification of serum apolipoproteins A-I and B-100 in clinical samples using an automated SISCAPA–MALDI-TOF-MS workflow

Proteomic

Quantifying Protein Measurands by Peptide Measurements: Where Do Errors Arise?

Proteomic