Proteins are involved in a wide array of biological processes, from apoptosis to cellular checkpoints and inflammation, among others, all of which are pertinent to diseases ranging from cancer to neurodegenerative, cardiovascular, and infectious diseases (Chen et al., 2018). Consequently, investigating the proteome is crucial for understanding disease pathways and drug action mechanisms, and identifying novel therapeutic targets and noninvasive biomarkers for disease diagnosis, prognosis, and assessing treatment response.
The proteome is complex and dynamic, with protein expression, secretion, posttranslational modifications, and interactions, responding to stimuli and differing between tissues. Accurate proteome mapping therefore requires the analysis of biological samples across multiple pathological states and treatment phases, as well as analytical methods that are simple, rapid, cost-effective, highly reproducible and sensitive. Detection of low-abundant proteins, such as cytokines, angiogenic factors, growth factors, and proteases, is critical, given their central roles in signalling and their potential as therapeutic targets.
Mass spectrometry (MS) is the traditional method for proteome analysis due to its broad coverage, allowing the detection of several thousand proteins in a single liquid chromatography (LC)-MS/MS experiment (Ren et al., 2021). However, this approach requires expensive instrumentation and trained personnel for both sample handling and data analysis. Moreover, when applied to complex biological matrices such as human serum or plasma, high-abundance proteins like albumin and globulins can mask low-abundance proteins, limiting detection below low μg/ml or high ng/ml concentrations without extensive sample fractionation or enrichment to decrease the sample complexity (Ren et al., 2021; Vanarsa et al., 2020). Consequently, MS methods may be inadequate for detecting clinically relevant proteins, as many candidate biomarkers with clinical applicability are present at sub pg/ml to sub ng/ml levels (Ren et al., 2021). Although targeted MS methods have progressively improved sensitivity to reach detection limits of 50–100 pg/ml, their multiplexing capacity is often restricted to approximately 20–30 analytes per assay (Ren et al., 2021).
To address the limitations of MS-based approaches, immunoassay-based multiplex proteomics technologies have emerged as complementary tools to traditional proteomic methods. These technologies enable the rapid and simultaneous quantification of hundreds to thousands of proteins within a single assay while maintaining high sensitivity, requiring minimal sample preparation and allowing accessible data interpretation. They are derived from the enzyme-linked immunosorbent assay (ELISA), the most commonly used protein quantification technique in research environments and the clinical gold standard for single-analyte detection. ELISAs achieve detection limits of 1 to 10 pg/ml, without requiring sample pretreatment (Ren et al., 2021).
