Serum N-Glycosylation RPLC-FD-MS Assay to Assess Colorectal Cancer Surgical Interventions.

A newly developed analytical strategy was applied to profile the total serum N-glycome of 64 colorectal cancer (CRC) patients before and after surgical intervention. In this cohort, it was previously found that serum N-glycome alterations in CRC were associated with patient survival. Here, fluorescent labeling of serum N-glycans was applied using procainamide and followed by sialic acid derivatization specific for α2,6- and α2,3-linkage types via ethyl esterification and amidation, respectively. This strategy allowed efficient separation of specific positional isomers on reversed-phase liquid chromatography-fluorescence detection-mass spectrometry (RPLC-FD-MS) and complemented the previous glycomics data based on matrix-assisted laser desorption/ionization (MALDI)-MS that did not include such separations. The results from comparing pre-operative CRC to post-operative samples were in agreement with studies that identified a decrease in di-antennary structures with core fucosylation and an increase in sialylated tri- and tetra-antennary N-glycans in CRC patient sera. Pre-operative abundances of N-glycans showed good performance for the classification of adenocarcinoma and led to the revisit of the previous MALDI-MS dataset with regard to histological and clinical data. This strategy has the potential to monitor patient profiles before, during, and after clinical events such as treatment, therapy, or surgery and should also be further explored.

Development of Tier 2 LC-MRM-MS protein quantification methods for liquid biopsies.

In the pursuit of personalized diagnostics and tailored treatments, quantitative protein tests contribute to a more precise definition of health and disease. The development of new quantitative protein tests should be driven by an unmet clinical need and performed in a collaborative effort that involves all stakeholders. With regard to the analytical part, mass spectrometry (MS)-based platforms are an excellent tool for quantification of specific proteins in body fluids, for example focused on cancer. The obtained readouts have great potential in determining tumor aggressiveness to facilitate treatment decisions, and can furthermore be used to monitor patient response. Internationally standardized TNM classifications of malignant tumors are beneficial for diagnosis, however treatment outcome and survival of cancer patients is poorly predicted. To this end, the importance of the tumor microenvironment has endorsed the introduction of the tumor-stroma ratio as a prognostic parameter in solid primary tumor types. Currently, the stromal content of tumor tissues is determined via routine diagnostic pathology slides. With the development of liquid chromatography (LC)-MS methods we aim at quantification of tumor-stroma specific proteins in body fluids. In this mini-review the analytical aspect of this developmental trajectory is further detailed.

Longitudinal Serum Protein Analysis of Women with a High Risk of Developing Breast Cancer Reveals Large Interpatient Versus Small Intrapatient Variations: First Results from the TESTBREAST Study.

The prospective, multicenter TESTBREAST study was initiated with the aim of identifying a novel panel of blood-based protein biomarkers to enable early breast cancer detection for moderate-to-high-risk women. Serum samples were collected every (half) year up until diagnosis. Protein levels were longitudinally measured to determine intrapatient and interpatient variabilities. To this end, protein cluster patterns were evaluated to form a conceptual basis for further clinical analyses. Using a mass spectrometry-based bottom-up proteomics strategy, the protein abundance of 30 samples was analyzed: five sequential serum samples from six high-risk women; three who developed a breast malignancy (cases) and three who did not (controls). Serum samples were chromatographically fractionated and an in-depth serum proteome was acquired. Cluster analyses were applied to indicate differences between and within protein levels in serum samples of individuals. Statistical analyses were performed using ANOVA to select proteins with a high level of clustering. Cluster analyses on 30 serum samples revealed unique patterns of protein clustering for each patient, indicating a greater interpatient than intrapatient variability in protein levels of the longitudinally acquired samples. Moreover, the most distinctive proteins in the cluster analysis were identified. Strong clustering patterns within longitudinal intrapatient samples have demonstrated the importance of identifying small changes in protein levels for individuals over time. This underlines the significance of longitudinal serum measurements, that patients can serve as their own controls, and the relevance of the current study set-up for early detection. The TESTBREAST study will continue its pursuit toward establishing a protein panel for early breast cancer detection.

Serum N-glycan profiles differ for various breast cancer subtypes.

Breast cancer is the most prevalent cancer in women. Early detection of this disease improves survival and therefore population screenings, based on mammography, are performed. However, the sensitivity of this screening modality is not optimal and new screening methods, such as blood tests, are being explored. Most of the analyses that aim for early detection focus on proteins in the bloodstream. In this study, the biomarker potential of total serum N-glycosylation analysis was explored with regard to detection of breast cancer. In an age-matched case-control setup serum protein N-glycan profiles from 145 breast cancer patients were compared to those from 171 healthy individuals. N-glycans were enzymatically released, chemically derivatized to preserve linkage-specificity of sialic acids and characterized by high resolution mass spectrometry. Logistic regression analysis was used to evaluate associations of specific N-glycan structures as well as N-glycosylation traits with breast cancer. In a case-control comparison three associations were found, namely a lower level of a two triantennary glycans and a higher level of one tetraantennary glycan in cancer patients. Of note, various other N-glycomic signatures that had previously been reported were not replicated in the current cohort. It was further evaluated whether the lack of replication of breast cancer N-glycomic signatures could be partly explained by the heterogenous character of the disease since the studies performed so far were based on cohorts that included diverging subtypes in different numbers. It was found that serum N-glycan profiles differed for the various cancer subtypes that were analyzed in this study.

Clinical Perspective on Proteomic and Glycomic Biomarkers for Diagnosis, Prognosis, and Prediction of Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is known as a highly aggressive malignant disease. Prognosis for patients is notoriously poor, despite improvements in surgical techniques and new (neo)adjuvant chemotherapy regimens. Early detection of PDAC may increase the overall survival. It is furthermore foreseen that precision medicine will provide improved prognostic stratification and prediction of therapeutic response. In this review, omics-based discovery efforts are presented that aim for novel diagnostic and prognostic biomarkers of PDAC. For this purpose, we systematically evaluated the literature published between 1999 and 2020 with a focus on protein- and protein-glycosylation biomarkers in pancreatic cancer patients. Besides genomic and transcriptomic approaches, mass spectrometry (MS)-based proteomics and glycomics of blood- and tissue-derived samples from PDAC patients have yielded new candidates with biomarker potential. However, for reasons discussed in this review, the validation and clinical translation of these candidate markers has not been successful. Consequently, there has been a change of mindset from initial efforts to identify new unimarkers into the current hypothesis that a combination of biomarkers better suits a diagnostic or prognostic panel. With continuing development of current research methods and available techniques combined with careful study designs, new biomarkers could contribute to improved detection, prognosis, and prediction of pancreatic cancer.

The Time Has Come for Quantitative Protein Mass Spectrometry Tests That Target Unmet Clinical Needs.

Protein mass spectrometry (MS) is an enabling technology that is ideally suited for precision diagnostics. In contrast to immunoassays with indirect readouts, MS quantifications are multiplexed and include identification of proteoforms in a direct manner. Although widely used for routine measurements of drugs and metabolites, the number of clinical MS-based protein applications is limited. In this paper, we share our experience and aim to take away the concerns that have kept laboratory medicine from implementing quantitative protein MS. To ensure added value of new medical tests and guarantee accurate test results, five key elements of test evaluation have been established by a working group within the European Federation for Clinical Chemistry and Laboratory Medicine. Moreover, it is emphasized to identify clinical gaps in the contemporary clinical pathways before test development is started. We demonstrate that quantitative protein MS tests that provide an additional layer of clinical information have robust performance and meet long-term desirable analytical performance specifications as exemplified by our own experience. Yet, the adoption of quantitative protein MS tests into medical laboratories is seriously hampered due to its complexity, lack of robotization and high initial investment costs. Successful and widespread implementation in medical laboratories requires uptake and automation of this next generation protein technology by the In-Vitro Diagnostics industry. Also, training curricula of lab workers and lab specialists should include education on enabling technologies for transitioning to precision medicine by quantitative protein MS tests.

Serum N-Glycome analysis reveals pancreatic cancer disease signatures.

BACKGROUND &AIMS: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer type with loco-regional spread that makes the tumor surgically unresectable. Novel diagnostic tools are needed to improve detection of PDAC and increase patient survival. In this study we explore serum protein N-glycan profiles from PDAC patients with regard to their applicability to serve as a disease biomarker panel. METHODS: Total serum N-glycome analysis was applied to a discovery set (86 PDAC cases/84 controls) followed by independent validation (26 cases/26 controls) using in-house collected serum specimens. Protein N-glycan profiles were obtained using ultrahigh resolution mass spectrometry and included linkage-specific sialic acid information. N-glycans were relatively quantified and case-control classification performance was evaluated based on glycosylation traits such as branching, fucosylation, and sialylation. RESULTS: In PDAC patients a higher level of branching (OR 6.19, P-value 9.21 × 10-11 ) and (antenna)fucosylation (OR 13.27, P-value 2.31 × 10-9 ) of N-glycans was found. Furthermore, the ratio of α2,6- vs α2,3-linked sialylation was higher in patients compared to healthy controls. A classification model built with three glycosylation traits was used for discovery (AUC 0.88) and independent validation (AUC 0.81), with sensitivity and specificity values of 0.85 and 0.71 for the discovery set and 0.75 and 0.72 for the validation set. CONCLUSION: Serum N-glycome analysis revealed glycosylation differences that allow classification of PDAC patients from healthy controls. It was demonstrated that glycosylation traits rather than single N-glycan structures obtained in this clinical glycomics study can serve as a basis for further development of a blood-based diagnostic test.

HILIC-MRM-MS for Linkage-Specific Separation of Sialylated Glycopeptides to Quantify Prostate-Specific Antigen Proteoforms.

Elevated serum prostate-specific antigen (PSA) levels in body fluids may indicate prostate cancer (PCa), but it is noted that the clinical performance is rather poor. Specificity and sensitivity values of 20 and 94% at a cutoff value of 4.1 ng/mL, respectively, result in overdiagnosis and unnecessary interventions. Previous exploratory studies have indicated that the glycosylation of PSA potentially leads to improved PCa diagnosis based on qualitative analyses. However, the applied methods are not suited for a quantitative evaluation or implementation in a medical laboratory. Therefore, in this proof-of-principle study, we have evaluated the use of hydrophilic interaction liquid chromatography (HILIC) in combination with targeted quantitative mass spectrometry for the sialic acid linkage-specific analysis of PSA glyco-proteoforms based on either trypsin or ArgC peptides. The efficiency of PSA proteolysis was optimized as well as the glycopeptide separation conditions (buffer type, strength, and pH). The HILIC-based analysis of PSA glyco-proteoforms presented here has the potential for the clinical validation of patient cohorts. The method shows the feasibility of the use of a HILIC stationary phase for the separation of isomeric glycopeptides to detect specific glyco-proteoforms. This is the first step toward the development and evaluation of PSA glyco-proteoforms for use in a clinical chemistry setting aiming for improved PCa diagnosis or screening.

Monitoring glycation levels of a bispecific monoclonal antibody at subunit level by ultrahigh-resolution MALDI FT-ICR mass spectrometry.

Bispecific monoclonal antibodies (BsAbs) are engineered proteins with multiple functionalities and properties. The "bi-specificity" of these complex biopharmaceuticals is a key characteristic for the development of novel and more effective therapeutic strategies. The high structural complexity of BsAbs poses a challenge to the analytical methods needed for their characterization. Modifications of the BsAb structure, resulting from enzymatic and non-enzymatic processes, further complicate the analysis. An important example of the latter type of modification is glycation, which can occur in the manufacturing process, during storage in the formulation or in vivo after application of the drug. Glycation affects the structure, function, and stability of monoclonal antibodies, and consequently, a detailed analysis of glycation levels is required. Mass spectrometry (MS) plays a key role in the structural characterization of monoclonal antibodies and top-down, middle-up and middle-down MS approaches are increasingly used for the analysis of modifications. Here, we apply a novel middle-up strategy, based on IdeS digestion and matrix-assisted laser desorption ionization (MALDI) Fourier transform ion cyclotron resonance (FT-ICR) MS, to analyze all six different BsAb subunits in a single high-resolution mass spectrum, namely two light chains, two half fragment crystallizable regions and two Fd' regions, thus avoiding upfront chromatography. This method was used to monitor glycation changes during a 168 h forced-glycation experiment. In addition, hot spot glycation sites were localized using top-down and middle-down MALDI-in-source decay FT-ICR MS, which provided complementary information compared to standard bottom-up MS.

Serum N-glycome alterations in colorectal cancer associate with survival.

Proteins are routinely measured in clinical laboratories for diagnosis, prognosis and therapy monitoring. Nevertheless, both test improvements (performance) and innovations (biomarkers) are needed, and protein N-glycosylation offers a rich source of potential markers. Here, we have analyzed the total serum N-glycome in a matched case-control study (124 cases versus 124 controls) of colorectal cancer patients. The results were validated in an independent sample cohort (both 61 cases versus 61 controls) and further tested in post-operative samples of cured patients. Our results revealed significant differences between patients and controls, with increased size (antennae) and sialylation of the N-glycans in the colorectal cancer patient sera as compared to mainly di-antennary N-glycans in sera from controls. Furthermore, glycan alterations showed strong associations with cancer stage and survival: The five-year survival rate largely varied between patients with an altered serum N-glycome (46%) and an N-glycome similar to controls (87%). Importantly, the total serum N-glycome showed prognostic value beyond age and stage. This clinical glycomics study provides novel serum biomarker candidates and shows the potential of total serum N-glycans as a prognostic panel. Moreover, serum N-glycome changes reverted to a control-like profile after successful treatment as was demonstrated from pre- and post-operative samples.

Application of a Serum Protein Signature for Pancreatic Cancer to Separate Cases from Controls in a Pancreatic Surveillance Cohort.

BACKGROUND: Pancreatic cancer (PC) surveillance is currently offered to individuals with a genetic predisposition to PC, but routinely used radiological screening modalities are not entirely reliable in detecting early-stage PC or its precursor lesions. We recently identified a discriminating PC biomarker signature in a sporadic patient cohort. In this study, we investigated if protein profiling can accurately distinguish PC from non-PC in a pancreatic surveillance cohort of genetically predisposed individuals. METHODS: Serum samples of 66 individuals with a CDKN2A germline mutation who participated in the pancreatic surveillance program (5 cases, 61 controls) were obtained following a standardized protocol. After sample clean-up, peptide and protein profiles were obtained on an ultrahigh-resolution matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry platform. A discriminant score for each sample was calculated with a previously designed prediction rule, and the median discriminant scores of cases and controls were compared. Individuals with precursor lesions of PC (n = 4) and individuals with a recent diagnosis of melanoma (n = 4) were also separately considered. RESULTS: Cases had a higher median discriminant score than controls (0.26 vs 0.016; P = .001). The only individual with pathologically confirmed precursor lesions of PC could also be clearly distinguished from controls, and having a (recent) medical history of melanoma did not influence the protein signatures. CONCLUSIONS: Peptide and protein signatures are able to accurately distinguish PC cases from controls in a pancreatic surveillance setting. Mass spectrometry-based protein profiling therefore seems to be a promising candidate for implementation in the pancreatic surveillance program as an additional screening modality.

Developments in FTICR-MS and Its Potential for Body Fluid Signatures.

Fourier transform mass spectrometry (FTMS) is the method of choice for measurements that require ultra-high resolution. The establishment of Fourier transform ion cyclotron resonance (FTICR) MS, the availability of biomolecular ionization techniques and the introduction of the Orbitrap™ mass spectrometer have widened the number of FTMS-applications enormously. One recent example involves clinical proteomics using FTICR-MS to discover and validate protein biomarker signatures in body fluids such as serum or plasma. These biological samples are highly complex in terms of the type and number of components, their concentration range, and the structural identity of each species, and thus require extensive sample cleanup and chromatographic separation procedures. Clearly, such an elaborate and multi-step sample preparation process hampers high-throughput analysis of large clinical cohorts. A final MS read-out at ultra-high resolution enables the analysis of a more complex sample and can thus simplify upfront fractionations. To this end, FTICR-MS offers superior ultra-high resolving power with accurate and precise mass-to-charge ratio (m/z) measurement of a high number of peptides and small proteins (up to 20 kDa) at isotopic resolution over a wide mass range, and furthermore includes a wide variety of fragmentation strategies to characterize protein sequence and structure, including post-translational modifications (PTMs). In our laboratory, we have successfully applied FTICR "next-generation" peptide profiles with the purpose of cancer disease classifications. Here we will review a number of developments and innovations in FTICR-MS that have resulted in robust and routine procedures aiming for ultra-high resolution signatures of clinical samples, exemplified with state-of-the-art examples for serum and saliva.

Structure characterization of unexpected covalent O-sulfonation and ion-pairing on an extremely hydrophilic peptide with CE-MS and FT-ICR-MS.

In this study, we characterized unexpected side-products in a commercially synthesized peptide with the sequence RPRTRLHTHRNR. This so-called peptide D3 was selected by mirror phage display against low molecular weight amyloid-ß-peptide (Aß) associated with Alzheimer's disease. Capillary electrophoresis (CE) was the method of choice for structure analysis because the extreme hydrophilicity of the peptide did not allow reversed-phase liquid chromatography (RPLC) and hydrophilic interaction stationary phases (HILIC). CE-MS analysis, applying a strongly acidic background electrolyte and different statically adsorbed capillary coatings, provided fast and efficient analysis and revealed that D3 unexpectedly showed strong ion-pairing with sulfuric acid. Moreover, covalent O-sulfonation at one or two threonine residues was identified as a result of a side reaction during peptide synthesis, and deamidation was found at either the asparagine residue or at the C-terminus. In total, more than 10 different species with different m/z values were observed. Tandem-MS analysis with collision induced dissociation (CID) using a CE-quadrupole-time-of-flight (QTOF) setup predominantly resulted in sulfate losses and did not yield any further characteristic fragment ions at high collision energies. Therefore, direct infusion Fourier transform ion cyclotron resonance (FT-ICR) MS was employed to identify the covalent modification and discriminate O-sulfonation from possible O-phosphorylation by using an accurate mass analysis. Electron transfer dissociation (ETD) was used for the identification of the threonine O-sulfation sites. In this work, it is shown that the combination of CE-MS and FT-ICR-MS with ETD fragmentation was essential for the full characterization of this extremely basic peptide with labile modifications.

Serum peptide signatures for pancreatic cancer based on mass spectrometry: a comparison to CA19-9 levels and routine imaging techniques.

PURPOSE: The detection of pancreatic tumors lacks a sensitive and specific diagnostic tool. Mass spectrometry (MS)-based profiling of serum proteins is a promising approach for discovery of new clinical biomarkers or biomarker signatures. METHODS: Serum samples from pancreatic cancer (PC) patients and control individuals were collected and processed using a standardized protocol. Samples were divided in a calibration set (n = 49 PC and 110 controls) and a validation set (n = 39 PC and 75 controls). Peptide profiles were obtained using a combination of automated solid-phase extraction with reversed-phase C18 paramagnetic beads and matrix-assisted laser desorption ionization time-of-flight MS. RESULTS: Linear discriminant analysis with double cross-validation resulted in a discriminating peptide signature for PC in the calibration set with a sensitivity of 78 % and a specificity of 91 % [area under the curve (AUC) of 92 %]. Classification was validated with a sensitivity of 93 % and a specificity of 100 % (AUC of 98 %), and the results were compared with carbohydrate antigen 19-9 levels and currently available clinical imaging techniques. The ten most discriminating peptide peaks were identified as fragments of proteins involved in the clotting cascade, acute phase response and immunologic response. CONCLUSIONS: In this study, it is shown that MS-based serum peptide profiles can discriminate between PC and control samples. The approach has great potential for high-throughput analysis in surveillance programs and appears to be most promising for patients with an inherited risk for PC, who benefit from more frequent screening.

Urinary signatures of Renal Cell Carcinoma investigated by peptidomic approaches.

Renal Cell Carcinoma (RCC) is typically asymptomatic and surgery usually increases patient's lifespan only for early stage tumours. Moreover, solid renal masses cannot be confidently differentiated from RCC. Therefore, markers to distinguish malignant kidney tumours and for their detection are needed. Two different peptide signatures were obtained by a MALDI-TOF profiling approach based on urine pre-purification by C8 magnetic beads. One cluster of 12 signals could differentiate malignant tumours (n = 137) from benign renal masses and controls (n = 153) with sensitivity of 76% and specificity of 87% in the validation set. A second cluster of 12 signals distinguished clear cell RCC (n = 118) from controls (n = 137) with sensitivity and specificity values of 84% and 91%, respectively. Most of the peptide signals used in the two models were observed at higher abundance in patient urines and could be identified as fragments of proteins involved in tumour pathogenesis and progression. Among them: the Meprin 1α with a pro-angiogenic activity, the Probable G-protein coupled receptor 162, belonging to the GPCRs family and known to be associated with several key functions in cancer, the Osteopontin that strongly correlates to tumour stages and invasiveness, the Phosphorylase b kinase regulatory subunit alpha and the SeCreted and TransMembrane protein 1.

Metrological traceability in mass spectrometry-based targeted protein quantitation: a proof-of-principle study for serum apolipoproteins A-I and B100.

In this study, we have followed up on previous liquid chromatography (LC) multiple reaction monitoring (MRM) mass spectrometry (MS) approaches for measurement of apolipoprotein (apo) A-I and apo B100 in serum aiming for implementation of a multiplexed assay in a clinical chemistry laboratory with full metrological traceability. Signature peptides were selected and detected by dynamic MRM, and stable isotope labeled (SIL)-peptides were used as internal standards. Five apo A-I and four apo B100 peptides were measured in serum digests with linearity (R(2)>0.992) in the physiologically relevant concentration ranges. Linearity with regard to protein concentration was ascertained at five concentration levels (R(2)>0.926 and R(2)>0.965, for the apo A-I and apo B100 peptides, respectively). Three native value-assigned sera were used as external calibrators for further method verification. Imprecision values on sample preparation and LC-MS/MS acquisition were below the established minimal specifications for apo A-I and apo B100 (5.0% and 5.3%, respectively). Correlation of LC-MS/MS results with immunoturbidimetric assay results, for normo- and hypertriglyceridemic samples, showed R(2)>0.944 for apo A-I and R(2)>0.964 for apo B100. This LC-MS/MS method has potential for clinical application in normo- and dyslipidemic patients. BIOLOGICAL SIGNIFICANCE: Measurement of apo A-I and apo B100 may offer an alternative to high and low density lipoprotein cholesterol (HDL-c and LDL-c) methods for cardiovascular disease risk assessment in dyslipidemic patients [1]. An LC-MS/MS method for apo A-I and apo B100 has the advantage of antibody independent and specific detection of protein signature peptides. The introduction of an LC-MS/MS method for apo A-I and apo B100 can serve as an example for many existing and newly developed (multiplex) biomarker methods in quantitative clinical chemistry proteomics (qCCP). Such LC-MS/MS methods should meet basic clinical chemistry principles with regard to test evaluation [2]. Criteria for imprecision should be pre-defined, e.g., based on biological variation. The use of commutable and traceable serum-based calibrators will improve inter-laboratory reproducibility of LC-MS/MS methods and may contribute to a more rapid transition of biomarker discovery to clinical utility with benefit for the patient treatment and improvement of general health care.

Fibronectin is a serum biomarker for Duchenne muscular dystrophy.

PURPOSE: To identify and validate serum biomarkers for the progression of Duchenne muscular dystrophy (DMD) using a MS-based bottom-up pipeline. EXPERIMENTAL DESIGN: We used a bottom-up proteomics approach, including a protein concentration equalization step, different proteolytic digestions, and MS detection schemes, to identify candidate biomarkers in serum samples from control subjects and DMD patients. Fibronectin was chosen for follow-up based on the differences in peptide spectral counts and sequence coverage observed between the DMD and control groups. Subsequently, fibronectin levels were determined with ELISA in 68 DMD patients, 38 milder Becker muscular dystrophy patients, 33 patients with other neuromuscular disorders, and 15 age-matched adult and child controls. RESULTS: There was a significant increase in fibronectin levels in DMD patients compared to age-matched controls. Fibronectin levels in patients with Becker muscular dystrophy, Bethlem myopathy, or myasthenia gravis were comparable to control levels. Progressive elevation in fibronectin levels was observed in longitudinal samples from 22 DMD patients followed up for a period of 6 months up to 4 years. CONCLUSION AND CLINICAL RELEVANCE: This study suggests that serum fibronectin levels may constitute a promising biomarker to monitor disease progression in DMD patients.

Detection of pancreatic cancer using serum protein profiling.

BACKGROUND: Currently, no suitable biomarkers for the early detection of pancreatic cancer (PC) are available. Proteins present in the serum could reflect a state of the disease. In this study, these profiles as a diagnostic marker for PC were evaluated. METHODS: Serum samples were obtained from PC patients (n = 50 calibration set, n = 39 validation set) and healthy volunteers (n = 110 and n = 75 respectively) according to a uniform standardized collection and processing protocol. For peptide and protein isolation, automated solid-phase extraction (SPE) with Weak Cation Exchange (WCX) magnetic beads (MB) was performed using a 96-channel liquid handling platform. Protein profiles were obtained by mass spectrometry (MS) and evaluated by linear discriminant analysis with double cross-validation. RESULTS: A discriminating profile for PC has been identified, with a sensitivity of 78% and a specificity of 89% in the calibration set with an area under the curve (AUC) of 90%. These results were validated with a sensitivity of 74% and a specificity of 91% (AUC 90%). CONCLUSION: Serum profiles of healthy controls and PC can be discrimated between. Further research is warranted to evaluate specificity and whether this biosignature can be used for early detection in a high risk population.

Alterations of the serum peptidome in renal cell carcinoma discriminating benign and malignant kidney tumors.

Renal cell carcinoma (RCC) is typically asymptomatic and surgery usually increases patient's life only for early stage tumors. However, some cystic and solid renal lesions cannot be confidently differentiated from clear-cell-RCC. Therefore possible markers for early detection and to distinguish malignant kidney tumors are needed. To this aim, we applied MALDI-TOF and LC-MS/MS analysis to RPC18 MB purified serum of ccRCC, non-ccRCC patients and controls. A cluster of five signals differentiate malignant tumors from benign renal masses and healthy subjects. Moreover, a combination of six ions showed the highest specificity and sensitivity to distinguish ccRCC from controls. Healthy subjects were also differentiated from non-ccRCC by three features. Peptide ratios obtained by MALDI-TOF were compared with those from label-free LC-ESI and no statistical difference was found (p>0.05). ESI-results were linked with MALDI profiles by both TOF/TOF sequencing and MALDI FT-ICR accurate mass measurements. About 200 unique endogenous peptides, originating from 32 proteins, were identified. Among them, SDPR and ZYX were found down-expressed, while SRGN and TMSL3 were up-expressed. In conclusion, our results suggest the possibility to discriminate malignant kidney tumors based on a cluster of serum peptides. Moreover, label-free approach may represent a valid method to verify results obtained by MALDI-TOF. This article is part of a Special Issue entitled: Integrated omics.