Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics

Abstract

The rigorous testing of hypotheses on suitable sample cohorts is a major limitation in translational research. This is particularly the case for the validation of protein biomarkers; the lack of accurate, reproducible, and sensitive assays for most proteins has precluded the systematic assessment of hundreds of potential marker proteins described in the literature. Here, we describe a high-throughput method for the development and refinement of selected reaction monitoring (SRM) assays for human proteins. The method was applied to generate such assays for more than 1000 cancer-associated proteins, which are functionally related to candidate cancer driver mutations. We used the assays to determine the detectability of the target proteins in two clinically relevant samples: plasma and urine. One hundred eighty-two proteins were detected in depleted plasma, spanning five orders of magnitude in abundance and reaching below a concentration of 10 ng/ml. The narrower concentration range of proteins in urine allowed the detection of 408 proteins. Moreover, we demonstrate that these SRM assays allow reproducible quantification by monitoring 34 biomarker candidates across 83 patient plasma samples. Through public access to the entire assay library, researchers will be able to target their cancer-associated proteins of interest in any sample type using the detectability information in plasma and urine as a guide. The generated expandable reference map of SRM assays for cancer-associated proteins will be a valuable resource for accelerating and planning biomarker verification studies.

Fig. 1

Workflow outlining SRM assay generation, refinement and application to detect target proteins in plasma and urine. In the first step, a crude synthetic peptide library was used to generate QQQ full fragment ion spectra for the extraction of the preliminary coordinates for SRM assays (A). In the second step, SRM assays were refined by measuring the crude synthetic peptides in SRM mode using the coordinates established in full scan mode (B). This step refined the relative transition intensities specific for the SRM acquisition mode and the iRT in the chromatographic gradient to be used for endogenous peptide detection. The final SRM assay library was then used to detect the CAPs in complex samples (depleted plasma and urine) (C). Decoy transition groups and positive controls were included in the SRM measurements to allow for objective data analysis using the mProphet software tool (26).

Fig. 2

Number of peptides per protein in the SRM assay library for CAPs.

Fig. 3

Detectability results for depleted plasma and urine. Estimated protein concentrations for the CAPs in plasma were extracted from Human Plasma PA (41). The plotted concentration range shows detected CAPs (blue) and proteins that could not be detected (grey) in depleted plasma (A). Proteins detected by SRM were compared to proteins previously observed by large-scale proteomic experiments derived from Human Plasma PA (including measurements in crude and depleted plasma without additional fractionation) (B). Estimated protein concentrations for the CAPs in urine were extracted from Urine PA (41). The plotted concentration range shows detected CAPs (blue) and proteins that could not be detected (grey) in urine (C). Proteins detected by SRM were compared to proteins previously observed by large-scale proteomic experiments derived from Urine PA combined with protein observations from Adachi et al. (49) (D).

Fig. 4

Functional interaction network for pancreatic cancer. The diagram depicts functional interactions of the identified candidate cancer driver mutations for pancreatic cancer and the detectable cancer-associated proteins. Nodes represent CAPs (circles), CDMs (squares) and CDMs that are also reported cancer-associated on protein level (triangles). Colors denote the detectability of the proteins in plasma or urine: blue – detectable; pink – not detectable; grey – not targeted in plasma or urine. Functional interactions between the proteins are marked as edges. The figure was generated using Cytoscape (68).

Fig. 5

Quantification of selected proteins in plasma of ovarian cancer patients and patients with benign ovarian tumors. All proteins with a p-value below 0.01 and a fold-change larger than 1.1 were considered significant.