Review Article
New Strategies to Categorize Blood for Proteomic Biomarker Discovery
Matthew Kuruc*, Haiyan Zheng, Amenah Soherwardy, Sowmya Avadhani, Devjit Roy, Ingrid M Verhamme and Swapan Roy
Corresponding Author: Matthew Kuruc, Biotech Support Group LLC, 1 Deer Park Drive, Suit M, Monmouth Junction NJ 08852 USA
Received: March 04, 2020; Revised: July 27, 2020; Accepted: March 18, 2020
Citation: Kuruc M, Zheng H, Sowerhardy A, Avadhani S, Roy D, et al. (2020) New Strategies to Categorize Blood for Proteomic Biomarker Discovery. Proteomics Bioinformatics, 2(2): 90-107.
Copyrights: ©2020 Kuruc M, Zheng H, Sowerhardy A, Avadhani S, Roy D, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Although much effort has gone into genomic sequencing to define disease, the downstream products of gene sequences-proteins, nevertheless remain the master regulators of biology via their interactions with nucleic acids and other macromolecules. Many proteins are measurable in blood, making it a rich resource for biomarkers. Yet for reasons largely unrelated to analytical limitations, this resource remains largely untapped. In this review, we describe how chronic illness manifests itself in blood and how we might study innate immunity to understand mechanisms that can potentially translate into new biomarkers and therapeutic modalities. We draw upon our own knowledgebase of proteome information reportable after using depletion or enrichment products in LC-MS/MS workflows and how this knowledge can be utilized in new strategies for biomarker discovery from blood samples. We note that BSG’s products have simply and efficiently reduced the complexity of the serum proteome allowing for cost-effective workflows, without the use of antibody-based depletion methods. Finally, we discuss how patterns of Serpins, a superfamily of protease inhibitors, may serve as a surrogate measure of the progressive stages of the innate immune systems’ response to both infectious and non-infectious disease. This convergence of strategies and LC-MS/MS technologies has made the task immediately available to investigators to now develop the next generation of molecular tests for more precise and personalized treatment of patients.


Blood is the body’s vehicle for the accumulative evidence of pathological insults for diseases. Secreted proteins, extracellular vesicles and circulating blood cells mediate individualized homeostasis via intercellular communication, immune responses, vascular and endothelial cell function, tissue remodelling, fluid exchange and nutrient assimilation [1]. Thus, plasma/serum proteins and other circulating factors directly regulate complex processes such as aging and the development of common chronic diseases. Most diseases are multi-factorial with many proteins collectively acting within highly regulated networks-even single gene diseases can be at the centre of larger, complex regulatory networks.

As such, a disease state results whenever this protein network becomes dysregulated over long periods via a confluence of heredity, lifestyle, or environmental stimuli. Because blood mediates coordination between nonadjacent tissues, it is essential to understand how this dysregulation manifests itself, regardless of the underlying causative factors. Quantitative proteomics from blood can help unravel these regulatory elements. Yet, extracting and characterizing functional changes and adaptations to disease for many of even the highest abundance proteins in circulation remains limited. We therefore propose new strategies to support proteomic analysis of blood.

Proteins in blood can be separated into four main compartments-red cells, white cells, platelets and plasma (Figure 1). Serum differs from plasma primarily in the amount of Fibrinogen, however, for purposes of this review, the concepts proposed herein consider that proteome information derived from serum or plasma would be similar.

For that reason, the terms are used interchangeably here.

In this review, we describe how blood cells release inflammatory cargo proteins, disrupting the delicate balance necessary for normal homeostasis. More precisely, information about the function and communication between proteins and blood cells will ultimately be the best possible information that can be derived to understand disease states [1]. Consequently, proteomic biomarker panels from blood will become highly beneficial, as blood is a relatively non-invasive sample type that can be monitored longitudinally throughout a lifetime (Figure 2).

Blood proteomic analysis (e.g., by LC-MS/MS) does however, have inherent challenges. Serum proteomics can be especially challenging for two reasons: 1) the presence of highly abundant proteins, e.g., albumin alone accounts for about 50% of the total protein mass and 2) immunoglobulins, a proteolytically resistant protein family. Several sample preparation strategies are used to address these challenges, most of which employ the use of immuno-affinity depletion to remove one or more high abundance proteins. Common limitations of immuno-affinity however are high costs, regeneration requirements, which may result in a diminished and inconsistent performance and a required marriage of species to antibody. Because of these limitations, Biotech Support Group (BSG) has developed products and methods that are not based on immuno-affinity, but rather are derived from non-biological bead-based chemistries. These have proven advantageous in a variety of LC-MS/MS workflows [2-6].

With some modest adjustments, Viaralet et al. [5] concluded that the BSG product - AlbuVoid™ - proved to be faster and more cost-effective than antibody-based methods to improve quantitative clinical proteomics. Furthermore, BSG’s HemoVoid™ proved especially useful for annotating erythrocytes in the human proteome project to identify additional proteins and N-termini; 778 proteins were identified from the cytosolic fraction, 171 of which were not represented in either the soluble non-depleted fraction or the membrane fraction [6]. Based on BSG’s internal investigations, we have accumulated data that encompasses greater than 1000 serum proteins that can be observed by LC-MS/MS, and categorically characterized with respect to the proposed strategy described here (Tables 1, 2 and 3).

While acknowledging some exceptions, notably C-reactive protein (CRP) or antibodies, consequential changes in the blood proteome are not necessarily derived from tissue leakage, but rather from proteolytic modifications, presumably driven in large part by inflammatory release of blood’s cellular protein cargo. Within the coagulation/complement axis, many proteins circulate as inactive precursors (zymogens) and only become active upon proteolysis. Once activated, protein sub-forms then become ligands for cell receptors, substrates for other proteases in cascading sequences, or interacting partners for regulating mechanisms involving all blood cells, vessel walls and vasculature, along with other plasma co-factors (i.e., lipids, Heparins, metal cations, etc.). For these reasons, we examine new ways to observe and measure such categorical and functional responses to inflammatory disease and related disorders.

Unlike proteins from tissue, the vast majority of proteins contained in blood, either cellular or humoral (extracellular), are quite constant; blood’s cellular content being derived either from cells without nuclei (red cells and platelets) or from those with lobed nuclei with limited new protein production capacity (neutrophils). Thus, differential changes are derived from a host’s systemic response to many varieties of environmental stimuli (both infectious and non-infectious), not from altered gene expression. As such, we make the case in this paper for proteomic analysis of blood to become a discipline of categorical classification and functional metrics, rather than a discipline of finding the exceedingly low concentration (<

Furthermore, categorical metrics have the advantage of monitoring proteins in a highly observable LC-MS/MS concentration range, ≥ 0.1 µg/ml in most cases.

This new strategy, to represent proteome information within categories, is designed to derive characteristic patterns, rather than single biomarkers, that can support clinical manifestations of disease or response to medical intervention. By categorical classification, we hope to gain a much deeper understanding of the molecular relationships that are shared amongst apparently distinct pathological phenotypes. This would help explain, for example, the increased risk of cancer in patients with inflammatory bowel disease, or the apparent link between Rheumatoid arthritis or lupus with increased risk of blood clots. Finally, once we understand these shared relationships, we hope to address therapies that may have been developed for one clinical condition and apply them towards other clinical phenotypes, with biomarkers that can help guide selection and utility.


While important, we have purposely left out the influence of the red cell proteome. This is because there is limited information on the role of erythrocytes, with notable exceptions (i.e., Paroxysmal nocturnal haemoglobinuria), in the central theme of this review, namely, the orchestration of the innate immune response.



Innate immunity refers to first-line, non-specific defense mechanisms that come into play immediately or within hours of a perceived pathogenic insult in the body. The innate immune response consists of physical, chemical and cellular defences against pathogens. Its main purpose is to immediately prevent the spread and movement of foreign or non-self-pathogens throughout the body and to initiate the second line of defence, the adaptive or acquired immune response. As a second-line defense, the adaptive response occurs downstream from the innate immune response and starts transferring immunological longer term memory towards the non-self-pathogens. So a normal resolution of the innate response leads to a productive handoff to the adaptive response. Conversely, an unresolved innate response may delay or confound a suitable adaptive response, with both acute and chronic disease consequences.

Taken together, the human immune system has evolved to adapt and respond to a variety of physical insults and never-ending exposure to infectious agents to survive. While the emergence of COVID-19 reminds us that infectious insults remain a large healthcare threat, mankind’s pharmacological skills (e.g., antibiotics, vaccines, etc.) has largely eliminated many infectious insults of the past. As a result, we are able to live longer than our predecessors. Unfortunately, our pharmacopeia and inflammatory response systems are not sufficiently capable of fending off today’s longer-lifetime exposure to environmental and lifestyle insults that we now face. These exposures and insults contribute to chronic inflammation which, over time, are manifested in a variety of pathological conditions, including an important link between the coagulation and innate inflammatory system [7, 8].


Thrombo-inflammation describes a process by which the activation of coagulation assists the function of the innate immune system and, conversely, components of the immune system contribute to thrombosis. Thus, the innate immune system is an integrated triangulated network that when functioning properly provides steady state control of pathways involved with coagulation, complement and leukocyte recruitment (Table 4 and Figure 3). Any dysregulation within one affects the others and so collectively, a dysregulated innate immune system can contribute to the genesis of many acute and chronic pathologies. For example, chronic inflammation is widely recognized as a potential contributor to cancer and many progressive debilitating diseases (e.g., inflammation due to H.pylori leads to stomach lesions and cancer). As witnessed with COVID-19, the pre-existing inflammatory status, may be a key factor to the acute severity of disease upon exposure to infectious pathogens.

Because the innate immune system does not change genetically over time, measuring panels of its protein level orchestration is a worthwhile goal of proteomic investigation. Because of the many feedback signals necessary to maintain steady state within the network, therapeutically modulating even one rogue component may ultimately unwind the overall dysregulation and contribute to longer term management of the disease. For these reasons, we have focused this review on key regulatory elements of innate immunity that can be observed, reported and surveyed by proteomic analysis of serum/plasma. Within this model system, we describe protein contributions from each pathway and new strategies for proteomic categorization, function and disease characterization.

White blood cells (WBCs, also called leukocytes) are the cells of the immune system that are rapidly recruited to protecting the body against both infectious disease and perceived environmental insults. When anti-coagulated whole blood is centrifuged in collection tubes, the white blood cells (WBCs) form a thin, white layer of cells (the buffy coat;) between the sedimented red blood cells (erythrocytes) and plasma (see tube in Figure 1). WBCs make up approximately 1% of the total blood volume in a healthy adult, substantially less numerous than the red blood cells (about 45%). Having nuclei distinguishes WBCs from the enucleated red blood cells (RBCs) and platelets, yet, even with nuclei, most are terminally differentiated and do not undergo cell division in the bloodstream. White blood cells are composed of differentiated constituents, each having specific functions. Neutrophils are the most abundant white blood cell, constituting 60-70% of the circulating leukocytes and they thus contribute to the observable blood proteome much more so than the rest of the white blood cell constituents combined. Neutrophils have extensive crosstalk with each of the major blood cell subsets (megakaryocyte/platelets, myeloid and lymphoid) and other extracellular soluble proteins contained in plasma, further magnifying their importance in health and disease.

For example, changes in circulating leukocytes including the ratios of neutrophils-to-lymphocytes (NLR), monocytes-to-lymphocytes (MLR) and platelets-to-lymphocytes (PLR), have been used to predict tumor occurrence and prognosis [10]. During the beginning (acute) phase of inflammation, neutrophils migrate to the site of inflammation, particularly as a result of infection, environmental stimuli, or onset of cancer. Inflammation follows chemotactic signals such as Interleukin-8 (IL-8), C5a from Complement activation, as well as other peptides and small molecules. Neutrophils, as “first responders” release a variety of proteases (i.e., Elastase) to remodel the extracellular matrix of the tissues to which they migrate.

Once arrived, neutrophils then release granule proteins and/or chromatin (DNA & histones) to form an extracellular fibril matrix known as Neutrophil extracellular traps (NETs). Such NET release has been observed to occur not only during acute (bacterial or viral) inflammation but also in numerous pathological conditions, such as autoimmune diseases, vascular diseases, and cancer [11]. In addition to NETs, neutrophil granules can be secreted extracellularly (released cargo) in response to localized immunological stimuli. As neutrophils have limited capacity for de novo protein synthesis, this released cargo thus becomes a subset proteome that collectively reflects a weighted average of cell maturities and the inflammatory stimulus that triggered the release. These released proteins can be observed and reported in the general blood circulation (many in our BSG serum knowledgebase, see Table 1).

Platelets are rapidly deployed to sites of injury or infection, and can modulate inflammatory processes by interacting with neutrophils, forming platelet-neutrophil aggregates. Platelets play a central role in innate immunity, initiating and participating in multiple inflammatory processes, operating in parallel with their better known clotting function. Platelets contain dense granules, alpha granules and cytosolic proteins; granule secretion being pivotal to establishing and controlling the microenvironment at the local inflammatory site.

Granule cargo release is both contextual and kinetically controlled, mediating early activation, or persisting long after the initial stimuli. Persistence of Platelet-released along with Neutrophil-released cargo in unresolved chronic inflammation, necessitates a systemic response to regulate their effects, proteolysis being the most deleterious [12].

Granule characteristics

1. α granules (alpha granules) – contents include insulin-like growth factor 1, transforming growth factor beta (TGF-β), platelet factor 4, and other clotting proteins (such as thrombospondin, fibronectin, factor V, and von Willebrand factor) [13].

2. δ granules (delta or dense granules) – contents include adenosine di- & tri-phosphates, proteins, and the majority of platelet calcium, an essential co-factor in the coagulation cascade [13].

Like neutrophil granule cargo, this released cargo thus becomes a subset proteome that collectively reflects the inflammatory stimulus that triggered the release. Released protein cargo from these different granules thus forms a signature characteristic of inflammatory responses that can be observed in serum and reported (Table 1). Differences in quantitative elements from one granule vs. another may be informative as to the relative weight that one granule type cargo has to a particular disease phenotype. The released cargos from both neutrophils and platelets simultaneously imparts their net effects on the third component of the triangulated network – the complement cascade.



The complement cascade is a major component of the immune system that provides powerful host surveillance and protection from invading microbes. Comprising about 5% of the total protein mass in plasma (Figure 1 and Table 2), most complement proteins circulate in blood as inactive precursors (zymogens); when triggered, these zymogens become activated through proteolytic cascades. These cascades enhance the ability of antibodies and phagocytic cells to clear microbes and damaged cells as well as promote local inflammation.

The complement system links the innate immune system to the adaptive immune system. This is a critical juncture; a delicate balance must be maintained to allow activation when necessary to counteract foreign or modified self/host surfaces, while concurrently protecting healthy self/host tissue [14]. Protection is achieved systemically through the concerted action of activators and inhibitors - about 50 membrane-bound and soluble proteins - that ensure cell and tissue integrity essential for normal health and well-being. When dysregulated, pathological conditions can arise, including neurodegenerative diseases, cancer, age-related macular degeneration (AMD), membranoproliferative glomerulonephritis, systemic lupus erythematosus, transplant rejection, paroxysmal nocturnal haemoglobinuria (PNH), ischemia-related conditions and autoimmune disease, to name a few [14,15].

The three best characterized branches of complement activation are: the classical, lectin, and alternative pathways, as shown in Figure 6.

1. The classical pathway is initiated by the C1 complex binding to multimeric antibody complexes, leading to cleavage of C4 and C2 components and formation of the classical C3 convertase, C4bC2a.

2. The lectin pathway is activated by binding of mannan-binding lectin (MBL), or ficolins (secreted, lectin- type pattern recognition receptors) to carbohydrate or acetylated groups on target surfaces. MBL and ficolins interact with MBL-associated serine proteases (MASP) leading to cleavage of C4 and C2 and formation of the classical C3 convertase, C4bC2a [16]. Noteworthy is that one of the neutrophil granules previously described, is Ficolin-rich; another example of the many network associations between cellular and extracellular events occurring within the innate immune response.

3. Alternative pathway activation involves interaction of C3(H2O) and/or previously generated C3b with factor B, which when cleaved by factor D, generates the alternative C3 convertases C3(H2O)Bb and/or C3bBb. Complement related proteins are always present in the blood and a small percentage spontaneously activate (Table 1). At about 1.5 mg/ml concentration in serum, C3 is by far the most abundant. Notably, low-level hydrolysis of the C3b thioester bond - also known as the C3 ‘tick-over’ notated as C3 (H2O) - keeps the alternative pathway in constant alert to pathogen challenge.

All three pathways converge upon generation of the C3 convertase complexes, facilitating the proteolytic cleavage of C3 to generate split forms opsonin C3b and anaphylatoxin C3a. C3b covalently binds to proteins distributed across the target cell surface. This is followed by an amplification reaction that generates additional C3 convertases and deposits more C3b at the local site. C3b can also bind to C3 convertases switching them to C5 convertases, which then cleaves C5. Thus, by whichever initial means of activation, the complement cascade system leads to one or more important final outcomes:


1. Opsonization of pathogens or damaged-self cells to enhance phagocytosis,

2. Production of anaphylatoxins C3a & C5a involved in the acute inflammatory response,

3. Recruitment of leukocytes to the inflammatory site,

4. B- and T-cell stimulation, and

5. The terminating end of the cascade – assembly of the membrane attack complex (MAC) on the cell surface.

The terminating end of the complement cascade is derived from the C3 Convertase proteolytic product - C5b, which engages the sequential recruitment of C6, C7, C8, and C9, assembling the MAC. Also known as the “terminal complement complex”, it results from the coordination of C5b-7 insertion in the membrane, which then captures C8, inducing polymerization of a C9 ring – to as many as 18, C9’s per pore. Terminal MACs punch a hole (pore) in the membrane of the invading pathogen or target cell, and when a sufficient number of MAC pores form, the cell dies by osmotic lysis.

However, when insufficient quantities of MAC or when sufficient inhibitors of MAC are present, sub-lytic conditions persist that are non-lethal, and unable to kill the cell. Instead, these conditions promote other cellular stress adaptations thereby setting up the duality of outcomes imposed by Complement activation. At sub-lytic doses, the complement MAC has wide ranging effects that differ based

on the cell types, leading to a variety of cellular responses, such as extracellular vesicle secretion, aggregation and chemotaxis. Sub-lytic Complement can also induce increased cell resistance to lytic doses of Complement [17]. These can all conspire to have pathogenic consequences. Complement regulators expressed at high levels on malignant cell membranes form an escape mechanism from MAC, setting up sub-lytic concentrations that can activate intracellular signals leading to malignant cell proliferation [18, 19].

While traditionally described as three activation pathways, an additional, largely under-appreciated pathway is Complement’s evolutionarily conserved link to coagulation to eliminate damaged tissues [20]. C1 Inhibitor (Serpin G1; see next section for further details) serves as one model protein mediator of this linkage, as it acts to inhibit both complement activation and coagulation initiation. As another example, C4b-binding protein is a cofactor for both Factor I (a Complement regulator) and Protein S (a Coagulation regulator). Also, Complement may activate platelets or facilitate biochemical and morphological changes in the vascular endothelium, thus potentiating coagulation and contributing to haemostasis in response to injury [21, 22]. Conversely, Complement can be activated from proteolytic enzymes derived from coagulation and fibrinolysis that can cleave both C3 and C5 [23, 24]. Consequently, the Complement system adapts to, and is influenced by many different proteolytic triggering events.

Such events can also be influenced by competing factors from coagulation and neutrophil recruitment. For example, in mouse models of fatal injury deprived of neutrophils, amplification of complement can occur, which suggests infiltrating inflammatory cells participate in localized Complement activation [25]. Likewise, platelets adhered to injured vessel walls form strong adhesive substrates for leukocytes, a major event in thrombo-inflammation. This series of responses is mediated by Complement and specifically to alternative Complement activator Properdin, derived in part from neutrophil granule cargo [8].

It has also been proposed that the release of Properdin from neutrophils is both a major determinant of local Complement activity and behaves differently from endogenous serum Properdin [26]. In like manner, Properdin released from neutrophils, is structurally related to Thrombospondin-1 (THBS1), a protein released from platelet cargo, both containing conformationally diverse Thrombospondin Type 1 Repeats (TSRs) [27,28]. It is interesting to speculate how TSR binding site competition might influence Complement regulation (one example being THBS1 interaction with Alternative Complement regulator-Factor H [29]). Significantly, several reports suggest Complement-mediated interactions between Neutrophils and Platelets [30, 31]. Regardless of the underlying mechanism, the end result may well be a tug-of-war between platelets and neutrophils for the localized control and regulation of Complement [32] (Figure 7).


These triangulated pathways cooperatively form an intensified cycle resulting in local inflammation, thrombosis, and tissue damage. Chen et al. [33] illustrates how this all may play out in disease. In that study, proteomic analysis classified tumor tissues of over 500 cancers into just 10 subtypes, regardless of the primary tumor of origin. Out of the 10, four subtypes were based solely from the host’s stromal character at the local microenvironment, unrelated to cellular mutations. Of the four stromal subtypes, two reflected immune components: the first by presence of immune T cells, while the second immune subtype, was highlighted by complement activation [32].

Taken together, these studies illustrate how the complement system orchestrates host defense by sensing a danger signal, translating the signal into specific cellular responses, and concurrently, communicating with other biological pathways ranging from adaptive immunity to hemostasis [34]. Such importance notwithstanding, there are limited tests available to assess these conditions in clinical practice. C3 and C4 are most frequently measured; total complement activity (CH50 lytic assay) can be measured if a deficiency is suspected. These tests, however, are non-specific and none can monitor sub-lytic activity, which can often be the most malevolent outcome of complement activation. Clearly, a better characterization of the total picture of Complement activity is needed. Proteomics can serve that need as it can identify and develop biomarkers to capture and report virtually all potentially competing influences, context dependencies and duality of outcomes imposed by Complement. In this regard, we propose here the functional profiling of the protease inhibitor family of Serpins as an important way to address this unmet need.

SERPIN Function and Regulation


As proteolysis is irreversible, there is an essential balance and regulation of proteolytic cascades necessary to keep aberrancies controlled. Central to this maintenance are the Serpins. This unique family of protease inhibitors serves the central control function of innate immunity, in some way regulating all of its proteolytic mechanisms.

Our goal is to show how patterns of Serpins, a superfamily of protease inhibitors, may serve as a surrogate measure of the progressive stages of the innate immune systems’ response to a disease.


Serpins are a superfamily of proteins with similar structures found in all kingdoms of life. They were first identified for their protease inhibition activity (proteolysis regulation). Although some proteins with Serpin sequence annotation are not protease inhibitors, but instead perform diverse functions such as hormone transport, we focus in this section on only serum Serpins with inhibitory activity.

Serpins are an extensively studied family of both intercellular and extracellular proteins that exhibit conformational adaptabilities and a most unique functional mechanism. Often called suicidal inhibitors, inhibitory Serpins are in sharp contrast to the more conventional competitive mechanism for protease inhibitors that bind to and block access to the protease active site in a concentration dependent (Michaelis-Menten type) equilibrium. Such is not the case with Serpins, as the initial interaction starts through a decoy process (an intermediate Michaelis complex). Here, the protease sensing the Serpin as a suitable substrate, initially binds to a peptide region of the Serpin – known as the reactive center loop (RCL) -that transiently protrudes from the core of the Serpin body. From this intermediate complex, one of two possible final outcomes are produced, called, respectively, the Substrate and Inhibitor Pathways, as depicted in Figure 8, and summarized as: follows:

In the inhibitor pathway, the protease selectively cleaves a peptide bond in the reactive center loop (RCL) of the serpin. The resulting acyl-enzyme undergoes an extensive and rapid conformational change, with a 180 degree translocation of the attached protease. During this process the active site is deformed, and hydrolysis cannot be completed. This process results in an irreversible covalent complex. Trapped in this suicidal covalent embrace, both the protease and the Serpin are irreversibly modified and cannot be regenerated back to their active forms.

In the Substrate Pathway however, the protease releases from the complex and remains active (the ‘On’ sub-form), but not so for the inhibitor as the RCL region is cleaved and the inhibitor becomes permanently inactive (the ‘Off’ sub-form) [35, 36].

Nine inhibitory Serpins account for ≥ 5% of the protein mass contained in serum (Table 4, see also top fraction in Figure 1). With such a large regulating influence in blood, Serpins are themselves subject to many co-factors (e.g., Heparin) that act upon their inhibition efficiency. Any aberrations in this finely tuned mechanism can lead to progressive loss of functionally active forms or the accumulation of inactive forms, Figures 8 & 9. Insufficient Serpin control of irreversible and inflammatory proteolytic activity can lead to systemic dysregulation of innate immunity and progression of disease.

Further confounding the significance of this bifurcated inhibition mechanism is that measurements of Serpins have conventionally relied on immunological (ELISA)-type assays that count all sub-forms in aggregate and thereby assume homogeneous populations. This can lead to erroneous conclusions about their functional role in disease. Fortuitously, the different active vs. inactive Serpin sub-forms are reportable from biofluids using LC-MS/MS analysis [37]. In our own analysis for cancer, we have identified two critical nodes in this network relating to the progressive loss of functionally-active Serpins: (A1) Alpha-1-Antitrypsin and (D1) Heparin Cofactor II [38]. These proteins are included as part of Biotech Support Group’s Stroma Liquid Biopsy™ [39] panel of cancer biomarkers.

Other reports corroborate these results that tumorigenesis can systemically be characterized by chronic exhaustion of inhibitory active Serpins and resulting increased protease activity (Figure 10).

Context Dependent Proteomic Categorization of Disease

In the course of this review, we have provided a brief description of the three key innate immunity pathways, how they interact with each other, and how they are all regulated through protease activation balanced by protease inhibition, most notably through the Serpin family. As noted in our review, these immune responses are extremely context-dependent, e.g., the vasculature at inflammatory sites differs significantly from the surrounding tissue. Many factors contribute to create the context in such environments: platelets attached to vessel walls, vasodilation, shear sensing receptors and the relative amounts of diffusive to axial transport of solutes. Thus, the activation of cells and the release of their cargo proteins at the local site offers the means for a categorical deconstruction of the inflammatory elements of disease. Potential markers may now be reported from blood through the protein cargos released from neutrophils and platelets; these cargo proteins are readily observable through quantitative LC-MS/MS analysis. We highlight these proteins in the BSG knowledgebase in Table 2.

Finally, this context-specific, released cargo enters the general circulation and simultaneously influences another tier of response, namely, the highly observable and measurable Complement cascade and Serpin regulation (Tables 3 and 4). All these various, systemic responses can be monitored and categorized by quantitative proteomic analysis: Platelet-released cargo, Neutrophil-released cargo, complement components and Functional ‘On’ & ‘Off’ sub-forms of Serpins (Figure 11).

Through this new strategy, we posit that biomarker panels can be derived from these categorical proteins which increase or decrease in characteristic patterns from pathological conditions. In turn, these panels can then be used to assess patients for actionable decisions.

This ground truth protein data creates a survey of the function and communication between plasma and cells in blood. With advancements in proteomics and bioinformatics for chronic diseases, we can aspire to bring blood-based protein biomarkers to the clinic. Unlike single markers such as HbA1c for diabetes management, future advances in protein biomarkers will not come from one protein assay or even a small set of protein assays, but from patterns of protein changes. The good news is that these potential protein patterns are highly observable using LC-MS/MS and this capability has become even more precise and comprehensive with improvements in instrument speed and resolution. Advancements in the quantification of multiple proteins at once, in both targeted label and label-free analysis; coincide with the use of internal standards and simple efficient sample prep workflows. This convergence of technologies has made the task immediately available to those who, like us, seek to develop the next generation of molecular tests for more precise and personalized treatment of patients. 


1.       M Stastna, Eyk JEV (2012) Secreted proteins as a fundamental source for biomarker discovery. Proteomics 12: 722-735.


2.       Zheng, H (2015) AlbuVoid™ coupled to on-bead digestion-tackling the challenges of serum proteomics. J Proteom Bioinformatics 8: 225.


3.       Biotech Support Group Application Report (2019) AlbuVoid™ PLUS & AlbuSorb™ PLUS - Evaluating Different Windows of Observation Solves The Many Challenges of Serum Proteomics. Available online at:


4.       Klatt S, Roberts A, Lothian A (2020) Optimizing red blood cell protein extraction for biomarker quantitation with mass spectrometry. Anal Bioanal Chem. Available online at:


5.       Vialaret, Jerome & Kadi, Sarah & Tiers, Laurent & O Flynn, Robin & Lehmann, et al. (2018) Albumin depletion of human serum to improve quantitative clinical proteomics. Curr Top Pept Protein Res 19: 53-62.


6.       Lange, Philipp F (2014) Annotating N termini for the human proteome project: N termini and Nα-acetylation status differentiate stable cleaved protein species from degradation remnants in the human erythrocyte proteome. J Proteome Res 13: 2028-2044.


7.       Esmon CT (2004) Interactions between the innate immune and blood coagulation systems. Trends Immunol 25: 536-542.


8.       Swystun, Laura L, Liaw PC (2016) The role of leukocytes in thrombosis. Am Soc Hematol 128: 753-762.


9. staff (2014) Medical gallery of Blausen Medical 2014. WikiJournal of Medicine 1.


10.    Feng, Zhao S (2019) Elevated plasma fibrinogen and the neutrophil-to-lymphocyte ratio as predictive risk factors for prostate cancer. Int J Clin Exp Med 12: 13117-13126.

11.    Kolaczkowska E, Kubes P (2013) Neutrophil recruitment and function in health and inflammation. Nat Rev Immunol 13: 159-175.


12.    El Rayes, Tina (2015) Lung inflammation promotes metastasis through neutrophil protease-mediated degradation of Tsp-1. Proc Natl Acad Sci 112: 16000-16005.


13.    Reactome pathway database (2019) Available online at:,R-HSA-76002&FLG=P02776


14.    Zipfel, Peter F, Skerka C (2009) Complement regulators and inhibitory proteins. Nat Rev Immunol 9: 729.


15.    Varela, Carlos J, Tomlinson S (2015) Complement: An overview for the clinician. Hematology/Oncology Clinics 29: 409-427.


16.    Ricklin, Daniel (2010) Complement: A key system for immune surveillance and homeostasis. Nat Immunol 11: 785.


17.    Bohana-Kashtan, Osnat (2004) Cell signals transduced by complement. Mol Immunol 41: 583-597.


18.    Roumenina, Lubka T (2019) Context-dependent roles of complement in cancer. Nat Rev Cancer 19: 1-18.


19.    Afshar-Kharghan, Vahid (2017) The role of the complement system in cancer. J Clin 127: 780-789.


20.    Dzik, Jolanta M (2010) The ancestry and cumulative evolution of immune reactions. Acta Biochimica Polonica 57: 443-466.


21.    Oikonomopoulou, Katerina, et al. (2012) Interactions between coagulation and complement-their role in inflammation. Springer-Verlag, 2012.


22.    Markiewski MM, B Nilsson, KN Ekdahl, TE Mollnes, JD Lambris (2007) Complement and coagulation: Strangers or partners in crime? Trends Immunol 28: 184-192.

23.    Amara, Umme (2010) Molecular intercommunication between the complement and coagulation systems. J Immunol 185: 0903678.


24.    Krisinger MJ, Goebeler V, Lu Z, Meixner SC, Myles T, et al. (2012) Thrombin generates previously unidentified C5 products that support the terminal complement activation pathway. Blood 120: 1717-1725.


25.    Girardi, Guillermina (2003) Complement C5a receptors and neutrophils mediate fatal injury in the antiphospholipid syndrome. J Clin Invest 112: 1644-1654.


26.    Kemper, Claudia, Hourcade DE (2008) Properdin: New roles in pattern recognition and target clearance. Mol Immunol 45: 4048-4056.


27.    Cortes, Claudio (2013) Local release of properdin in the cellular microenvironment: Role in pattern recognition and amplification of the alternative pathway of complement. Front Immunol 3: 412.


28.    Crombie, René (2000) Mechanism of thrombospondin-1 anti-HIV-1 activity. AIDS Patient Care STDs 14: 211-214.


29.    Resovi, Andrea (2014) Current understanding of the thrombospondin-1 interactome. Matrix Biology 37: 83-91.


30.    Blatt, Adam Z, Pathan S, Ferreira VP (2016) Properdin: A tightly regulated critical inflammatory modulator. Immunol Rev 274: 172-190.


31.    Saggu, Gurpanna (2013) Identification of a novel mode of complement activation on stimulated platelets mediated by properdin and C3 (H2O). J Immunol 190: 6457-6467.


32.    Chen, Fengju (2019) Pan-cancer molecular subtypes revealed by mass-spectrometry-based proteomic characterization of more than 500 human cancers. Nat Commun 10: 1-15.


33.    Merle, Nicolas S (2015) Complement system part I-molecular mechanisms of activation and regulation. Front Immunol 6: 262.


34.    Nording, Henry, Langer HF(2018) Complement links platelets to innate immunity. Semin Immunol 37.


35.    Law, Ruby HP (2006) An overview of the serpin superfamily. Genome Biology 7: 216.


36.    Khan, Sazzad M (2011) Serpin inhibition mechanism: A delicate balance between native metastable state and polymerization. J Amino Acids 2011.


37.    Roy, Swapan, Kuruc M (2019) Methods to Monitor the Functional Subproteomes of SERPIN Protease Inhibitors. Functional Proteomics. Humana Press, New York, NY, pp: 41-54.


38.    Verhamme, Ingrid M (2019) Loss of Functional Alpha-1-Antitrypsin and Heparin Cofactor II in Inflammation and Cancer. The Serpins 2019 Conference, September 19-22, 2019 in Sevilla, Spain.


39.    Stroma Liquid Biopsy™ (2019) Blood-based biomarkers to monitor stromal conditioning in cancer. Whitepaper


40.    Sun, Zhifu, Yang P (2004) Role of imbalance between neutrophil elastase and alpha 1-antitrypsin in cancer development and progression. The Lancet Oncology 5: 182-190.


41.    Janciauskiene, Sabina (2001) Conformational properties of serine proteinase inhibitors (serpins) confer multiple pathophysiological roles. Biochim Biophys Acta 1535: 221-235.


42.   Manco-Johnson MJ (1994) Antithrombin III. Anticoagulant: Physiologic, pathologic, and pharmacologic. CRC Press, Boca Raton, Florida, USA Chapter 3: 27-40.


43.   Hatto, MW, Hoogendoorn H, Southward SM, Ross B, Blajchman MA (1997) Comparative metabolism and distribution of rabbit heparin cofactor II and rabbit antithrombin in rabbits. Am J Physiol 272: E824-E831.