Understanding the Role of Immunoaffinity-Based Mass Spectrometry Methods for Clinical Applications

Both ligand binding assays (LBA)2 and mass spectrometry (MS) methods are widely used in routine clinical analysis. In recent years, an interesting trend has emerged which blends these 2 techniques to combine the selectivity of immunoaffinity (IA) extraction with the specificity of MS detection (IA-MS). The brief communication by Laha and coworkers in the current issue of Clinical Chemistry, entitled “Characterizing Antibody Cross-reactivity for Immunoaffinity Purification of Analytes prior to Multiplexed Liquid Chromatography–Tandem Mass Spectrometry,” is an excellent example of the power of this combined approach (1). These authors, who have had previous experience with multiplexed liquid chromatography–tandem MS (LC-MS/MS) vitamin D analysis (2), showed that the limited specificity of an anti–1α,25-dihydroxyvitamin D capture antibody could be used with LC-MS/MS to deliver a sensitive, highly specific assay for 5 vitamin D–related metabolites. Because of differing affinities of the capture antibody for the various metabolites and their wide range in concentrations (1000-fold), Laha et al. performed a detailed binding assessment by LC-MS/MS using synthetic standards to verify the suitability of their approach. Moreover, because 2 known interfering metabolites were shown not to bind to the antibody, the authors were able to use a shorter chromatographic run time. The report by Laha et al. highlights the growing awareness about the need for highly specific assays in clinical biomarker analysis. Historically, lipids have been measured by competitive LBA formats. However, accumulating evidence has raised concerns about the specificity of these approaches, and several assays have been replaced by more specific LC-MS/MS methods. Testosterone analysis is probably the most widely recognized example of this trend (3). Still, although LC/MS/MS is a well-established tool for clinical biomarker analysis, comparatively few IA-MS applications have appeared for small molecules (4), and the uptake of IA-MS utilization is uncertain. Interestingly, the situation is entirely different for proteins. Clinical IA-MS methods have flourished, a trend linked to the widespread use of proteomic methods for biomarker discovery. IA capture, typically in the form of immunoprecipitation, is commonly used with targeted proteomic methods to simplify protein mixtures and/or to concentrate proteins before targeted MS analysis. This second property is important because antibodies can enrich a target protein as much as 1000-fold, allowing current MS methods to detect low-abundance proteins in clinically accessible samples (5). Indeed, several examples have been reported that use variations of IA-MS for protein biomarker quantification (6–8). In most cases, a surrogate peptide for the protein of interest, obtained by proteolytic digestion, is detected to provide greater sensitivity. An important variation of this technique, known as SISCAPA (stable isotope standards and capture by antipeptide antibodies) (9), uses antipeptide antibodies for enrichment following up-front enzymatic digestion. SISCAPA is particularly useful for analyzing large protein mixtures and has been extensively applied to the verification of disease-related biomarkers (10, 11). Because both methods incorporate stable isotope–labeled internal standards (SIL-IS) for the target peptide, good analytical precision is obtained. Despite evidence for success, not all IA-MS applications are justified. Given the cost and complexity of IA-MS, intelligent decisions must be made regarding deployment for clinical applications. So, how can one determine the best use of this rapidly evolving technology for clinical applications? To address this question, we must first analyze the relative strengths and limitations of the individual methods compared to the combined technique. In the section below, important attributes are evaluated for LBA, MS, and IA-MS methods. For the sake of this discussion, it will be assumed that MS-based methods use LC-MS/MS. Specificity, the cornerstone of any enduring clinical assay, has been a growing issue with LBA and a true advantage of IA-MS. As shown by Laha et al. (1), it is possible to use IA-MS to derive unparalleled specificity. Rank: IA-MS > MS > > LBA. Although LC-MS/MS is quite sensitive for many small molecules, ELISA assays for protein biomarkers are generally 10-fold more sensitive than IA-MS methods. Newer generation mass spectrometers continue to close this gap. Rank: LBA > IA-MS > MS. All of the methods listed have issues with matrix effects. For LBA this issue can generally be addressed with dilution, whereas MS methods address matrix effects by extraction, chromatography, and the use of SIL-IS. IA-MS combines IA selectivity and SIL-IS utilization. Rank: IA-MS > LBA, MS. Standard LBA methods are straightforward and can be readily transferred between different laboratories. MS methods can involve multiple extraction steps and may use chemical derivatization. IA-MS methods are also complex. Rank: LBA > IA-MS, MS. ELISA methods require significant time for reagent generation, and multiple antibodies must be screened to find suitable pairs. Although MS-based methods can be developed more quickly, substantial variation can occur depending on the nature of the analyte(s) involved. Rank: IA-MS, MS > LBA. For several MS methods the desired detection limits are reached by the use of large sample volumes. The use of exaggerated sample volumes (i.e., >100 μL) can be problematic for clinical trials in drug development owing to multiple demands for patient sampling. IA-MS has an advantage over MS in terms of sample enrichment. Rank: LBA > IA-MS > MS. A clear advantage exists for MS detection, for which at least 3 orders of magnitude are routinely achieved. IA-MS methods have lower dynamic ranges than MS methods. The limited dynamic range of LBA imposes the need for multiple dilutions during sample analysis, a situation improved by the use of electrochemiluminescence detection. Rank: MS > IA-MS > LBA. ELISA is the most expensive method owing to the cost associated with generating multiple antibodies. Although IA-MS methods use a single antibody, often 10-times more antibody is used per sample compared to LBA methods. Rank: MS > > IA-MS > LBA. The care, maintenance, and training associated with MS operation should not be underestimated. IA-MS adds additional complexity over MS. Rank: LBA > > MS > IA-MS. Although some LBA have overnight incubations, the parallel nature of plate readers vs the serial nature of LC-MS/MS is a significant advantage. IA-MS methods also require incubation, which lowers throughput. Rank: LBA > MS > IA-MS. The capacity for multianalyte analysis is a true advantage to MS methods and a way to offset the limitation of sample throughput. For proteins, MS is quickly becoming the preferred method for multianalyte analysis. MS is already the default for small molecule mixtures. Rank: IA-MS, MS > > LBA. The analysis presented in the preceding section suggests that IA-MS is best used to provide biomarker methods with specificity not achievable by LBA and to deliver target analyte enrichment superior to that of the conventional extraction methods associated with LC-MS/MS. The multianalyte capability of IA-MS methods is also used in most successful applications. Unfortunately, operational complexity and low throughput currently limit widespread clinical adoption of IA-MS methods. Although low sample throughput can be offset by multianalyte detection, analysis of multiple analytes is not needed in many clinical applications and in some cases can be prohibitively expensive. Certainly, IA-MS is well positioned as the evolving trend towards biomarker panels or molecular signatures continues. For protein biomarkers, we have found IA-MS to provide significant value during the early stages of clinical translation. In these situations, rapid development of fit-for-purpose assays, often for limited-analyte mixtures, can determine which proteins are essential to measure in clinical studies by use of more highly validated methods. Because sample throughput is not critical at this stage, IA-MS methods are quite practical to implement. Although IA-MS methods are certainly suitable for use in clinical trials, our preference has been to use IA-MS to help establish the specificity of ELISA methods. Given the growing access to MS technology, cross-validation will be a growing expectation for clinical methods for which LBA is used in drug development (12). The use of IA-MS for clinical applications is not a passing fad. To the contrary, we will see expanded applications to both large- and small-molecule biomarkers in the years ahead. However, despite expanding interest, IA-MS purveyors should pay attention to the need to address specific gaps. Among these is the frequent need for large sample volumes and preconcentration before analysis. As advances continue to occur in LC-MS technology, more methods will forego beads in favor of plate-based capture, similar to LBA. In addition to being more compatible with standard laboratory automation formats, smaller sample volumes will enable greater incorporation into clinical protocols. Innovation targeting increased LC-MS/MS throughput will also occur. Notable work in this area has already been undertaken by Grant and colleagues (13). Another trend will be a move away from nano-LC for protein quantification to micro-LC formats, which provide greater speed and robustness. Lastly, IA-MS requires a unique skill set, and it will be increasingly important to train scientists to achieve fluency in both LBA and MS technologies. Owing to historical differences, we should not underestimate this challenge. IA-MS has a bright future in the field of clinical chemistry. With careful consideration given to how IA-MS enables clinical biomarker workflow, we truly have the opportunity to capitalize on both the power and the promise of this technology. ligand binding assays mass spectrometry immunoaffinity liquid chromatography–tandem MS stable isotope standards and capture by anti-peptide antibodies stable isotope–labeled internal standard.