Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays

Abstract

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers.

Keywords: Biomarker discovery; Biomarkers; Cancer; Mass spectrometry; Multiple reaction monitoring; Plasma or serum; Selected reaction monitoring; Targeted proteomics; Validation; Verification.

Figure 1

Schematic of the various stages of the biomarker pipeline. Modified from A) Rifai, et al. (Rifai et al., 2006) and B) Surinova, et al. (Surinova et al., 2011), and used with permission. Note that the definitions of the different stages are not always the same. We will be using the Surinova definitions in this review.

Figure 2

Schematic of a “bottom‐up” 1D or 2D LC/MRM‐MS workflow using SIS peptides or SIS proteins. Reproduced from Figure 1 of (Percy et al., 2013f), Bioanalysis 5(22), 2837–2856 (2013), with permission of Future Science Ltd.

Figure 3

Concentration range of proteins in plasma and in urine. A) Concentration range and detectability of cancer‐associated proteins (CAPs) in plasma and urine. A) The plotted concentration range shows detected CAPs (blue) and CAPs that could not be detected (gray) in depleted plasma. Estimated protein concentrations for the CAPs in plasma were extracted from Human Plasma PeptideAtlas (Farrah et al., 2011). B) Proteins detected by SRM were compared to proteins previously observed by large‐scale proteomic experiments derived from Human Plasma PA (including measurements in unfractionated, crude, and depleted plasma). C) The plotted concentration range shows detected CAPs (blue) and CAPs that could not be detected (gray) in urine. Estimated protein concentrations for the CAPs in urine were extracted from Urine PeptideAtlas (Farrah et al., 2011) D) 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. (Adachi et al., 2006). Figure and figure legend reprinted from (Huttenhain et al., 2012), with permission. B) Concentration ranges and functions for 70 plasma proteins. Reprinted from (Anderson and Anderson, 2002), with permission.

Figure 4

Peptide interference‐screening in control and patient plasma samples. A) In the control samples, 3 transitions per peptide are monitored in buffer and plasma (n = 2 for each sample type). The average relative ratios of the Q1/Q3 MRM ion pairs for the SIS peptide in buffer, the SIS peptide in plasma, and the NAT peptide in plasma) are determined, and the variability and assessment of peak shape, symmetry, and retention time are performed. B) Interferences can be detected through peptide relative response correlation plots for each protein. For the samples that deviate from linearity (see the sample marked with an arrow), the extracted ion chromatograms for each peptide need to be inspected to determine which peptide contains the interference. Figure and figure legend reprinted for Part A are reprinted, with permission, from (Percy et al., 2013b) and the figure and figure legend reprinted for part B are reprinted, with permission, from (Percy et al., 2013d).

Figure 5

Reproducibility of MRM analyses without SIS peptides, with an equimolar mixture of SIS peptides, and with a concentration‐balanced mixture of SIS peptides.

Figure 6

Serum concentrations of A1BG, LRG1 as determined by MRM‐MS, and their associations with NSCLC and the effect of using both proteins together as biomarkers. A–B) MRM Intensities of selected reference peptides of A1BG and LRG1 both showed good linear correlation with on‐column abundance. The x‐axis represents base‐3 logarithm of ratios of spiked light and heavy isotopic peptides, with the y‐axis corresponding to the observed peak area ratios in base‐3 logarithmic scale. Red triangles suggest the limit of linear quantification (LOQ) of each peptide. Note that these two peptides were used to report the absolute concentration, with comparison to another two less‐optimal peptides shown in Figure S4. C–D) The chromatography peaks of the best transitions of two peptides for A1BG and LRG1. Note that the Signal‐to‐Noise ratios are sufficient for quantification. E) The distribution of serum levels of A1BG and LRG1 between cancer and control groups. F) ROC analysis suggested over‐expressed A1BG and LRG1 were associated with NSCLC and their combined panel could provide the better discriminative performance than each of the protein. Figure and figure legend are reprinted from (Liu et al., 2012), with permission.

Figure 7

Schematic of a phosphatase‐based phosphopeptide quantitation (PPQ) experiment. Proteins are digested with trypsin and isotope‐labeled standard peptides (non‐phosphorylated forms of target) are added (light gray) to increase accuracy of quantitation and specificity of detection. The sample is split into two and buffer‐only or phosphatase treated. Two LC/MRM‐MS analyses are then performed. Phosphatase treatment will increase the signal of the natural peak (dark) if phosphorylation is present. Peak area ratios are then determined from the area of the natural peak (dark) versus the area of the internal standard (light gray). Phosphorylation stoichiometry can then be determined by comparing the Peak area ratios from the untreated and phosphatase treated samples as indicated in the boxed formula (assuming 100% dephosphorylation efficiency). Figure and figure legend are reprinted from (Domanski et al., 2010), with permission.

Figure 8

A comparison of IP‐MRM with ELISA for the quantitation of 6 colon cancer biomarker candidates. Response curves for IP‐MRM analyses of recombinant TIMP1, COMP, MMP9, THBS2, MSLN and ENG proteins. Proteins were spiked at 10L640 ng/mL in a background matrix of 60 mg/mL BSA in DPBS and analyzed by IP‐MRM as described in Experimental Procedures. Values plotted are mean ± standard deviation (n = 3). Figure and figure legend reprinted from (Lin et al., 2013), with permission.