Breast cancer is a heterogeneous disease whose molecular diversity is not well reflected in clinical and pathological markers used for prognosis and treatment selection. As tumor cells secrete proteins into the extracellular environment, some of these proteins reach circulation and could become suitable biomarkers for improving diagnosis or monitoring response to treatment. As many signaling pathways and interaction networks are altered in cancerous tissues by protein phosphorylation, changes in the secretory phosphoproteome of cancer tissues could reflect both disease progression and subtype. To test this hypothesis, we compared the phosphopeptide-enriched fractions obtained from proteins secreted into conditioned media (CM) derived from five luminal and five basal type breast cancer cell lines using label-free quantitative mass spectrometry. Altogether over 5000 phosphosites derived from 1756 phosphoproteins were identified, several of which have the potential to qualify as phosphopeptide plasma biomarker candidates for the more aggressive basal and also the luminal-type breast cancers. The analysis of phosphopeptides from breast cancer patient plasma and controls allowed us to construct a discovery list of phosphosites under rigorous collection conditions, and second to qualify discovery candidates generated from the CM studies. Indeed, a set of basal-specific phosphorylation CM site candidates derived from IBP3, CD44, OPN, FSTL3, LAMB1, and STC2, and luminal-specific candidates derived from CYTC and IBP5 were selected and, based on their presence in plasma, quantified across all cell line CM samples using Skyline MS1 intensity data. Together, this approach allowed us to assemble a set of novel cancer subtype specific phosphopeptide candidates for subsequent biomarker verification and clinical validation.

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.