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Background

To meet the demand for kidney transplants (KTx), organs are frequently retrieved not only from standard criteria donors (SCD; a donor who is aged <50 years and suffered brain death from any number of causes, such as traumatic injuries or a stroke) but also from expanded criteria donors [ECDs; any donor aged >60 years or a donors aged ≥50 years with two of the following: a history of high blood pressure, a creatinine serum level ≥1.5 mg/dl or death resulting from a stroke]. This comes at the cost of a higher risk of primary non-function (PNF; the permanent hyperkalemia, hyperuremia and fluid overload that result in the need for continuous dialysis after KTx), delayed graft function (DGF; the need for dialysis session at least once during the first week after KTx), earlier graft loss and urinary complications (vesico-ureteral reflux, obstruction of the vesico-ureteral anastomosis, urine leakage) (1-3). An increased risk of graft failure and graftectomy can result in recipient immunization, leading to increasingly difficult donor selection and higher risk of consecutive graft failure (4,5). However, there is also evidence that graft survival is unaffected by the procurement of kidneys from ECDs compared to kidneys retrieved from SCDs (6,7).

Currently, there is no commercially available diagnostic tool for the quality assessment of the kidney before KTx (8). To this end, the majority of medical centers will typically perform a 0-h biopsy (9,10), but the results only become available days after surgery and assessment is limited to a limited part of the kidney. A 0-h biopsy does not provide an insight into the condition of the entire organ and cannot be used to predict its function after KTx. The period of kidney storage should be as short as possible and the decision on KTx should be made during this period. However, predictive models based on clinical data, such as the Kidney Donor Profile Index (KDPI) (11,12), the continuous kidney donor risk index (13) and deceased donor score (14), are insufficient for assessing the condition of potentially transplanted kidneys. A number of preservation and perfusion solutions have been assessed as possible novel biomarkers of kidney quality and predictors of short- and long-term outcomes. These include metabolites, enzymes, complement-related molecules, antibodies, histones and cytoskeletal elements released by tubular, interstitial, immunological and epithelial cells (15-17). However, none of these previous studies have contributed to the identification of biomarkers that are beneficial for assessing the value of the kidney. This is due to the lack of randomized controlled trials in this area to confirm the utility of potential biomarkers. Some of the markers, such as lactate dehydrogenase (LDH) or neutrophil gelatinase-associated lipocalin (NGAL), are not tissue specific (18,19). In addition, the methods used to detect the majority of the candidates are time-consuming, requiring qualified personnel, expensive equipments and reagents. Therefore, there remain to be a demand for a rapid, non-invasive diagnostic tool and reliable predictive model for assessing the post-transplant function of a sub-optimal donor kidney.

Studies on single protein biomarkers

The analysis of biological samples inevitably involves the detection of a wide range of proteins. In such scenarios, two primary pathways for analysis emerge, namely targeted and untargeted. The former involves targeting specific groups of proteins, such as immunoglobulins or individual proteins based on existing knowledge, assessing their relevance to the phenomena in question. To detect these known individual particles, targeted analytical methods were used in previous studies. These included ELISA, western blotting and enzymatic/cytotoxic assays.

Proteins released after cell disruption

LDH

LDH was one of the first proteins to be studied in the renal perfusate. This cytosolic enzyme is responsible for the conversion of pyruvate to lactate by NADH under normoxic and hypoxic conditions (20). In total, five tetrameric isoenzymes consisting of LDHA and LDHB subunits have been previously described (18,21,22). They differ in their degree of substrate affinity, electrophoretic mobility, inhibition constants and tissue distribution (18). In an experimental rat model, LDHA was previously found to be mainly present in the proximal renal tubules, whilst LDHB was found to be mainly expressed in the distal part of the nephron (23).

In relation to KTx, LDH has been documented to serve as a non-specific marker of cell injury (18). Perfusate LDH activity is not applicable in the assessment of renal function prior to KTx. Despite the studies showing a positive association between LDH concentration and DGF (15,24-26), there are no randomized controlled trials that have confirmed the viability of LDH measurements for the assessment of kidney quality. Furthermore, LDH is not a kidney-specific biomarker (18,27,28). Guzzi et al (15) previously found that besides glutathione S-transferase (GST), LDH levels were the most commonly reported parameter in the renal perfusate. Elevated LDH levels have been reported to associate positively with DGF in cases of donation after cardiac death (DCDs) (24-26), but not in all cases of donations after brain death (DBDs) (29,30). According to previous studies, (15,24-26,31,32) where LDH levels were measured only in perfusate from DCDs, LDH levels were found to be positively associated with DGF in all cases. By contrast, in studies describing the measurement of LDH levels in the perfusate of kidneys from DBDs, a positive association between DGF and LDH levels was only found in two (29,30) of the four selected studies found (15). In addition, this meta-analysis (15) also showed that LDH activity should not be considered as a marker of PNF in patients with DCDs grafts. Further analysis of cases of DBDs and DCDs demonstrated that although the LDH levels were associated positively with DGF in the majority of the included studies, following multivariable analysis only one study showed a weak association (32). In another meta-analysis previously conducted by Bhangoo et al (16), perfusate LDH activity was found to be a predictor of DGF, PNF and graft failure (GF). However, this previous analysis lacked a donor-type subgroup assessment (16). A number of the included studies revealed a significant association between LDH activity and DGF, PNF (31,33). Among the different types of donors, LDH activity was the highest in kidneys from DCD cases, which reflected the greatest extent of damage prior to KTx among the studied organs (34). Perfusate assessment has been used to estimate renal cell injury after ischemia in a previous study (29), where LDH levels were previously found to be increased during the ischemic period (29). This phenomenon also associated positively with damage to renal tubular cells detected by electron microscopy. The lesions found include mitochondrial swelling and loss of detail in the inner cristae, swelling and detachment of the basolateral tubular membrane connective tissue (29).

GSTs

GSTs form one of the most frequently studied groups of biomarkers obtained from the renal hypothermic machine perfusate (15,16). In humans, the GST family consists of three subpopulations according to their localization: Cytosolic, mitochondrial and microsomal (35). GSTs can be divided into subclasses, designated by Greek letters that differ in their levels of expression in humans. α-GST is abundantly expressed in liver and renal proximal tubular cells, whereas distal tubular cells mainly express the p-GST isoform (36,37). Although GSTs mainly function as catabolic agents to catalyze the detoxification of xenobiotics within glutathione, they have also been reported to mediate cell signaling. p-GST isoform can inhibit the function of kinases involved in the MAPK pathway, which regulates cell proliferation and cell death (38).

GSTs are considered one of the most valuable and reliable non-invasive markers for pre-transplant DGF prediction, but their utility in forecasting long-term outcomes, PNF and discarding kidneys from transplantation remains controversial (15,16). Significant differences were observed in the accuracy of the predictive values of different isoforms for DGF. Hall et al (39) previously found that p-GST measured at baseline and at the end of hypothermic machine perfused (HMP) kidneys from deceased donors was associated positively with DGF. The relative risk ratio of DGF for each log-unit increase at baseline and post-perfusion p-GST concentration after adjustment (for black ethnicity, male sex, history of previous kidney transplant, diabetes as the cause of end-stage renal disease, need for blood transfusion before KTx, number of human leukocyte antigen mismatches, body mass index in kg/m2 and duration of dialysis before transplant) was found to be 1.14 (95% CI, 1.00-1.28) and 1.33 (95% CI, 1.02-1.72), respectively. α-GST did not associate with DGF. In addition, the concentrations of both iso-enzymes did not differ between the transplanted and discarded organs at start and just before end of perfusion, showing that GSTs levels could not be used as a tool for discarding kidneys from KTx.

Perfusate GST levels have been previously compared with HMP parameters to improve the predictive value of GST. However, the value of this prospect remains controversial, where no clear association has yet been established. In a previous study by Moers et al (33), a correlation between the studied biomarkers [such as LDH, aspartate aminotransferase, N-Acetyl-/β-glucosaminidase, GSTs, alanine aminopeptidase (Ala-AP) and heart fatty acid binding proteins (H-FABP)] and pump parameters (such as cold ischemia time and renal vascular resistance) was not confirmed. Hall et al (39) also previously found no correlation between pump parameters (such as renal resistance at 4 h of perfusion and perfusate flow at 4 h) and concentrations of GST isoforms. By contrast, Qiao et al (40) found that the model combining end-of-perfusion vascular resistance and GST [area under the curve (AUC)=0.888; 95% CI, 0.842-0.933] significantly improved DGF predictability compared to using terminal resistance (AUC=0.756; 95% CI, 0.693-0.818) or GST alone (AUC= 0.729, 95% CI, 0.591-0.806).

Perfusate GST activity has also been investigated using other potential biomarkers of DGF. Gok et al (41) reported that GST with Ala-AP activity or GST activity with FABP concentration corresponded positively to renal injury during ischemia. However, its role in predicting the occurrence of PNF and in kidney discards for transplantation remains unclear (33).

Extracellular histones

Ischemic injury during HMP leads to the release of histones from disrupted cells (42), including extracellular histones H2A, H2B, H3 and H4. Each nucleated cell contains nucleosomes built from these four elements in an equimolar manner (43). Following the induction of pathological conditions, such as ischemia, histones are released from dying cells into the extracellular space (44,45). Using an experimental porcine model of warm ischemia and machine perfusion of retrieved kidneys, extracellular histones were reported to be cytotoxic to endothelial and renal epithelial cells in a temperature-dependent manner (46). Furthermore, histone release is higher during sub normothermic machine perfusion (SNMP) at 28°C compared with hypothermic machine perfusion (HMP) at 4°C (46). Under normal conditions, histones are responsible for nucleosome assembly (47), chromatin stability (47) and epigenetic modifications in transcription, replication and DNA repair (48). However, in the extracellular space, they function as damage-associated molecular pattern proteins (DAMPs) (49).

A previous retrospective study of 309 kidneys from DCDs was conducted on extracellular histones in the renal perfusate. van Smaalen et al (42) measured histone H3 levels at 1, 2 and 4 h of HMP. In uncontrolled DCD kidneys (Maastricht categories 1 and 2), no difference in H3 levels could be found compared with the PNF, DGF and IF (immediate function) groups. In the control cohort (Maastricht categories 3 and 4), a higher H3 concentration in perfusate was associated with DGF [univariable odds ratio (OR)=3.071; 95% CI, 1.588-5.941; multivariable OR=2.433; 95% CI, 1.253-4.723]. When comparing two groups of patients with histone H3 concentrations above and below the median, Kaplan-Meier analysis revealed a significant difference in graft survival in favor of lower concentrations. In particular, the 1- and 5-year survival rates were significantly superior in the lower H3 group (at 1 year, 84 vs. 72%; at 5 years, 79 vs. 66%) (50).

FABPs

Ischemia leads to the overloading of proximal tubular cells with free fatty acids (FFAs) and tubulo-interstitial damage (51,52). During oxidative stress, FFAs bind to fatty acid binding proteins (FABPs), thereby preventing their intracellular accumulation and further oxidation (53). In addition, they can regulate the expression of genes involved in FFA metabolism and promote their β-oxidation in peroxisomes (53). To date, two isoforms have been described in human proximal tubular cells, namely liver (L)-FABPs and heart (H)-FABPs, which are also present in distal tubular cells (54). Under normal conditions, FABPs are involved in the cellular uptake and utilization of FFAs from the plasma by rapid incorporation into triacylglycerols and phospholipids, promotion of FFA metabolism in mitochondria or peroxisomes, regulation of intracellular cholesterol metabolism, regulation of gene expression involved in lipid metabolism and modulation of cell proliferation (54,55).

Perfusate FABPs have been reported to associate with DGF. Moers et al (33) found that H-FABP was an independent predictor of DGF but only had a moderate prognostic value. In another previous study, L-FABP levels were reported to be associated with estimated glomerular filtration rate (eGFR) 6 months after KTx (56). To the best of our knowledge, the association between FABP levels in the renal perfusate and PNF has not been studied. Sun et al (57) could not confirm the predictive value of FABPs for DGF and 3-year post-transplant function (expressed by eGFR value) in a retrospective study of cases of DCDs. Perfusate FABPs levels have been shown to associate with high vascular resistance and early graft dysfunction (33). Fig. 1 presents a list of molecules that can be released after renal tubular cells disruption upon necrosis and apoptosis resulting from ischemia.

Figure 1 Proteins released after cell disruption. Metabolism switches from aerobic to anaerobic during ischemia, resulting in lactate production and intracellular acidosis. These conditions cause the inhibition of Na+/K+-dependent ATPase activity, leading to the accumulation of sodium ions and cellular edema. Other consequences of ischemia include leakage of lysosomal enzymes, cytoskeletal breakdown and decreased calcium excretion. Excess calcium leads to the generation of ROS. Ischemia also triggers the expression and redistribution of microtubule cytoskeletal elements. Cell-cell integrity is altered, leading to loss of cell polarity and redistribution of the basolateral membrane. All of the aforementioned conditions can lead to cell death. The figure shows preformed proteins that are released extracellularly after cell death. The figure was created with BioRender® Science Suite, Inc. ROS, reactive oxygen species; NAG, N-Acetyl-/β-glucosaminidase; FABP, fatty acid binding protein; LDH, lactate dehydrogenase; AST, aspartate aminotransferase; GST, glutathione S-transferases.

Proteins secreted during ischemia in HMP

NGAL

NGAL is a protein that is originally synthesized in the bone marrow and is stored in neutrophil granules (58). NGAL has been previously detected in the lung, colon, trachea and renal epithelium (19). NGAL is capable of binding siderophores. Therefore, it has been postulated that NGAL can serve as a bacteriostatic agent by sequestering iron (59) and as a regulator of extracellular iron-induced injury (60). Production in non-hematopoietic locations has been associated with systemic inflammation, where one such stimuli is IL-1β (61). NGAL is typically released in response to ischemia (62) and nephrotoxic agent (such as cisplatin) contact (63). In addition, ATP depletion induces NGAL mRNA expression, leading to the production of NGAL (62). In this context, necrosis and cell apoptosis is a factor that can trigger NGAL mRNA expression in renal tubular cells (63).

In a previous systematic review, Guzzi et al (15) found three studies on NGAL (29,32,56), but only one (56) showing a positive association between NGAL concentration in the HMP kidney perfusate and DGF occurrence. The study by Moser et al (29) found that NGAL levels are not significantly different between the DGF and non-DGF groups. In another study by Hoogland et al (32), NGAL concentrations measured 4 h after initiation of perfusion were not reported to be significantly associated with the risk of DGF or PNF. Furthermore, the post-HMP NGAL concentration was found to be associated with 6-month eGFR but not with PNF (56). In another study on discarded human kidneys, NGAL levels were found to be markedly higher after 6 h of normothermic machine perfusion (NMP) administration in organs from donors with higher serum creatinine levels (sCr) at the time of retrieval (64).

However, care must be taken when examining the perfusate for the presence of NGAL and interpreting the available data. NGAL is secreted in different forms, including monomeric, dimeric and conjugated with MMP-9 (65). Available assays utilizing antibodies have not been suitably adapted to measure the monomeric and heterodimeric forms released by injured or stressed tubular cells (19). Another important issue is the timing of sample collection from the perfusion machine. NGAL synthesis and release are considered to be altered by hypothermia (15). To determine the most appropriate time interval, measuring NGAL in the renal perfusate not only after 4 h, but also after 14-16 h of HMP, are of importance to confirm the effect of hypothermia and time of perfusion on its concentrations.

MMPs

MMPs have been recognized for their roles in ischemia and reperfusion processes. They have been studied in the context of ischemia-reperfusion injury in the central nervous system (66), lungs (67), liver (68), heart, (69,70), skeletal muscle (71), retina (72) and kidney (73-77). MMPs, also known as matrixins, are zinc-dependent enzymes that are located mainly in the extracellular space (78). However, MMP-1, MMP-2 and MMP-11 have been found to function intracellularly. To date, 23 MMPs have been identified in humans (79). They are first synthetized as pre-proenzymes and the majority are secreted into the extracellular space. MMPs are typically produced after stimuli, such as by inflammatory cytokines (TNF-α and IL-1), free radicals, reactive oxygen species (ROS), oncogenic cellular transformation, physical stress and chemical agents (78). In addition, a number of soluble factors can induce the expression of MMPs and molecules on the cell surface, including leukocyte function-associated antigen-1, intercellular adhesion molecule-1-mediated cell adhesion very late antigen 4 and vascular cell adhesion molecule (VCAM)-1 (80). The interaction between gp39-CD40 in monocytes and α5β1 integrin-fibronectin can also lead to MMP expression (80). Secreted pre-proenzymes are activated in the extracellular space by tissue, plasma or opportunistic bacterial proteinases. In particular, the urokinase-type plasminogen activator/plasmin system has been reported to serve a role in MMP activation (81). Pro-MMP-2 has been reported to be activated on the cell surface (82). Pro-MMP-2 is localized in podosomes or the invadopodia (83,84). This activation process requires the activation of the first membrane-type MMP (MT1-MMP), and the tissue inhibitor of MMP-2 (TIMP-2)-bound MT1-MMP (78). The TIMP-2 in the latter complex binds through its C-terminal domain to the hemopexin domain of pro-MMP-2, which is assumed to localize the zymogen close to the active MT1-MMP (78). It is also activated by plasmin produced by urokinase-type plasmin activator (from an inactive form), which is attached to a high-affinity cell membrane binding site by a specific N-terminal sequence of its non-catalytic chain (82).

MMP-2 and MMP-9, also known as gelatinases, are the most frequently investigated MMPs in KTx and organ preservation. MMP-2 activity contributes to the proteolysis of collagen types I, IV, V, VII, X, XI and XIV, gelatin, elastin, fibronectin, laminin and aggrecan (69,85). By contrast, MMP-9 targets include collagen types IV, V, VII, X and XIV, gelatin, aggrecan, elastin, entactin and fibronectin (86). Data on the presence of MMPs in the renal perfusate and their predictive value remain scarce. Moser et al (29) previously investigated the activity of NGAL, LDH and MMPs in renal perfusates from DBDs and donors after controlled cardiac death (cDCDs). MMPs could be detected in all samples and a significant positive association between perfusate MMP levels and the occurrence of DGF was reported. However, this association was not observed for NGAL and LDH levels. Additionally, higher concentrations of MMP-2 and MMP-9 were observed in the cDCDs group compared with those in the DBDs group. In another previous proteomic analysis on three types of donors, namely living kidney donors (LKDs), DBDs and cDCDs, the levels of MMPs were found to be ranked in the following manner: LKDs < DBDs < cDCDs (34).

Previous studies using animal models have shown that different storage methods may influence MMP secretion. In one such study, it was observed that HMP reduced MMP-9/NF-κB-dependent expression compared with static cold storage (SCS) in a rabbit model (87). Notably, HMP did not affect MMP-2 expression. In another study performed by Sulikowski et al (88) on a rat model, the authors investigated the impact of University of Wisconsin solution (UW) and EuroCollins solution (EC) on the gene expression of MMP-2 and tissue inhibitor of MMP-2 (TIMP-2). After 24 h of cold ischemia time (CIT), the gene expression levels of MMP-2 and TIMP-2 were found to be decreased in kidneys perfused with UW, whereas they were increased in kidneys perfused with EC. After warm ischemia, the levels of MMP-2 and TIMP-2 gene expression were increased in kidneys perfused with UW, whereas they were significantly lower in kidneys perfused with EC.

Kidney injury molecule-1 (KIM-1)

KIM-1, also known as hepatitis A virus cellular receptor 1 and T cell immunoglobulin- and mucin-domain-containing molecule, is considered to be a biomarker of ischemia-mediated renal injury during preservation (56). Its attractiveness stems from its specific expression pattern and function in renal proximal tubular cells. KIM-1 is a cell membrane glycoprotein (89), which is comprised of an extracellular portion, a six-cysteine immunoglobulin-like domain, two N-glycosylation sites and a thrombospondin-rich domain, which is characteristic of mucin-like O-glycosylated proteins (90). KIM-1 is predominantly localized on the apical surface of renal proximal tubular epithelial cells (91). It exhibits homology to a hepatitis A virus receptor (89). KIM-1 expression is typically absent under healthy conditions, but is activated under various conditions and diseases, such as cell dedifferentiation, ischemic injury (89), toxic injury (92), autosomal dominant polycystic kidney disease (93) and renal cell carcinoma (94). In the renal proximal epithelium, KIM-1 serves as a phosphatidylserine receptor that can recognize apoptotic cells and direct them into lysosomes (95). It can also bind to oxidized lipoproteins in injured cells. In addition, KIM-1 has been observed to mediate the transformation of epithelial cells into phagocytic cells (96).

A previous study on 671 kidneys retrieved from standard criteria donors (SCDs) and ECDs failed to demonstrate the utility of KIM-1 as a biomarker, predictor of DGF or long-term outcomes (56). KIM-1 concentrations were measured at the beginning and end of the perfusion. The mean difference between the KIM-1 concentrations at these points was not found to be associated with DGF. In an experimental model of NMP of discarded human kidneys, KIM-1 was found to be released at lower levels in kidneys with a higher urine output (64). In a previous study, in the DCDs kidney group, perfusate KIM-1 was proposed as an independent marker of DGF and was correlated with 3-month eGFR (57).

IL-18

IL-18 is a cytokine that belongs to the IL-1 family and has been detected during hypothermic machine perfusion (25,56). IL-18 precursors are present in monocytes, macrophages, dendritic cells, intestinal cells, keratocytes, epithelial cells and renal tubular cells (97), in addition to being readily released by dying cells (97). Transcription of the IL-18 precursor is stimulated by the binding of Toll-like receptors to PAMPs, which then signals through the NF-κB pathway (97). Activation of the IL-18 precursor leads to its intracellular conversion into its mature form by caspase-1 (98). Extracellular activation mechanisms involve various proteases, such as neutrophil proteinase 3, granzyme B and chymase (99,100). In renal epithelial cells, the IL-18 precursor can be activated and converted into its mature form by the MMP meprin B (101).

IL-18 was originally identified to be an IFN-γ-inducing factor. It serves an important role in both naive and adaptive immunity (102). Among IL-12 and IL-15, which can upregulate IL-18 receptor expression, IL-18 induces IFN-γ production in CD4, CD8 T cells and natural killer (NK) cells (103). In addition, IL-18 can directly upregulate perforin- and FasL-dependent cytotoxicity in NK and CD8 T cells (103). IL-1β/IL-18 signaling initiates the transcription of several inflammatory factors, including GM-CSF, IL-4, histamine and TNFα, which facilitate leukocyte infiltration (104). IL-18, in the absence of IL-12 and IL-15, is responsible for the differentiation of naive T cells into T helper 2 cells, which produce IL-4 and IL-13, (105,106). Upon IL-18 stimulation, mast cells and basophils can produce IL-4 and IL-13 (107), whilst γδ T-cells produce IL-17 (97).

Previous studies on kidneys during storage using perfusate IL-18 could not confirm its predictive value for DGF (25,56). Its concentration was higher in samples from kidneys developing DGF, but no statistical significance could be found. In addition, although IL-18 associated with PNF in kidneys from DCDs, the diagnostic accuracy of IL-18 alone was poor (56). Similarly, in kidneys with a KDPI >80, IL-18 provided no predictive value for PNF, DGF or 1-year post-transplant outcomes according to another previous study (108). Table I shows a list of protein biomarkers detected using untargeted analysis methods. Fig. 2 shows molecules secreted during ischemia in HMP.

Figure 2 Proteins secreted during ischemia in HMP. The figure represents molecules that are expressed upon ischemia as a trigger factor, some of which are linked to the cellular membrane, including kidney injury molecule-1, alanyl-aminopeptidase and part of pre-pro MMP-2. MMPs are mostly secreted as pro-enzymes and are activated extracellularly. IL-18, produced as a pre-protein, is activated intracellularly and then secreted from the cell. Neutrophil gelatinase-associated lipocalin is present in three different forms: Monomeric, dimeric and heterodimeric with MMP-2. The figure was created with BioRender® Science Suite Inc. KIM-1, kidney injury molecule-1; NGAL, Neutrophil gelatinase-associated lipocalin.

Table I Protein biomarkers of kidney quality detected in human perfusate.

Table I

Protein biomarkers of kidney quality detected in human perfusate.

Protein class	Name	Type of donor	(Refs.)
Cytoplasmic enzymes	Lactate dehydrogenase	DBDs, DCDs and LKDs	(15,16,26,29,34)
	Glutathione-S-transferases and its isoforms	DBDs and DCDs	(15,16)
	Glutathione peroxidase	DBDs	(145)
	Peroxidoxin-2	DBDs, DCDs and LKDs	(34)
	Alanine aminopeptidase (cytosolic form)	DCDs	(41)
	Protein deglycase DJ-1	DCDs, DBDs and LKDs	(34)
	Alcohol dehydrogenase, subunit β	DBDs and DCDs	(17)
	Aldose reductase	DBDs and DCDs	(17)
	α-enolase	DBDs and DCDs	(17)
	Aminoacylase	DBDs and DCDs	(17)
	Superoxide dismutase	DBDs	(144)
Mitochondrial enzymes	Aspartate aminotransferase	DBDs and DCDs	(33)
	GAPDH	DBDs and DCDs	(17)
	Superoxide dismutase	DBDs	(144)
Lyzosomal enzymes	N-Acetyl-/β-glucosaminidase	DBDs and DCDs	(33)
Proteins secreted extracellularly	MMP-2	DCDs, DBDs and LKDs	(34)
	Neutrophil gelatinase-associated lipocalin	DBDs, DCDs and LKDs	(34)
	α1-antitrypsin	DBDs, DCDs and LKDs	(34)
	Superoxide dismutase	DBDs	(144)
Proteins attached to cellular membrane	Kidney injury molecule 1	DBDs and DCDs	(56)
	Alanine aminopeptidase (membrane form)	DCDs	(41)
	MMP-2 (membrane attached form)	DBDs, DCDs and LKDs	(29,34)
Nucleus components	Histones H2A, H2B, H3 and H4	DCDs	(42)
Complement elements	C3a, c3d, and soluble c5b-9	DCDs	(128)
	C1q subcomponent subunit B, C1s subcomponent, C1r subcomponent and C4b-binding protein α chain	DBDs	(116)
Cytoskeletal elements	Actinin-1	DBDs	(116)
	Talin-1	DBDs	(116)
	Desmoplakin	DBDs	(116)
	Collagen α-1(I) chain	DCDs, DBDs and LKDs	(34)
Proteasome elements	Liver-FABP	DCDs, DBDs and LKDs	(34)
	Heart-FABP	DBDs and DCDs	(56)
	Leucyl aminopeptidase	DCDs	(143)
	Pyroglutamyl aminopeptidase	DCDs	(143)
	Arginyl aminopeptidase	DCDs	(143)
	Dipeptidyl IV-aminopeptidase	DCDs	(143)
Peroxisomal elements	Catalase	DBDs	(144)
Immunological components	Immunoglobulin heavy variable 2-26	DBDs	(116)
	Immunoglobulin κ-chain	DBDs and DCDs	(17)
	Immunoglobulin γ1-chain	DBDs and DCDs	(17)
	Immunoglobulin γ2-chain	DBDs and DCDs	(17)
	Immunoglobulin γ3-chain	DBDs and DCDs	(17)
	Immunoglobulin γ3-chain	DBDs and DCDs	(17)
	Vascular cell adhesion molecule	DBDs	(141)
	Intercellular adhesion molecule	DBDs	(141)
	TNF-α	DBDs	(141)
	IFN-γ	DBDs	(141)
	IL-1β, -2, -6, -18	DBDs and DCDs	(56,141)
	IL-4, -8, -10	Not mentioned	(145,146)
	IL-1Rα	Not mentioned	(145)
	IL-6R	DBDs	(141)
	Macrophage inflammatory protein-1α	Not mentioned	(145)
	Monocyte chemoattractant protein-1	Not mentioned	(145)
	Chemokine (C-X-C motif) ligand 1	DBDs	(141)
Cellular iron homeostasis	Transferrin	DBDs and DCDs	(17)
	Hemopexin	DBDs and DCDs	(17)
	Haptoglobin	DBDs and DCDs	(17)
	Oxyhemoglobin	DCDs	(117)
Blood coagulation	Fibrinogen γ-chain	DBDs and DCDs	(17)
	Fibrinogen α-chain	DCDs	(117)
	Annexin A5	DBDs and DCDs	(17)
	Plasminogen activator inhibitor-1	DBDs and DCDs	(17)
Transport proteins	Transthyretin	DBDs and DCDs	(17)
	Albumin	DBDs and DCDs	(17)
	Vitamin D binding protein	DBDs and DCDs	(17)
	High density lipoprotein	DCDs	(117)

[i] DBDs, donations after brain death; DCDs, donation after cardiac death; LKDs, living kidney donors; FABP, fatty acid binding protein.

Novel directions and highlights in proteomic studies

Whole-proteome analysis

Studies conducted over the past decade have provided novel insights and techniques into the proteomic analysis of the renal perfusate, where untargeted protein analysis techniques, including two-dimensional-polyacrylamide gel electrophoresis (2D-PAGE) and liquid chromatography-mass spectrometry (LC-MS), have been devised.

2D-PAGE (109) is a potent method for detecting nearly all protein elements in tested samples. According to this technique, proteins are separated according to their isoelectric points by isoelectric focusing, followed by SDS-PAGE, which segregates proteins based on their molecular weight and electrical charge (110). Staining with Coomassie Blue or silver helps to identify the target protein fractions, which can then be excised for further analysis (111).

LC-MS is currently the most accurate method for proteomic investigation (112). This tool involves digesting the protein sample with proteolytic enzymes, which is most commonly trypsin, to generate unique protein mass value. These peptides are then separated by high-performance liquid chromatography. After separation, MS is used to analyze each peak, converting the samples to the gas phase and transferring them to the ionization chamber. Electrospray ionization then ionizes the samples into cations, which are subsequently separated based on their mass-to-charge ratio using a mass analyzer. The detector identifies and quantifies each ion and the results are compared with database information (113). Proteomics most frequently uses the following two modifications of the MS element known as the ionizer: i) Matrix-assisted laser desorption/ionization (MALDI), which is laser desorption with the participation of a matrix; and ii) electrospray ionization. Other modifications can also be made to mass analyzers. They include quadrupole mass analyzers, Fourier transform ion cyclotron mass analyzer, Orbitrap mass analyzers, ion trap mass analyzer and TOF mass analyzer (114). At present, the most commonly applied method in proteome research is the time-of-flight (TOF) analyzer combined with a MALDI ionizer (113). TOF allows for the study of the flight time of ions between the ionizer and the detector, which depends on the ratio of the mass to the number of ion charges (112). The greatest advantage of MALDI-TOF is the direct detection of the composition of a complex mixture of proteins and other molecules (113,115). The underlying principles of both 2D-PAGE and LC-MS are shown in Fig. 3.

Figure 3 Whole-proteome analysis methods. LC-MS serves as a vital tool for whole-proteome analysis. This method involves digesting the protein sample with proteolytic enzymes, commonly trypsin, generating unique protein mass value. These peptides are then subjected to HPLC for separation. (A) After separation, MS analyzes each peak, converting samples to the gas phase and transferring them to the ionization chamber. (B) Electrospray ionization ionizes the samples into cations, which are subsequently separated based on their mass-to-charge ratio in a mass analyzer. The detector identifies and quantifies each ion, with results compared to database information. (C) 2D-PAGE is a potent method for detecting nearly all protein elements in tested samples. Proteins are separated according to their isoelectric points through isoelectric focusing, followed by SDS-PAGE, which segregates proteins based on their molecular mass and electrical charge. Staining with Coomassie Blue or silver helps to identify the target protein fractions, which can then be excised for further analysis. The figure was created with BioRender® Science Suite Inc. LC, liquid chromatography; HPLC, high performance LC; MS, mass spectrometry; IEF, isoelectic focusing.

Complement elements

Previous studies on LC-MS analysis have highlighted the role of the complement system in renal injury during HMP and oxygenated-HMP (116,117). The complement system forms a part of the innate immune response that contributes to extensive endothelial cell damage (118). This system contains soluble proteins (such as C3a, C3b and C5a) and membrane-bound proteins (C5b, C6, C7, C8 and C9). Under physiological conditions, regulatory proteins control the degradation of C3 and C5 convertases to prevent overreactions (118-120). Different elements are involved in three pathways: Classical, alternative and lectin pathways. Both ischemia and reperfusion are important factors that can trigger the activation of the complement system (121). In addition, preformed donor-specific antibodies can activate the complement system by binding to C1q or C3d (122,123). Activation by DAMPs released during ischemia and reperfusion leads to the formation of a membrane-associated complex (MAC). This complex is comprised of C5b-9 subunits and has been implicated in apoptosis induction (124,125), direct cell injury, necrosis and neutrophil influx (126). MAC can also induce a pro-inflammatory response through the NF-κB signaling pathway in endothelial cells (127). Fig. 4 presents the different pathways of the complement system.

Figure 4 Complement pathways. The complement system is comprised of soluble proteins and membrane-bound receptors. Under physiological conditions, regulatory proteins control the degradation of C3 and C5 convertases to prevent overreactions. The indiscriminate activation of complement system necessitates the presence of preformed regulators on autologous surfaces to spare self-cells from the undirected nature of alternative pathway activation. Different elements, such as C1gC1r2C1s2 complex, MASP1/2 and C3, are involved in three pathways: classical, alternative and lectin pathways. Both ischemia and reperfusion are important factors that can trigger activation of the complement system. Activation by DAMPs released during ischemia and reperfusion leads to the formation of a membrane-associated complex, which consists of C5b-9 subunits. The figure was created with BioRender® Science Suite Inc. DAMP, damage-associated molecular pattern; MASP1/2, Mannan-binding lectin serine protease 1.

A previous study was performed on 22 kidneys retrieved from DBDs stored in HMP (116). Perfusate samples that were obtained after 15 min of HMP in patients with a good outcome (GO) at 1-year post-transplantation (eGFR ≥45 ml/min/1.73 m2 and sCr level ≤120 μmol/l) were found to contain more complement C1q subcomponent subunit B, complement C1s subcomponent (C1S), complement C1r subcomponent (C1R) and C4b binding protein α chain compared with those in perfusate samples of patients with a suboptimal outcome (SO) at 1-year post-transplantation (eGFR ≤45 ml/min/1.73 m2 and sCr level ≥120 μmol/l). Similar observations were made for samples collected after 4 h of HMP. In the GO group, complement C1r subcomponent-like protein, C1S and C1R were also found to be significantly upregulated compared with those in the SO group. The authors showed that the statistically significant difference in the concentration of complement elements can distinguish between GO and SO at 1-year post-transplantation (116).

Another study by Mulvey et al (117) focused on the proteomic investigation of the perfusate from 67 paired DCDs kidneys stored in oxygenated and non-oxygenated HMP, yielding 1,716 proteins including complement cascade, platelet aggregation and detoxification of reactive oxygen species. The most abundant proteins identified were complement C3, apolipoprotein A1 and fibrinogen α chain. One of the most abundant proteins was found to be C3. In addition, complement cascade proteins (such as C1R, C1QC, C3, C5, C7, C8A and C8G) were correlated with 12-month eGFR, where their abundance decreased during HMP (117). Oxygenation did not affect the proteome profile, including that of the complement cascade (117). Using porcine kidneys and discarded human kidneys (128), perfusion was previously conducted with a blood-based solution for 4 and 6 h. C3a, C3d and soluble C5b-9 (sC5b-9) were then measured in perfusate samples. In porcine kidneys, the presence of sC5b-9 was reported to contribute to lower creatinine clearance. It was then observed that the levels of complement products in the perfusate were higher in the kidneys from DBDs compared with those from DCDs.

Cytoskeletal structural elements

To identify novel biomarkers, cytoskeletal structural elements have been previously studied. These biomarkers tend to be associated with non-specific cellular damage (34,116,129), unlike the aforementioned markers associated with specific pathways or systems. During ischemia, metabolism switches from aerobic to anaerobic conditions (130). This results in increased lactate production and intracellular acidosis. These conditions inhibit Na+/K+-dependent ATPase activity, leading to the accumulation of sodium ions and cellular edema (131). Other consequences of ischemia include leakage of lysosomal enzymes, cytoskeletal breakdown and decreased calcium excretion (130). In addition, the excess calcium accumulation that ensues leads to the generation of ROS (132), but the quantity of ROS generated is not as potent as that during reperfusion. This is due to the reduction in the activity of cytochromes, nitric oxide synthases, xanthine oxidase and reduced nicotinamide adenine dinucleotide phosphate oxidase activity (130). Ischemia has been shown to trigger the expression and redistribution of microtubule cytoskeletal elements (such as actin, fodrin, tubulin and uvomorulin) (133,134). Cell integrity is then altered, leading to loss of cell polarity and redistribution of the basolateral membrane (135). These conditions can lead to various forms of cell death, including necrosis, apoptosis, autophagy and programmed necrosis (136).

A study by Coskun et al (129) revealed a group of structural proteins associated with cellular damage in the kidney. In particular, the preservation solution from 25 kidneys retrieved from DBDs stored in SCS was analyzed. Among the 206 proteins identified, a subset that associated significantly with donor characteristics was identified. Specifically, perlecan levels were correlated positively with sCr and blood urea nitrogen (BUN) levels, increased level of talin-1 was related positively to CIT, keratin type II cytoskeletal 8 was associated positively with recipient sCr, whilst profilin was associated positively with donor age (DA) and recipient BUN levels, myosin 6, 9 and 11 were correlated with DA, collagen VI from epithelial cells was associated positively with DA and recipient BUN levels, whereas microfibril-associated glycoprotein 4 was associated positively with DA and recipient sCr (113). Another study also to previously investigated HMP perfusates for the presences of structural components. van Leeuwen et al (116) studied 22 DBD kidneys and found a positive correlation between actinin-1 and talin-1 concentration in the perfusate and the 1-year post-transplant function expressed by eGFR. Upregulated cytoskeletal proteins actinin-1 and talin-1 in the HMP perfusate after 4 h of HMP discriminated kidneys with GO and SO after 1-year post-transplantation. It was therefore hypothesized that lower eGFR in the SO group was a result of the loss of cellular integrity and disruption in the podocyte architecture (116). In addition, this previous study (116) reported that the presence of desmoplakin quantified within LC-MS in the HMP perfusate after 4 h of perfusion was associated with SO. Desmoplakin is one of the most abundant components in desmosomes and cellular junctions (137). Together with immunoglobulin heavy variable 2-26, desmoplakin had a predictive value of 86% for SO occurrence in the first year after transplantation (116). The designs and results of whole-proteome studies are listed in Tables II and III.

Table II Whole proteome analysis study designs.

Table II

Whole proteome analysis study designs.

Author, year	Analytical method	Type of donor	Kidney amount	Outcome	Time of sample acquistion	(Refs.)
Snoeijs et al, 2013	i) 2D-DIGE; ii) LC-MS (spots identification)	DCD and DBD	18 (6 uncontrolled DCD; 6 controlled DCD; 6 DBD)	Immediate function/DGF/PNF	1 h of HMP	(17)
Moser et al, 2017	i) 2D-DIGE; ii) MS (spots identification); iii) Western blotting (results confirmation)	DCD, DBD, LKD	41 (9 DCD, 16 DBD, 16 LKD)	DGF/SGF (SGF was defined as serum creatinine >265 μmol/l on post-transplant day 5 but no need for dialysis by day 5)	End of HMP	(34)
van Leeuwen et al, 2021	LC-MS	DBD	22	Suboptimal outcome at 1-year post-transplantation (kidney function with an eGFR ≥45 ml/min/1.73 m2 and a serum creatinine level of ≤120 μmol/l); good outcome at1-year post-transplantation (kidneys with an eGFR ≤45 ml/min/1.73 m2 and a serum creatinine level of ≥120 μmol/l 1-year post-transplantation)	15 min of HMP (T1) and just before ending HMP (T2)	(116)
Mulvey et al, 2023	LC-MS	DCD	137	eGFR measured one year after kidney transplant	15 min of HMP; just before leaving donor's hospital; end of HMP	(117)

[i] DBDs, donations after brain death; DCDs, donation after cardiac death; LKDs, living kidney donors; LC, liquid chromatography; MS, mass spectrometry; DIGE dimensional gel electrophoresis; eGFR, estimated glomerular filtration rate; DGF, delayed graft function; SGF, slow graft function; HMP, hypothermic machine perfusion.

Table III Whole proteome analysis study results.

Table III

Whole proteome analysis study results.

Authors, year	Number of detected proteins	Number of selected proteins	Clinical outcome	Analytical method	Significance	(Refs.)
Snoeijs et al, 2013	64	19	Uncontrolled DCD, 4 DGF and 2 PNF; Controlled DCD, 3 IF and3 DGF; DBD, 3 IF and 3 DGF	i) 2D-DIGE; ii) LC-MS (spots identification)	i) α1-antitrypsin was upregulated in kidneys (considering all donor types) with DGF; ii) haptoglobin was downregulated in the perfusate of DCD kidneys (compared with DBD kidneys)	(17)
Moser et al, 2017	Not mentioned	7	Not mentioned	i) 2D-DIGE; ii) MS (spots identification) Western Blot (results confirmation)	i) total protein concentration-DCD > DBD > LKD; ii) 7 protein significantly different among the 3 groups, namely serum albumin, α-1-antitrypsin peroxiredoxin-2, heavy chain of immuno-globulin, fragment of collagen 1 and fatty acid binding protein, protein deglycase	(34)
van Leeuwen et al, 2021	1,255	T1, 28; T2, 48	GO, 11 [12-month eGFR 67.4 (15.5)]; SO, 11 [12-month eGFR 27.6 (9.7)]	LC-MS	T1: i) 18 proteins significantly upregulated in GO vs. SO.; ii) all significant proteins are located in extracellular regions, 5 of them belong to complement and coagulation cascades, including complement C1q subcomponent subunit B, complement C1s subcomponent, complement C1r subcomponent and C4b-binding protein α chain; iii) at T1, ATP-citrate synthase together with fatty acid binding protein 5 provided a predictive value of 91%, corresponding to a ROC with AUC of 0.97; and iv) 10 proteins significantly downregulated in GO vs. SO, 2 of them, fatty acid binding protein 4 and fatty acid binding protein 5, are involved in Peroxisome proliferator-activated receptor signalling. T2: i) 22 proteins significantly upregulated in GO vs. SO, 5 of them belong to complement and coagulation cascades, of which 4 are involved in complement activation of the classical pathway, namely complement C1r subcomponent-like protein, C1S and C1; ii) 26 proteins significantly downregulated in GO vs. SO, 14 of them are cytoskeletal proteins, including desmoplakin, talin-1 and α-actinin-1, 13 of the downregulated proteins are affiliated with the immune system; and iii) immunoglobulin heavy variable 2-26 togetherx heavy desmoplakine provided a predictive value of 86%, corresponding to ROC with AUC of 0.95 for 26 proteins.	(116)
Mulvey et al, 2023	1,716	137	Mean eGFR in HMP + O2 group, 41 ml/min/1, 73 m2; In HMP without O2 group, 40 ml/min/1, 73 m2	LC-MS	i) Overall HMP duration associated with increasing levels of a subgroup of proteins; ii) HDL and complement cascade proteins are associated with 12-month eGFR; iii) blood-derived proteins are enriched in the perfusate of kidneys that developed acute rejection, these proteins belonged to 'regulation of response to wound healing' and 'metabolic processes contributed to ATP generation and nucleotide phosphorylation'; iv) the most abundant proteins in all samples were complement C3, apolipoprotein A1 and fibrinogen α-chain	(117)

[i] DBDs, donations after brain death; DCDs, donation after cardiac death; LKDs, living kidney donors; DGF, delayed graft function; IF, immediate function; LC, liquid chromatography; MS, mass spectrometry; DIGE dimensional gel electrophoresis; eGFR, estimated glomerular filtration rate; GO, good outcome; SO, suboptimal outcome; ROC, receiver operating characteristic; AUC, area under the curve; HMP, hypothermic machine perfusion.

Other directions in proteomic investigations

Both 2D-PAGE and LC-MS have certain limitations. 2D-PAGE lacks specificity and frequently requires additional methods, such as western blotting, to confirm protein identity (111). LC-MS in contrast commands substantial financial investment, specialized equipment and trained personnel. Sample preparation for quantification is also time-consuming (112).

Modern methods, such as microarrays or protein chips, have emerged for the analysis of large protein panels (138). These microarrays contain predefined panels of proteins or antibodies tailored to the objectives of the experiment, such as analysis of specific protein fractions, cancer markers or virus antigens. Upon addition of the sample to the microarray plate, proteins will bind to the antibodies if present. Antibodies conjugated to fluorochromes are then introduced and bind to the previously formed complexes. This process distinguishes between capture, reverse and functional arrays, each designed for distinct analytical purposes. Fluorescent detectors then provide quantitative and qualitative results, enabling the simultaneous measurement of multiple compounds from a single sample (139). When the focus is on a limited number of proteins or a single protein, light scattering-based protein analysis techniques come into play. These include batch dynamic light scattering, static light scattering, charge and ζ potential measurements, in addition to circular dichroism spectrometry and isothermal titration calorimetry. These methods provide valuable information regarding protein size, abundance, charge, chirality, interactions and binding to other molecules (138,140). Perfusate analysis using a method that is a bridge between classical ELISA and microarrays, such as a multiplex immunoassay on a single platform, was performed by Baboudjian et al (141) in a prospective study of 74 kidneys from deceased donors (both ECDs and SCDs). VCAM obtained at the end of HMP was found to be a non-invasive predictor of early graft dysfunction at both 1 week (OR=3.57; 95% CI, 1.06-12.03) and 3 months (OR=4.039; 95% CI, 1.11-14.73) after transplantation (141). Table IV lists all the techniques utilized for proteomic analysis of renal perfusate. Fig. 5 shows a representative multiplex immunoassay on one platform and different types of ELISA.

Figure 5 Multiplex immunoassay on one platform and different types of ELISA. (A) Scheme of a representative multiplex immunoassay on one platform, such as the Human Luminex® Discovery Assay (Luminex Corporation; DiaSorin S.p.A.). The method relies on the simultaneous binding of proteins of interest to specific antibody-conjugated beads. The complex protein-bead-antibody is then conjugated to a fluorescent antibody, where the specific signals of the protein of interest are emitted by the fluorescent antibody and analyzed by a laser detector. (B) ELISA is based on protein identification by binding a specific antibody to an antigen present on the molecule of interest and detecting a signal from the staining agent conjugated to an antibody. It can be performed in the following four manners: Direct, indirect, sandwich and competitive. The figure was created with BioRender® Science Suite Inc. mAb, monoclonal antibody; VCAM, Vascular cell adhesion protein 1; PE, Phycoerythrin.

Table IV Analytical methods for protein detection in perfusate.

Table IV

Analytical methods for protein detection in perfusate.

Method	Mechanism of action	Advantages	Disadvantages
LC and high-performance LC	Separation and identification of proteins by mass transfer of a sample through a polar mobile phase and a non-polar stationary phase.	i) High resolution and speed of analysis; ii) precise flow rate control; iii) senstive detection; and iv) low sample requirement	i) Expensive solvents and columns; ii) regular maintenance and calibration is needed; and iii) sophisticated software is required
LC-mass spectrometry	Mixtures are separated according to their physical and chemical properties, then the components within each peak are identified and detected based on their mass spectrum	i) The capability to quantify multiple analytes simultaneously; and ii) the method does not necessarily require immunological reagents	i) Regular maintenance and calibration is needed; ii) sophisticated software is required; iii) the instrument requires skilled personnel; and iv) expensive
2D-PAGE	Separation of proteins in SDS gel by PAGE first by their charge then by their size, identifying each protein after staining for example within Coomassie Blue	i) Enables the detection of hundreds of proteins on a single gel plate; and ii) enhanced resolution, detection, quantitation and reproducibility	i) Inability to resolve proteins that are too basic or too acidic, too large or too small; and ii) restricted to soluble and/or high abundant proteins
Enzymatic activity assay	Carry out a reaction catalyzed by the protein under investigation and measure the concentration of the enzyme product using colorimetric, chemiluminescent or fluorescent method	i) High sensitivity and specificity; ii) rapid response; iii) easy to perform	i) Difficulties in assay standardization; ii) instability of the enzymesduring storage
ELISA	Protein identification by binding a specific antibody to an antigen present on the desired molecule anddetecting a signal from staining agent conjugated with an antibody. It could be performed in 4 manners:Direct, indirect, Sandwich, competitive	i high sensitivity and specificity; ii) high throughput; iii) easy to perform; and iv) it can determine the concentration of antigen in a sample	i) Information limited to the amount or presence of the antigen in the sample; ii) detection is based on enzyme/substrate reactions
Western blotting	Separation of proteins by gel electrophoresis to resolve them by size and transfer to a membrane to immobilize the proteins. The proteins immobilized on the membrane are then identified in an immunoassay using colorimetric, chemiluminescent or fluorescent detection	i) The ability to identify specific target proteins; and ii) high sensitivity	i) Time-consuming procedure; ii) problems in reproducibility; and iii) false-positive results when an antibody reacts with a non-intended protein
Multiplex immunoassay on one platform	Simultaneous binding of proteins of interest to specific antibody conjugated beads, complex protein bead-antibody is conjugated to the fluorescent antibody, the specific signals of protein of interest are emitted by the fluorescent antibody and analyzed using a laser detector	i) Good reproducibility; ii) rapid processing speed; iii) low sample volume; and iv) high sensitivity	i) Cross-reactivity; ii) assay development time; iii) commitment to vendor-supplied assays; and iv) dynamic range

[i] LC, liquid chromatography.

Other potential protein biomarkers

In whole-proteome studies, other non-specific proteins associated with kidney injury have been detected in HMP perfusates. Proteins found at statistically significant levels include immunoglobulins κ, γ1, γ2 and γ3 chains (17). α1-Anti-trypsin with peroxidoxin-2 may discriminate between renal damage in DBDs, DCDs and LKDs (34).

Another group of proteins considered to be biomarkers and detected by whole-proteome analysis methods include proteins involved in transport (transthyretin, albumin and vitamin D-binding protein), blood coagulation (fibrinogen α-chain, fibrinogen γ-chain, annexin A5 and plasminogen activator inhibitor-1), energy metabolism (alcohol dehydrogenase subunit β, GAPDH, α-enolase, aldose reductase and aminoacylase), cellular iron homeostasis (transferrin, hemopexin, haptoglobin and oxyhemoglobin) and high-density lipoproteins (17,31). However, further studies are required to confirm their role in predicting short- and long-term outcomes in recipients.

A previous targeted proteomic analysis revealed the presence of Ala-AP (41,142), leucyl- and pyroglutamyl aminopeptidase (143), alanyl-arginyl- and dipeptidyl IV-aminopeptidase (143), aspartate aminotransferase (33) and N-acetyl-β-d-gluconamidase (33), glutathione peroxidase, catalase and superoxide dismutase (144), TNF-α, IFN-γ (141), IL-1β, -2, -4, -6, -8 and -10 (141,145,146), IL-1Rα, macrophage inflammatory protein-1, monocyte chemoattractant protein-1 (145), IL-6R and chemokine C-X-C motif ligand 1 (141). However, these proteins have been previously investigated, but none was found to be a reliable predictor of short- or long-term outcomes in recipients.

Conclusions and future perspectives

The number of patients with end-stage renal disease awaiting kidney transplantation is much higher compared with the number of transplanted organs (147). Therefore, an increasing number of kidneys have been retrieved from ECDs, which increases the risk of poor outcomes (148-150). However, organs in good condition, namely those not developing DGF or not requiring continuous dialysis therapy after KTx, are typically selected from this donor group.

Proteomic analysis of the perfusate remains to be a promising tool for the evaluation of kidneys before transplantation. This is especially true for the ECDs, DCDs and SCDs. Despite previous studies on this topic, protein markers that are sufficiently accurate for predicting the state of the kidney before KTx have remained elusive. However, the problem lies in the methodologies used in such studies. Searching for only one or a small group of proteins may not be the optimal approach. Changes in kidney metabolism during the entire transplantation procedure are extensive and must be monitored constantly. Therefore, biomarkers should include a large panel of proteins. Modern techniques of protein analysis will allow for such studies, whereas fast diagnostic methods (such as microarrays) will allow for the up-to-date supervision of kidney state during perfusion. To identify a reliable group of markers, profiling research must show the correlations of altered protein levels in the kidney and metabolic pathways activated during organ transplantation. Such pathways include ischemia-reperfusion, endothelial reticulum stress, oxidative stress and autophagy pathways. The optimal panel of markers should establish connections with all the proteins.

Another consideration should be the type of materials used for proteomic analysis. The present study has described proteins detected during HMP, which is a recognized method for kidney preservation, particularly for organs from ECDs (151,152). Continuous or pulsatile perfusion allows for the release and secretion of proteins into the perfusate. As a result, the dynamics of the processes during the HMP can be monitored. In addition, the quantity of proteins detected is likely to be more reliable compared with that detected during SCS. HMP ensures the removal of blood residues that may interfere with the final conclusions regarding the proteome profile.

Proteomic studies should be performed in different donor groups if the study aims to find an association between the detected protein and the selected endpoint. Various factors, such as CIT (153), diabetes and hypertension (154), cause of mortality (34), age (155,156) and terminal sCr level (157,158), can all affect the condition of the donated kidneys. Mixing organs from ECDs and SCDs will not lead to correct conclusions in the context of the selected endpoint due to the aforementioned factors. Another issue is defining the endpoint. In the majority of studies, DGF was defined as the need for dialysis within the first week after KTx (159-162). However, dialysis can be performed due to post-operative hyperkalemia or fluid overload that does not result from renal injury (163,164). Further studies should consider a more appropriate definition of DGF and other endpoints.

The quantification method is crucial for certain proteins. This applies to biomarkers that have isoforms, such as GSTs or form complexes, such as NGAL. Once a biomarker has been selected from the entire proteome, the next step should involve finding a suitable laboratory test or developing a novel method to detect the entire quantity of the desired molecule.

In summary, although numerous studies have been conducted with conflicting results, perfusate remains to be a promising source of protein biomarkers. Novel studies concerning the aforementioned issues may unravel other properties of well-known proteins, such as NGAL, KIM-1 or MMPs. Whole-proteome techniques will likely provide insights into non-specific kidney processes during preservation and complex protein profiles of numerous biological samples. Methods such as immunofixation, western blotting and ELISA enable the precise detection and quantification of specific proteins based on existing data. Immunofixation separates proteins electrophoretically and identifies them using specific antibodies, whilst western blotting employs primary and secondary antibodies for protein detection and ELISA quantifies proteins through spectrophotometric analysis.

Current advancements for studying proteins include microarrays and protein chips, which will allow for the simultaneous analysis of multiple targets. These techniques are particularly beneficial for studying specific protein fractions, cancer markers or viral antigens. Light scattering methods, such as dynamic light scattering and circular dichroism spectrometry, provide additional details on protein size, charge and interactions. Untargeted techniques, such as 2D-PAGE and LC-MS, enable comprehensive proteome profiling. 2D-PAGE separates proteins by isoelectric point and molecular mass, whereas LC-MS identifies proteins through peptide mass fingerprints and enzymatic digestion. Despite their complexity and cost, these methods will prove crucial for identifying novel proteins and understanding proteomic changes. Collectively, these techniques compose a robust framework for proteomic analysis, which is expected to advance the current understanding of protein function, interactions and roles in renal health and disease.

Recent studies on the role of the complement system and cytoskeletal elements show the association with short- and long-term outcomes (116,117,129). However, randomized controlled trials are required to establish their role in the assessment of kidney quality before transplantation. In addition, targeted methods for a protein of interest should be developed for further analysis. Despite novel storage protocols, such as NMP and SNMP, hypothermic methods remain in use in numerous countries and proteomic analysis of these perfusate is justified. SCS is the current storage standard for kidneys procured from DCDs in the UK (165). In the Netherlands, HMP is the standard method for kidney preservation in all donor types (166). To date, one randomized controlled trial has been performed in which SCS alone was compared with SCS plus a 1-h period of NMP at the end of storage (165). This previous study showed that SCS plus 1-h of NMP is not superior in reducing the DGF rate compared with kidney preservation by SCS alone, since this method did not improve the long-term results (135). However, additional studies comparing longer periods of NMP with HMP (165,167) are essential to confirm the safety and superiority of normothermic techniques over HMP or SCS. Nevertheless, proteomic analysis of the solutions used for normothermic perfusion should be performed as a source of novel biomarkers.

Availability of data and materials

Not applicable.

Authors' contributions

MB contributed to the design of the review. MB and MiS wrote the manuscript. MB and RD saw and verified all articles included in this review from the following four databases: Embase, PubMed (Medline), Web of Sscience and Scopus. MB designed the figures and tables. MiS, RD, MK and MaS revised the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Acknowledgements

The authors would like to thank Ms Anna Palińska (Off Course School, Warsaw) for creating the figures with BioRender® Science Suite Inc.

Funding

No funding was received.

References