Serum peptidome profiling revealed platelet factor 4 as a potential discriminating Peptide associated with pancreatic cancer

Cellular Components Contributing to the Development of Venous Thrombosis in Patients with Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive type of cancer and has a poor prognosis. Patients with PDAC are at high risk of developing thromboembolic events, which is a leading cause of morbidity and mortality following cancer progression. Plasma-derived coagulation is the most studied process in cancer-associated thrombosis. Other blood components, such as platelets, red blood cells, and white blood cells, have been gaining less attention. This narrative review addresses the literature on the role of cellular components in the development of venous thromboembolism (VTE) in patients with PDAC. Blood cells seem to play an important role in the development of VTE. Altered blood cell counts, i.e., leukocytosis, thrombocytosis, and anemia, have been found to associate with VTE risk. Tumor-related activation of leukocytes leads to the release of tissue factor-expressing microvesicles and the formation of neutrophil extracellular traps, initiating coagulation and forming a scaffold for thrombi. Tissue factor-expressing microvesicles are also thought to be released by PDAC cells. PDAC cells have been shown to stimulate platelet activation and aggregation, proposedly via the secretion of podoplanin and mucins. Hypofibrinolysis, partially explained by increased plasminogen activator inhibitor-1 activity, is observed in PDAC. In short, PDAC-associated hypercoagulability is a complex and multifactorial process. A better understanding of cellular contributions to hypercoagulability might lead to the improvement of diagnostic tests to identify PDAC patients at highest risk of VTE.

Aerobic exercise training mitigates tumor growth and cancer-induced splenomegaly through modulation of non-platelet platelet factor 4 expression

Exercise training reduces the incidence of several cancers, but the mechanisms underlying these effects are not fully understood. Exercise training can affect the spleen function, which controls the hematopoiesis and immune response. Analyzing different cancer models, we identified that 4T1, LLC, and CT26 tumor-bearing mice displayed enlarged spleen (splenomegaly), and exercise training reduced spleen mass toward control levels in two of these models (LLC and CT26). Exercise training also slowed tumor growth in melanoma B16F10, colon tumor 26 (CT26), and Lewis lung carcinoma (LLC) tumor-bearing mice, with minor effects in mammary carcinoma 4T1, MDA-MB-231, and MMTV-PyMT mice. In silico analyses using transcriptome profiles derived from these models revealed that platelet factor 4 (Pf4) is one of the main upregulated genes associated with splenomegaly during cancer progression. To understand whether exercise training would modulate the expression of these genes in the tumor and spleen, we investigated particularly the CT26 model, which displayed splenomegaly and had a clear response to the exercise training effects. RT-qPCR analysis confirmed that trained CT26 tumor-bearing mice had decreased Pf4 mRNA levels in both the tumor and spleen when compared to untrained CT26 tumor-bearing mice. Furthermore, exercise training specifically decreased Pf4 mRNA levels in the CT26 tumor cells. Aspirin treatment did not change tumor growth, splenomegaly, and tumor Pf4 mRNA levels, confirming that exercise decreased non-platelet Pf4 mRNA levels. Finally, tumor Pf4 mRNA levels are deregulated in The Cancer Genome Atlas Program (TCGA) samples and predict survival in multiple cancer types. This highlights the potential therapeutic value of exercise as a complementary approach to cancer treatment and underscores the importance of understanding the exercise-induced transcriptional changes in the spleen for the development of novel cancer therapies.

A niche-mimicking polymer hydrogel-based approach to identify molecular targets for tackling human pancreatic cancer stem cells

BACKGROUND

Pancreatic adenocarcinoma (PAAD) is one of the most fatal human cancers, but effective therapies remain to be established. Cancer stem cells (CSCs) are highly resistant to anti-cancer drugs and a deeper understanding of their microenvironmental niche has been considered important to provide understanding and solutions to cancer eradication. However, as the CSC niche is composed of a wide variety of biological and physicochemical factors, the development of multidisciplinary tools that recapitulate their complex features is indispensable. Synthetic polymers have been studied as attractive biomaterials due to their tunable biofunctionalities, while hydrogelation technique further renders upon them a diversity of physical properties, making them an attractive tool for analysis of the CSC niche.

METHODS

To develop innovative materials that recapitulate the CSC niche in pancreatic cancers, we performed polymer microarray analysis to identify niche-mimicking scaffolds that preferentially supported the growth of CSCs. The niche-mimicking activity of the identified polymers was further optimized by polyethylene glycol (PEG)-based hydrogelation. To reveal the biological mechanisms behind the activity of the optimized hydrogels towards CSCs, proteins binding onto the hydrogel were analyzed by liquid chromatography with tandem mass spectrometry (LC-MS/MS), and the potential therapeutic targets were validated by looking at gene expression and patients' outcome in the TCGA database.

RESULTS

PA531, a heteropolymer composed of 2-methoxyethyl methacrylate (MEMA) and 2-(diethylamino)ethyl methacrylate (DEAEMA) (5.5:4.5) that specifically supports the growth and maintenance of CSCs was identified by polymer microarray screening using the human PAAD cell line KLM1. The polymer PA531 was converted into five hydrogels (PA531-HG1 to HG5) and developed to give an optimized scaffold with the highest CSC niche-mimicking activities. From this polymer that recapitulated CSC binding and control, the proteins fetuin-B and angiotensinogen were identified as candidate target molecules with clinical significance due to the correlation between gene expression levels and prognosis in PAAD patients and the proteins associated with the niche-mimicking polymer.

CONCLUSION

This study screened for biofunctional polymers suitable for recapitulation of the pancreatic CSC niche and one hydrogel with high niche-mimicking abilities was successfully fabricated. Two soluble factors with clinical significance were identified as potential candidates for biomarkers and therapeutic targets in pancreatic cancers. Such a biomaterial-based approach could be a new platform in drug discovery and therapy development against CSCs, via targeting of their niche.

Discrimination of the chemotherapy resistance status of human leukemia and glioblastoma cell lines by MALDI-TOF-MS profiling

Chemotherapy mistreatment is partially due to a lack of rapid and reliable tools to discriminate between sensitive and resistant phenotypes. In many cases, the resistance mechanism is not fully understood, contributing to the diagnostic tools' absence. This work aims to determine the capacity of MALDI-TOF-MS profiling to discriminate between chemotherapy-resistant and sensitive phenotypes in leukemia and glioblastoma cells. A multivariate analysis of two therapy-resistant leukemia cell lines (Ki562 and Kv562) and two TMZ-resistant glioblastoma cell lines (U251-R and LN229-R) and their sensitive counterparts was performed. In this work, we first show MALDI-TOF-MS patterns analysis ability to differentiate these cancer cell lines by their chemotherapy-resistant status. We present a rapid and inexpensive tool that would guide and complement the therapeutic decision.

Case Report: Vaccine-Induced Immune Thrombotic Thrombocytopenia in a Pancreatic Cancer Patient After Vaccination With Messenger RNA-1273

Vaccination plays an important role during the COVID-19 pandemic. Vaccine-induced thrombotic thrombocytopenia (VITT) is a major adverse effect that could be lethal. For cancer patients, cancer-related thromboembolism is another lethal complication. When cancer patients receive their COVID-19 vaccines, the following thromboembolic events will be more complicated. We presented a case recently diagnosed with pancreatic cancer, who had received the mRNA-1273 (Moderna) vaccination 12 days prior. Ischemic stroke and VITT were also diagnosed. We aggressively treated the patient with steroids, immunoglobulin, and plasma exchange. The titer of anti-platelet factor four and d-dimer level decreased, but the patient ultimately died. The complicated condition of VITT superimposed cancer-related thromboembolism was considered. To our knowledge, only one case of mRNA-1273 related VITT was reported, and this case study was the first to report a cancer patient who was diagnosed with VITT after mRNA-1273 vaccination. Therefore, when the need for vaccination among cancer patients increased under the current COVID-19 pandemic, the possible risk of VITT for cancer patients should be carefully managed. Further studies of the risk evaluation of the COVID-19 vaccine in cancer patients might be required in the future.

Platelet Factor 4 as a Novel Exosome Marker in MALDI-MS Analysis of Exosomes from Human Serum

Exosomes are nanosized vesicles commonly found in biological fluids as a result of a secretion process involving endosomes and multivesicular bodies. The isolation and analysis of exosomes can be useful for noninvasive clinical diagnosis of a variety of human diseases. We investigated the utility of analyzing exosomal proteins, using matrix-assisted laser desorption/ionization combined with Fourier-transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS), as a means of determining the presence of exosomes. MALDI-FTICR-MS analyses of exosomes enriched from human serum via centrifugation in a mass range of m/z 1000-20 000 yielded a distinctive protein around m/z 7766. The high mass accuracy and resolution of MALDI-FTICR-MS allowed for reliable comparisons against a protein database, through which the protein was identified as platelet factor 4 (PLF4), whose singly charged protein peak has an elemental composition of C₃₄₁H₅₇₇N₉₆O₁₀₁S₄⁺, with a theoretical most abundant isotopic peak at m/z 7765.194 and a theoretical average peak at m/z 7766. The MALDI-TOF MS analysis of exosomes from the serum of 27 patients with different states of liver diseases provided the most abundant PLF4 peak for each mass spectrum, along with several additional minor peaks. In conclusion, MALDI-MS is suitable as an alternative exosome detection method, serving as a valuable confirmation tool, greatly decreasing the time and workload associated with exosome identification.

Hypertensive disorders of pregnancy: Strategy to develop clinical peptide biomarkers for more accurate evaluation of the pathophysiological status of this syndrome

Hypertensive disorders of pregnancy (HDP) is the most common and widely known as serious complication of pregnancy. As this syndrome is a major leading cause of maternal, fetal, and neonatal morbidity/mortality worldwide, many studies have sought to identify candidate molecules as potential disease biomarkers (DBMs) for use in clinical examinations. Accumulating evidence over the past 2 decades that the many proteolytic peptides appear in human humoral fluids, including peripheral blood, in association with an individual's health condition. This review provides the potential utility of peptidomic analysis for monitoring for pathophysiological status in HDP, and presents an overview of current status of peptide quantification technology. Especially, the technical limitations of the methods used for DBM discovery in the blood are discussed.

Soluble stroma-related biomarkers of pancreatic cancer

The clinical management of pancreatic ductal adenocarcinoma (PDAC) is hampered by the lack of reliable biomarkers. This study investigated the value of soluble stroma‐related molecules as PDAC biomarkers. In the first exploratory phase, 12 out of 38 molecules were associated with PDAC in a cohort of 25 PDAC patients and 16 healthy subjects. A second confirmatory phase on an independent cohort of 131 PDAC patients, 30 chronic pancreatitis patients, and 131 healthy subjects confirmed the PDAC association for MMP7, CCN2, IGFBP2, TSP2, sICAM1, TIMP1, and PLG. Multivariable logistic regression model identified biomarker panels discriminating respectively PDAC versus healthy subjects (MMP7 + CA19.9, AUC = 0.99, 99% CI = 0.98–1.00) (CCN2 + CA19.9, AUC = 0.96, 99% CI = 0.92–0.99) and PDAC versus chronic pancreatitis (CCN2 + PLG+FN+Col4 + CA19.9, AUC = 0.94, 99% CI = 0.88–0.99). Five molecules were associated with PanIN development in two GEM models of PDAC (PdxCre/LSL‐Kras^G12D and PdxCre/LSL‐Kras^G12D/+/LSL‐Trp53^R172H/+), suggesting their potential for detecting early disease. These markers were also elevated in patient‐derived orthotopic PDAC xenografts and associated with response to chemotherapy. The identified stroma‐related soluble biomarkers represent potential tools for PDAC diagnosis and for monitoring treatment response of PDAC patients.

Variation of fetuin-A in maternal and fetal serum during human parturition

BACKGROUND

parturition involves multiple signalling pathways and most advances in research underline the importance of fetal development and maturation in the timing of labour, especially the fetal pituitary-adrenal axis. But, there is currently no consensual hypothesis on all the physiological processes responsible for human parturition.

METHODS

sixty low-risk pregnant women were enrolled in a prospective cohort. Maternal blood was sampled regularly during consultations each week in last trimester, at delivery and at postnatal consultation. Cord blood was collected at delivery. We used proteomic analysis to identify maternal blood biomarkers of potential interest, focusing on serum proteins from 39 W G in pregnancies to delivery and postpartum.

RESULTS

among 56 peaks we identified variation in the N-terminal part of fetuin-A in maternal serum. Fetuin-A is a natural antagonist of TGF-beta and is able to bind calcium. We found a significant decrease in maternal serum fetuin-A in the days preceding delivery, independently of the mode of delivery. Also, there does not appear to be significant influence of the different fetal parameters (sex, Z-score) on maternal serum variations at delivery.

CONCLUSION

fetuin-A is described by the literature as a potential biomarker for organ dysfunction and metabolic syndrome disorders. The protein mineral homeostasis would be an interesting pathway to explore during pregnancy and particularly parturition.

Contribution of the plasma and lymph Degradome and Peptidome to the MHC Ligandome

Every biological fluid, blood, interstitial fluid and lymph, urine, saliva, lacrimal fluid, nipple aspirate, and spinal fluid, contains a peptidome-degradome derived from the cellular secretome along with byproducts of the metabolic/catabolic activities of each parenchymal organ. Clement et al. (J Proteomics 78:172-187, 2013), Clement et al. (J Biol Chem 291:5576-5595, 2016), Clement et al. (PLoS One 5:e9863, 2010), Clement et al. (Trends Immunol 32:6-11, 2011), Clement et al. (Front Immunol 4:424, 2013), Geho et al. (Curr Opin Chem Biol 10, 50-55, 2006), Interewicz et al. (Lymphology 37:65‑72, 2004), Leak et al. (Proteomics 4:753‑765, 2004), Popova et al. (PLoS One 9:e110873, 2014), Zhou et al. (Electrophoresis 25:1289‑1298, 2004), D'Alessandro et al. (Shock 42:509‑517, 2014), Dzieciatkowska et al. (Shock 42:485‑498, 2014), Dzieciatkowska et al. (Shock 35:331‑338, 2011), Jordan et al. (J Surg Res 143:130‑135, 2007), Peltz et al. (Surgery 146:347‑357, 2009), Zurawel et al. (Clin Proteomics 8:1, 2011), Ling et al. (Clin Proteomics 6:175‑193, 2010), Sturm et al. (Nat Commun 4:1616, 2013). Over the last decade, qualitative and quantitative analysis of the biological fluids peptidome and degradome have provided a dynamic measurement of tissue homeostasis as well as the tissue response to pathological damage. Proteomic profiling has mapped several of the proteases and resulting degradation by-products derived from cell cycle progression, organ/tissue remodeling and cellular growth, physiological apoptosis, hemostasis, and angiogenesis. Currently, a growing interest lies in the degradome observed during pathological conditions such as cancer, autoimmune diseases, and immune responses to pathogens as a way to exploit biological fluids as liquid biopsies for biomarker discovery Dzieciatkowska et al. (Shock 42:485-498, 2014), Dzieciatkowska et al. (Shock 35:331-338, 2011), Ling et al. (Clin Proteomics 6:175-193, 2010), Ugalde et al. (Methods Mol Biol 622:3-29, 2010), Quesada et al. (Nucleic Acids Res 37:D239‑243, 2009), Cal et al. (Front Biosci 12, 4661-4669, 2007), Shen et al. (PLoS One 5:e13133, 2010a), Antwi et al. (Mol Immunol 46:2931-2937, 2009a), Antwi et al. (J Proteome Res 8:4722‑4731, 2009b), Bedin et al. (J Cell Physiol 231, 915‑925, 2016), Bery et al. (Clin Proteomics 11:13, 2014), Bhalla et al. (Sci Rep 7:1511, 2017), Fan et al. (Diagn Pathol 7:45, 2012a), Fang et al. (Shock 34:291‑298, 2010), Fiedler et al. (Clin Cancer Res 15:3812‑3819, 2009), Fredolini et al. (AAPS J 12:504‑518, 2010), Greening et al. (Enzymes 42:27‑64, 2017), He et al. (PLoS One 8:e63724, 2013), Huang et al. (Int J Gynecol Cancer 28:355‑362, 2018), Hashiguchi et al. (Med Hypotheses 73:760‑763, 2009), Liotta and Petricoin (J Clin Invest 116:26‑30, 2006), Petricoin et al. (Nat Rev Cancer 6:961‑967, 2006), Shen et al. (J Proteome Res 9:2339‑2346, 2010a), Shen et al. (J Proteome Res 5:3154‑3160, 2006), Smith (Clin Proteomics 11:23, 2014), Wang et al. (Oncotarget 8:59376‑59386, 2017), Yang et al. (Clin Exp Med 12:79‑87, 2012a), Yang et al. (J Clin Lab Anal 26:148‑154, 2012b), Yang et al. (Anat Rec (Hoboken) 293:2027‑2033, 2010), Zapico-Muniz et al. (Pancreas 39:1293‑1298, 2010), Villanueva et al. (Mol Cell Proteomics 5:1840‑1852, 2006), Robbins et al. (J Clin Oncol 23:4835‑4837, 2005), Klupczynska et al. (Int J Mol Sci 17:410, 2016). In this review, we focus on the current knowledge of the degradome/peptidome observed in two main biological fluids (plasma and lymph) during physiological and pathological conditions and its importance for immune surveillance.

Mean platelet volume predicts survival in pancreatic cancer patients with synchronous liver metastases

Most pancreatic cancer (PC) patients manifest multiple liver metastases at the time of diagnosis. Activated platelets play a key role in tumor growth and tumor metastases. Mean platelet volume (MPV) is a platelet index and is altered in patients with malignancies. This study aimed to evaluate whether MPV can effectively predict death in PC patients with synchronous liver metastases. The clinical data of 411 PC patients with synchronous liver metastases between January 1, 2006 and December 31, 2013 were retrospectively analyzed. Subjects were divided into two groups by MPV levels. Clinicopathological data were collected retrospectively and relationships between MPV levels and clinical parameters were evaluated. Survival analysis was performed. Increased MPV was not significantly correlated with tumor location, tumor size, and CA19.9. The Kaplan-Meier analysis showed that the overall survival of patients with MPV > 8.7 fL was significantly shorter than that of those with MPV ≤ 8.7 fL (log-rank p < 0.001). Multivariable Cox proportional hazards model identified MPV as an independent poor prognostic factor for overall survival. In conclusion, elevated MPV is associated with worse survival outcome in PC patients with synchronous liver metastases. Further studies are warranted.

Metabolic biomarker signature to differentiate pancreatic ductal adenocarcinoma from chronic pancreatitis

OBJECTIVE

Current non-invasive diagnostic tests can distinguish between pancreatic cancer (pancreatic ductal adenocarcinoma (PDAC)) and chronic pancreatitis (CP) in only about two thirds of patients. We have searched for blood-derived metabolite biomarkers for this diagnostic purpose.

DESIGN

For a case-control study in three tertiary referral centres, 914 subjects were prospectively recruited with PDAC (n=271), CP (n=282), liver cirrhosis (n=100) or healthy as well as non-pancreatic disease controls (n=261) in three consecutive studies. Metabolomic profiles of plasma and serum samples were generated from 477 metabolites identified by gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry.

RESULTS

A biomarker signature (nine metabolites and additionally CA19-9) was identified for the differential diagnosis between PDAC and CP. The biomarker signature distinguished PDAC from CP in the training set with an area under the curve (AUC) of 0.96 (95% CI 0.93-0.98). The biomarker signature cut-off of 0.384 at 85% fixed specificity showed a sensitivity of 94.9% (95% CI 87.0%-97.0%). In the test set, an AUC of 0.94 (95% CI 0.91-0.97) and, using the same cut-off, a sensitivity of 89.9% (95% CI 81.0%-95.5%) and a specificity of 91.3% (95% CI 82.8%-96.4%) were achieved, successfully validating the biomarker signature.

CONCLUSIONS

In patients with CP with an increased risk for pancreatic cancer (cumulative incidence 1.95%), the performance of this biomarker signature results in a negative predictive value of 99.9% (95% CI 99.7%-99.9%) (training set) and 99.8% (95% CI 99.6%-99.9%) (test set). In one third of our patients, the clinical use of this biomarker signature would have improved diagnosis and treatment stratification in comparison to CA19-9.

Platelet chemokines in health and disease

In recent years, it has become clear that platelets and platelet-derived chemokines, beyond their role in thrombosis and haemostasis, are important mediators affecting a broad spectrum of (patho)physiological conditions. These biologically active proteins are released from α-granules upon platelet activation, most probably even during physiological conditions. In this review, we give a concise overview and an update on the current understanding of platelet-derived chemokines in a context of health and disease.

Note: The review process for this manuscript was fully handled by G. Y. H. Lip, Editor in Chief.

Sparse Proteomics Analysis - a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data

BACKGROUND

High-throughput proteomics techniques, such as mass spectrometry (MS)-based approaches, produce very high-dimensional data-sets. In a clinical setting one is often interested in how mass spectra differ between patients of different classes, for example spectra from healthy patients vs. spectra from patients having a particular disease. Machine learning algorithms are needed to (a) identify these discriminating features and (b) classify unknown spectra based on this feature set. Since the acquired data is usually noisy, the algorithms should be robust against noise and outliers, while the identified feature set should be as small as possible.

RESULTS

We present a new algorithm, Sparse Proteomics Analysis (SPA), based on the theory of compressed sensing that allows us to identify a minimal discriminating set of features from mass spectrometry data-sets. We show (1) how our method performs on artificial and real-world data-sets, (2) that its performance is competitive with standard (and widely used) algorithms for analyzing proteomics data, and (3) that it is robust against random and systematic noise. We further demonstrate the applicability of our algorithm to two previously published clinical data-sets.

Evaluation of serum phosphopeptides as potential biomarkers of gastric cancer

A serum phosphopeptide (DpSGEGDFLAEGGGVR) was demonstrated to be a potential biomarker for gastric cancer diagnosis, particularly for early stage cases.

CXCL4 mediates tumor regrowth after chemotherapy by suppression of antitumor immunity

The recurrence of colorectal cancer after chemotherapy is the leading cause of its high mortality. We propose that elucidating the mechanisms of tumor regrowth after chemotherapy in tumor-bearing mice may provide new insights into tumor relapse in cancer patients. We firstly report the identification of a chemokine, CXCL4, that plays an important role in the molecular mechanism of cancer regrowth after chemotherapy. A syngenic transplantation tumor model was established with murine colon cancer CT26 cells and treated with 5-FU. Genome-wide gene expression analysis determined that CXCL4 was transiently upregulated in the tumor model. Systemic overexpression of CXCL4 accelerated cancer growth in vivo, but not in vitro. Conversely, the anti-CXCL4 monoclonal antibody (CXCL4-mab) retarded tumor-regrowth after 5-FU treatment in immune-competent mice, but not nude mice. The CXCL4-mab treatment increased the local expression levels of IFN-γ and Gran-b genes in the tumor-bed, and elevated the function of CTLs against CT26 cells. Thus, the colon cancer cells in responding to the cytotoxic stress of 5-FU produce a high level of CXCL4, which suppresses antitumor immunity to confer the residual cancer cells an advantage for regrowth after chemotherapy. Our findings provide a novel target for developing therapeutics aiming to increase antitumor immunity after chemotherapy.

The Role of Cytokine PF4 in the Antiviral Immune Response of Shrimp

During viral infection in vertebrates, cytokines play important roles in the host defense against the virus. However, the function of cytokines in invertebrates has not been well characterized. In this study, shrimp cytokines involved in viral infection were screened using a cytokine antibody microarray. The results showed that three cytokines, the Fas receptor (Fas), platelet factor 4 (PF4) and interleukin-22 (IL-22), were significantly upregulated in the white spot syndrome virus (WSSV)-challenged shrimp, suggesting that these cytokines played positive regulatory roles in the immune response of shrimp against the virus. Further experiments revealed that PF4 had positive effects on the antiviral immunity of shrimp by enhancing the shrimp phagocytic activity and inhibiting the apoptotic activity of virus-infected hemocytes. Therefore, our study presented a novel mechanism of cytokines in the innate immunity of invertebrates.

Challenges in biomarker discovery with MALDI-TOF MS

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

Rapid Detection of Vancomycin-Intermediate Staphylococcus aureus by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

Vancomycin is the standard of care for the treatment of invasive methicillin-resistantStaphylococcus aureus(MRSA) infections. Infections with vancomycin-nonsusceptible MRSA, including vancomycin-intermediateS. aureus(VISA) and heterogeneous VISA (hVISA), are clinically challenging and are associated with poor patient outcomes. The identification of VISA in the clinical laboratory depends on standard susceptibility testing, which takes at least 24 h to complete after isolate subculture, whereas hVISA is not routinely detected in clinical labs. We therefore sought to determine whether VISA and hVISA can be differentiated from vancomycin-susceptibleS. aureus(VSSA) using the spectra produced by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Strains of MRSA were characterized for vancomycin susceptibility phenotype by broth microdilution and modified population analysis. We tested 21 VISA, 21 hVISA, and 38 VSSA isolates by MALDI-TOF MS. Susceptibility phenotypes were separated by using a support vector machine (SVM) machine learning algorithm. The resulting model was validated by leave-one-out cross validation. Models were developed and validated by using spectral profiles generated under various subculture conditions, as well as with and without hVISA strains. Using SVM, we correctly identified 100% of the VISA and 97% of the VSSA isolates with an overall classification accuracy of 98%. Addition of hVISA to the model resulted in 76% hVISA identification, 100% VISA identification, and 89% VSSA identification, for an overall classification accuracy of 89%. We conclude that VISA/hVISA and VSSA isolates are separable by MALDI-TOF MS with SVM analysis.

Pancreatic preneoplastic lesions plasma signatures and biomarkers based on proteome profiling of mouse models

Background:

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with a mortality that is almost identical to incidence. Because early detected PDAC is potentially curable, blood-based biomarkers that could detect currently developing neoplasia would improve patient survival and management. PDAC develops from pancreatic intraepithelial neoplasia (PanIN) lesions, graded from low grade (PanIN1) to high grade (PanIN3). We made the hypothesis that specific proteomic signatures from each precancerous stage exist and are detectable in plasma.

Methods:

We explored the peptide profiles of microdissected PanIN cells and of plasma samples corresponding to the different PanIN grade from genetically engineered mouse models of PDAC using capillary electrophoresis coupled to mass spectrometry (CE-MS) and Chip-MS/MS.

Results:

We successfully characterised differential peptides profiles from PanIN microdissected cells. We found that plasma from tumor-bearing mice and age-matched controls exhibit discriminative peptide signatures. We also determined plasma peptide signatures corresponding to low- and high-grade precancerous step present in the mice pancreas using the two mass spectrometry technologies. Importantly, we identified biomarkers specific of PanIN3.

Conclusions:

We demonstrate that benign and advanced PanIN lesions display distinct plasma peptide patterns. This strongly supports the perspectives of developing a non-invasive screening test for prediction and early detection of PDAC.

Differential protein expression and peak selection in mass spectrometry data by binary discriminant analysis

MOTIVATION

Proteomic mass spectrometry analysis is becoming routine in clinical diagnostics, for example to monitor cancer biomarkers using blood samples. However, differential proteomics and identification of peaks relevant for class separation remains challenging.

RESULTS

Here, we introduce a simple yet effective approach for identifying differentially expressed proteins using binary discriminant analysis. This approach works by data-adaptive thresholding of protein expression values and subsequent ranking of the dichotomized features using a relative entropy measure. Our framework may be viewed as a generalization of the 'peak probability contrast' approach of Tibshirani et al. (2004) and can be applied both in the two-group and the multi-group setting. Our approach is computationally inexpensive and shows in the analysis of a large-scale drug discovery test dataset equivalent prediction accuracy as a random forest. Furthermore, we were able to identify in the analysis of mass spectrometry data from a pancreas cancer study biological relevant and statistically predictive marker peaks unrecognized in the original study.

AVAILABILITY AND IMPLEMENTATION

The methodology for binary discriminant analysis is implemented in the R package binda, which is freely available under the GNU General Public License (version 3 or later) from CRAN at URL http://cran.r-project.org/web/packages/binda/. R scripts reproducing all described analyzes are available from the web page http://strimmerlab.org/software/binda/.

CONTACT

k.strimmer@imperial.ac.uk.

Potential for proteomic approaches in determining efficacy biomarkers following administration of fish oils rich in omega-3 fatty acids: application in pancreatic cancers

Pancreatic cancer is a disease with a significantly poor prognosis. Despite modern advances in other medical, surgical, and oncologic therapy, the outcome from pancreatic cancer has improved little over the last 40 years. To improve the management of this difficult disease, trials investigating the use of dietary and parenteral fish oils rich in omega-3 (ω-3) fatty acids, exhibiting proven anti-inflammatory and anticarcinogenic properties, have revealed favorable results in pancreatic cancers. Proteomics is the large-scale study of proteins that attempts to characterize the complete set of proteins encoded by the genome of an organism and that, with the use of sensitive mass spectrometric-based techniques, has allowed high-throughput analysis of the proteome to aid identification of putative biomarkers pertinent to given disease states. These biomarkers provide useful insight into potentially discovering new markers for early detection or elucidating the efficacy of treatment on pancreatic cancers. Here, our review identifies potential proteomic-based biomarkers in pancreatic cancer relating to apoptosis, cell proliferation, angiogenesis, and metabolic regulation in clinical studies. We also reviewed proteomic biomarkers from the administration of ω-3 fatty acids that act on similar anticarcinogenic pathways as above and reflect that proteomic studies on the effect of ω-3 fatty acids in pancreatic cancer will yield favorable results.

Plasma metabolite biomarkers for the detection of pancreatic cancer

Patients with pancreatic cancer (PC) are usually diagnosed at late stages, when the disease is nearly incurable. Sensitive and specific markers are critical for supporting diagnostic and therapeutic strategies. The aim of this study was to use a metabonomics approach to identify potential plasma biomarkers that can be further developed for early detection of PC. In this study, plasma metabolites of newly diagnosed PC patients (n = 100) and age- and gender-matched controls (n = 100) from Connecticut (CT), USA, and the same number of cases and controls from Shanghai (SH), China, were profiled using combined gas and liquid chromatography mass spectrometry. The metabolites consistently expressed in both CT and SH samples were used to identify potential markers, and the diagnostic performance of the candidate markers was tested in two sample sets. A diagnostic model was constructed using a panel of five metabolites including glutamate, choline, 1,5-anhydro-d-glucitol, betaine, and methylguanidine, which robustly distinguished PC patients in CT from controls with high sensitivity (97.7%) and specificity (83.1%) (area under the receiver operating characteristic curve [AUC] = 0.943, 95% confidence interval [CI] = 0.908–0.977). This panel of metabolites was then tested with the SH data set, yielding satisfactory accuracy (AUC = 0.835; 95% CI = 0.777–0.893), with a sensitivity of 77.4% and specificity of 75.8%. This model achieved a sensitivity of 84.8% in the PC patients at stages 0, 1, and 2 in CT and 77.4% in the PC patients at stages 1 and 2 in SH. Plasma metabolic signatures show promise as biomarkers for early detection of PC.

A PSA-guided approach for a better diagnosis of prostatic adenocarcinoma based on MALDI profiling and peptide identification

BACKGROUND

Prostate cancer (PCa) is the second cause of mortality in men worldwide. The prostate-specific antigen (PSA) test is routinely adopted in diagnosis; nevertheless more reliable biomarkers are continuously under investigation by monitoring the release of molecules into the bloodstream. The serum protein profiles appear to provide cancer-specific fingerprints that help to discriminate patients (especially with low PSA level) from controls, improving the performance of existing clinical tests.

METHODS

Samples from healthy controls and PCa patients with low (≤4 ng/mL) and high PSA (>4 ng/mL) levels were analyzed by MALDI profiling, and by a multi fractionation approach coupled to ESI-MS for peaks identification.

RESULTS

MALDI profiling achieved to detect 10 and 14 changed peaks (p-value <0.05), respectively, in PCa patients with low and high PSA versus controls. In particular, a peak identified as C3f fragment, resulted overexpressed in low PSA PCa patients.

CONCLUSIONS

PSA test, coupled to MALDI profiling, is able to detect changes, specifically related to PCa, in low molecular weight protein range. Furthermore, for the first time in prostate cancer research, the identification and quantification of the small peptide C3f appears to be relevant for the detection of false negatives, providing an additive diagnostic power to PSA (p<0.01) and suggesting its use in clinical tests.

Liquid chromatography-mass spectrometry based serum peptidomic approach for renal clear cell carcinoma diagnosis

Serum peptidomic approach was applied to investigate the peptidomic signature and discover the clinical biomarkers and biomarker patterns for RCC patients. The holistic orthogonal partial least-squares-discriminant analysis (OPLS-DA) based on qualified profile data successfully classified RCC patients from healthy controls, showing 100% sensitivity and specificity. Following critical criteria, several peptides presenting significant differences in serum level were picked out. The unsupervised hierarchical cluster analysis on those peptides was performed, showing 100% sensitivity and 93.3% specificity for RCC diagnosis regarding the present samples. Besides, receiver-operating characteristic (ROC) analysis was applied on single peptide biomarkers, with four peptides showing excellent predictive power. Among them, IYQLNSKLV and AGISMRSGDSPQD are reported for the first time for cancer detection.

Serum peptide pattern that differentially diagnoses hepatitis B virus-related hepatocellular carcinoma from liver cirrhosis

BACKGROUND

Although alpha-fetoprotein (AFP) is a useful serologic marker of hepatocellular carcinoma (HCC), it is not sufficiently sensitive to differentiate HCC and liver cirrhosis (LC) caused by hepatitis B virus (HBV) infection.

AIMS

The aim is to discover novel noninvasive specific serum biomarkers for the differential diagnosis of HBV-related HCC and LC.

METHODS

With a highly optimized peptide extraction and matrix-assisted laser desorption/ionization time of flight/time of flight mass spectrometric approach, we investigated serum peptide profiles of 80 HCC and 67 LC patients. Three supervised machine learning methods were employed to construct classifiers. Receiver operator curves were plotted to evaluate the performance of classifiers.

RESULTS

With a support vector machine-based strategy, we picked nine peaks with m/z ratios of 819.49, 1076.14, 1341.72, 2551.44, 3156.44, 3812.88, 4184.26, 4465.92, and 4776.41 to construct the classifier. We proposed a novel method for distinguishing HCC from cirrhosis, based on a multilayer perceptron (MLP) method. We obtained a sensitivity of 90.0%, specificity of 79.4%, and overall accuracy of 85.1% on an independent test set. The combination of the MLP model and serum AFP level outperformed serum AFP marker alone in distinguishing HCC patients from LC patients. In this experience, sensitivity increased from 62.5% to 87.5%, and specificity increased from 79.4% to 88.2%.

CONCLUSIONS

Our results indicate that the MLP model is a novel and useful serum peptide pattern for distinguishing HCC and LC. The peptidome signature alone or together with serum AFP determination may be a more effective method for early diagnosis of HCC in patients with HBV-related LC.

A proteomics approach to the identification of plasma biomarkers for latent tuberculosis infection

A proteomic analysis was performed to screen the potential latent tuberculosis infection (LTBI) biomarkers. A training set of spectra was used to generate diagnostic models, and a blind testing set was used to determine the accuracy of the models. Candidate peptides were identified using nano-liquid chromatography-electrospray ionization–tandem mass spectrometry. Based on the training set results, 3 diagnostic models recognized LTBI subjects with good cross-validation accuracy. In the blind testing set, LTBI subjects could be identified with sensitivities and specificities of 85.20% to 88.90% and 85.7% to 100%, respectively. Additionally, 14 potential LTBI biomarkers were identified, and all proteins were identified for the first time through proteomics in the plasma of healthy, latently infected individuals. In all, proteomic pattern analyses can increase the accuracy of LTBI diagnosis, and the data presented here provide novel insights into potential mechanisms involved in LTBI.

Deciphering the ovarian cancer ascites fluid peptidome

Background

Conventional proteomic approaches have thus far been unable to identify novel serum biomarkers for ovarian cancer that are more sensitive and specific than the current clinically used marker, CA-125. Because endogenous peptides are smaller and may enter the circulation more easily than proteins, a focus on the low-molecular-weight region may reveal novel biomarkers with enhanced sensitivity and specificity. In this study, we deciphered the peptidome of ascites fluid from 3 ovarian cancer patients and 3 benign individuals (ascites fluid from patients with liver cirrhosis).

Results

Following ultrafiltration of the ascites fluids to remove larger proteins, each filtrate was subjected to solid phase extraction and fractionated using strong cation exchange chromatography. The resultant fractions were analyzed using an Orbitrap mass spectrometer. We identified over 2000 unique endogenous peptides derived from 259 proteins. We then catalogued over 777 peptides that were found only in ovarian cancer ascites. Our list of peptides found in ovarian cancer specimens includes fragments derived from the proteins vitronectin, transketolase and haptoglobin.

Conclusions

Peptidomics may uncover previously undiscovered disease-specific endogenous peptides that warrant further investigation as biomarkers for ovarian cancer.

Biomarkers screening between preoperative and postoperative patients in pancreatic cancer

OBJECTIVE

To investigate discriminating protein patterns and potential biomarkers in serum samples between pre/postoperative pancreatic cancer patients and healthy controls.

METHODS

23 serum samples from PC patients (12 preoperative and 11 postoperative) and 76 from healthy controls were analyzed using matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-TOF MS) technique combined with magnetic beads-based weak cation-exchange chromatography (MB-WCX). ClinProTools software selected several markers that made a distinction between pancreatic cancer patients and healthy controls.

RESULTS

49 m/z distinctive peaks were found among the three groups, of which 33 significant peaks with a P < 0.001 were detected. Two proteins could distinguish the preoperative pancreatic cancer patients from the healthy controls. About 15 proteins may be potential biomarkers in assessment of pancreatic cancer resection.

CONCLUSION

MB-MALDI-TOF-MS method could generate serum peptidome profiles of pancreatic cancer and provide a new approach to identify potential biomarkers for diagnosis and prognosis of this malignancy.

Identification of potential serum peptide biomarkers of biliary tract cancer using MALDI MS profiling

BACKGROUND

The aim of this discovery study was the identification of peptide serum biomarkers for detecting biliary tract cancer (BTC) using samples from healthy volunteers and benign cases of biliary disease as control groups. This work was based on the hypothesis that cancer-specific exopeptidases exist and that their activities in serum can generate cancer-predictive peptide fragments from circulating proteins during coagulation.

METHODS

This case control study used a semi-automated platform incorporating polypeptide extraction linked to matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) to profile 92 patient serum samples. Predictive models were generated to test a validation serum set from BTC cases and healthy volunteers.

RESULTS

Several peptide peaks were found that could significantly differentiate BTC patients from healthy controls and benign biliary disease. A predictive model resulted in a sensitivity of 100% and a specificity of 93.8% in detecting BTC in the validation set, whilst another model gave a sensitivity of 79.5% and a specificity of 83.9% in discriminating BTC from benign biliary disease samples in the training set. Discriminatory peaks were identified by tandem MS as fragments of abundant clotting proteins.

CONCLUSIONS

Serum MALDI MS peptide signatures can accurately discriminate patients with BTC from healthy volunteers.

Potential serum biomarkers for glioblastoma diagnostic assessed by proteomic approaches

BACKGROUND

The rapid progress of proteomics over the past years has allowed the discovery of a large number of potential biomarker candidates to improve early tumor diagnosis and therapeutic response, thus being further integrated into clinical environment. High grade gliomas represent one of the most aggressive and treatment-resistant types of human brain cancer, with approximately 9-12 months median survival rate for patients with grade IV glioma (glioblastoma). Using state-of-the-art proteomics technologies, we have investigated the proteome profile for glioblastoma patients in order to identify a novel protein biomarker panel that could discriminate glioblastoma patients from controls and increase diagnostic accuracy.

RESULTS

In this study, SELDI-ToF MS technology was used to screen potential protein patterns in glioblastoma patients serum; furthermore, LC-MS/MS technology was applied to identify the candidate biomarkers peaks. Through these proteomic approaches, three proteins S100A8, S100A9 and CXCL4 were selected as putative biomarkers and confirmed by ELISA. Next step was to validate the above mentioned molecules as biomarkers through identification of protein expression by Western blot in tumoral versus peritumoral tissue.

CONCLUSIONS

Proteomic technologies have been used to investigate the protein profile of glioblastoma patients and established several potential diagnostic biomarkers. While it is unlikely for a single biomarker to be highly effective for glioblastoma diagnostic, our data proposed an alternative and efficient approach by using a novel combination of multiple biomarkers.

Plasma peptide biomarker discovery for amyotrophic lateral sclerosis by MALDI-TOF mass spectrometry profiling

The diagnostic of Amyotrophic lateral sclerosis (ALS) remains based on clinical and neurophysiological observations. The actual delay between the onset of the symptoms and diagnosis is about 1 year, preventing early inclusion of patients into clinical trials and early care of the disease. Therefore, finding biomarkers with high sensitivity and specificity remains urgent. In our study, we looked for peptide biomarkers in plasma samples using reverse phase magnetic beads (C18 and C8) and MALDI-TOF mass spectrometry analysis. From a set of ALS patients (n=30) and healthy age-matched controls (n=30), C18- or C8-SVM-based models for ALS diagnostic were constructed on the base of the minimum of the most discriminant peaks. These two SVM-based models end up in excellent separations between the 2 groups of patients (recognition capability overall classes > 97%) and classify blinded samples (10 ALS and 10 healthy age-matched controls) with very high sensitivities and specificities (>90%). Some of these discriminant peaks have been identified by Mass Spectrometry (MS) analyses and correspond to (or are fragments of) major plasma proteins, partly linked to the blood coagulation.

Genetic and molecular alterations in pancreatic cancer: implications for personalized medicine

Recent advances in human genomics and biotechnologies have profound impacts on medical research and clinical practice. Individual genomic information, including DNA sequences and gene expression profiles, can be used for prediction, prevention, diagnosis, and treatment for many complex diseases. Personalized medicine attempts to tailor medical care to individual patients by incorporating their genomic information. In a case of pancreatic cancer, the fourth leading cause of cancer death in the United States, alteration in many genes as well as molecular profiles in blood, pancreas tissue, and pancreas juice has recently been discovered to be closely associated with tumorigenesis or prognosis of the cancer. This review aims to summarize recent advances of important genes, proteins, and microRNAs that play a critical role in the pathogenesis of pancreatic cancer, and to provide implications for personalized medicine in pancreatic cancer.

Circulating proteolytic products of carboxypeptidase N for early detection of breast cancer

BACKGROUND

Carboxypeptidase N (CPN) is important in regulating vasoactive peptide hormones, growth factors, and cytokines by specifically cleaving their C-terminal basic residues. We investigated whether circulating peptides specifically cleaved by CPN in the tumor microenvironment can be stage-specific indicators of breast cancer.

METHODS

CPN activity was measured using an ex vivo peptide cleavage assay by incubating synthesized C3f peptide (His6-C3f_S1304-R1320-His6) in interstitial fluids of breast tumors and adjacent normal breast tissues in mice with orthotopic implantation of the human cell line MDA-MB-231. The nature and extent of peptide cleavage by CPN was investigated by fragment profiling using nanopore fractionation and mass spectrometry. The fragment profiles in interstitial fluid correlated with concentrations of CPN-catalyzed peptides in blood samples taken from the tumor-bearing mice, healthy women, and breast cancer patients. CPN expression in the same set of samples was further examined by immunohistochemistry and immunoblotting.

RESULTS

We showed that generation of C3f_R1310-L1319 specifically correlated with the CPN expression level. In both the mouse and clinical patient samples, CPN was clearly increased in tumor tissues compared with normal breast tissue, whereas corresponding CPN abundance in blood remained constant. Concentrations of 6 CPN-catalyzed peptides predominantly increased in sera taken from the mice (n = 8) at 2 weeks after orthotopic implantation. Six homologous peptides displayed significantly higher expression in the patients' plasma as early as the first pathologic stage of breast cancer.

CONCLUSIONS

Circulating CPN-catalyzed peptide concentrations reflect the CPN activity in tumors. These biomarkers show strong potential for the noninvasive and early diagnosis of breast cancer.

Serum dihydroxyacetone kinase peptide m/z 520.3 as predictor of disease severity in patients with compensated chronic hepatitis B

Background & aim

Due to known limitations of liver biopsy, reliable non-invasive serum biomarkers for chronic liver diseases are needed. We performed serum peptidomics for such investigation in compensated chronic hepatitis B (CHB) patients.

Methods

Liquid chromatography combined with tandem mass spectrometry (LC-MS/MS) was used to identify differentially expressed peptides in sera from 40 CHB patients (20 with S0G0-S1G1 and 20 with S3G3-S4G4). Ion pair quantification from differentially expressed peptides in a validation set of sera from 86 CHB patients was done with multiple reaction monitoring (MRM).

Results

21 differentially represented peptide peaks were found through LC-MS/MS. Ion pairs generated from eleven of these peptides (m/z < 800) were quantified by MRM. Summed peak area ratios of 6 ion pairs from peptide m/z 520.3 (176.1, 353.7, 459.8, 503.3, 351.3, 593.1), which was identified as dihydroxyacetone kinase (DAK) fragment, decreased from mild to advanced stages of fibrosis or inflammation. Area Under Receiver Operating Characteristic Curves (AUROCs) of five ion models discriminating fibrosis degrees were 0.871 ~ 0.915 (S2-4 versus S0-1) and 0.804 ~ 0.924 (S3-4 versus S0-2). AUROCs discriminating inflammation grades were 0.840 ~ 0.902 (G2-4 versus G0-1) and 0.787 ~ 0.888 (G3-4 versus G0-2). The diagnostic power of these models provides improved sensitivity and specificity for predicting disease progression as compared to aspartate aminotransferase to platelet ratio index (APRI), FIB-4, Forn’s index and serum DAK protein.

Conclusions

The peptide fragment (m/z 520.3) of DAK is a promising biomarker to guide timing of antiviral treatment and to avoid liver biopsy in compensated CHB patients.

Serum peptidomic profiling identifies a minimal residual disease detection and prognostic biomarker for patients with acute leukemia

The evaluation of minimal residual disease (MRD) in acute leukemia (AL) is currently recognized as a potential critical tool to assess the response and relapse rate of treatments. The present study investigated serum peptides from patients with AL to identify biomarkers that would be useful in providing clinical evaluations and independent prognostic information. The patterns of serum peptides from 123 patients with AL and 49 healthy controls were analyzed using matrix-assisted laser desorption/ionization-time of flight mass spectrometry. Furthermore, diagnostic models of differential peptides were established using the support vector machine (SVM) algorithm to discriminate between the AL patients and healthy controls or between the AL patients with various degrees of remission. Finally, the peptides were applied to evaluate the prognosis of the affected patients. The area under the receiver operating characteristic (ROC) curve (AUC), analyzed using the SVM algorithm to distinguish between the AL patients and healthy controls, was 0.921. The AUC of the models for distinguishing between the newly-diagnosed AL patients and those in AL-hematological complete remission (HCR) and between the AL-HCR patients from those in AL-molecular remission (MR), was 0.824 and 0.919, respectively. A short serum peptide of m/z 4625 was identified to decrease in density in parallel with an increase in the degree of remission, which was used to monitor the MRD level. The intensity of the m/z 4625 peptide was significantly correlated with a poor overall survival (OS). The m/z 4625 peptide was identified to be a partial fragment of SERPINA3. The serum peptide pattern is high in sensitivity and specificity and may be used to discriminate between AL patients with various degrees of remission. The m/z 4625 peptide may be used to monitor the MRD levels and provide independent prognostic information in patients with AL.

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma

Metabolomics as one of the most rapidly growing technologies in the "-omics" field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients [Formula: see text] We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and-despite all its current limitations-can deliver marker panels with high selectivity even in multi-class settings.

Identification and verification of transthyretin as a potential biomarker for pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers worldwide and is difficult to detect at its early stages when treatment is most effective. Therefore, we performed a comparative proteomic study to identify new biomarkers for the detection of PDAC.

METHODS

Serum samples from patients with PDAC, chronic pancreatitis and normal controls were compared using two-dimensional difference gel electrophoresis (2D-DIGE). Differentially expressed separated proteins were subsequently identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/TOF-MS). Then, transthyretin (TTR), one of the differentially expressed proteins, was validated through real-time PCR, western blot and immunohistochemistry. Finally, enzyme-linked immunosorbent assays (ELISA) were employed to confirm the levels of transthyretin in the sera.

RESULTS

A total of 21 protein spots showed greater than 1.5-fold changes in expression level in the sera from PDAC patients compared with the normal controls. Among the identified proteins, validation experiments verified the differential expression of transthyretin in PDAC tissue, confirming the proteomic data showing that transthyretin was significantly elevated in patients with PDAC. The ELISA results revealed that the sensitivity and specificity for TTR and CA19-9 in distinguishing PDAC patients from normal individuals were 90.5, 47.6, 66.7 and 85.7 %, respectively, and 81.0 and 85.7 % for their combination.

CONCLUSIONS

These results suggest that the level of transthyretin is elevated in patients with PDAC. In combination with CA19-9, transthyretin may provide additional information for the detection of PDAC and should be further investigated.

A novel serum metabolomics-based diagnostic approach to pancreatic cancer

BACKGROUND

To improve the prognosis of patients with pancreatic cancer, more accurate serum diagnostic methods are required. We used serum metabolomics as a diagnostic method for pancreatic cancer.

METHODS

Sera from patients with pancreatic cancer, healthy volunteers, and chronic pancreatitis were collected at multiple institutions. The pancreatic cancer and healthy volunteers were randomly allocated to the training or the validation set. All of the chronic pancreatitis cases were included in the validation set. In each study, the subjects' serum metabolites were analyzed by gas chromatography mass spectrometry (GC/MS) and a data processing system using an in-house library. The diagnostic model constructed via multiple logistic regression analysis in the training set study was evaluated on the basis of its sensitivity and specificity, and the results were confirmed by the validation set study.

RESULTS

In the training set study, which included 43 patients with pancreatic cancer and 42 healthy volunteers, the model possessed high sensitivity (86.0%) and specificity (88.1%) for pancreatic cancer. The use of the model was confirmed in the validation set study, which included 42 pancreatic cancer, 41 healthy volunteers, and 23 chronic pancreatitis; that is, it displayed high sensitivity (71.4%) and specificity (78.1%); and furthermore, it displayed higher sensitivity (77.8%) in resectable pancreatic cancer and lower false-positive rate (17.4%) in chronic pancreatitis than conventional markers.

CONCLUSIONS

Our model possessed higher accuracy than conventional tumor markers at detecting the resectable patients with pancreatic cancer in cohort including patients with chronic pancreatitis.

IMPACT

It is a promising method for improving the prognosis of pancreatic cancer via its early detection and accurate discrimination from chronic pancreatitis.

Profiling the potential tumor markers of pancreatic ductal adenocarcinoma using 2D-DIGE and MALDI-TOF-MS: up-regulation of Complement C3 and alpha-2-HS-glycoprotein

BACKGROUND/AIMS

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with an increasing incidence worldwide. Due to lack of early diagnosis and poor prognosis, it is rather critical to improve the early diagnosis of PDAC. A comparative proteomic method was used to analyze serum proteins to find a new potential specific marker.

METHODS

Comparative analysis of the pancreatic peripheral blood protein profiling from 40 pancreatic cancer patients, 10 pancreatic benign tumor patients, 10 chronic pancreatitis patients and 40 cancer-free controls. The samples were carried out by 2D-differential gel electrophoresis (2D-DIGE) and differentially expressed proteins were identified by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS). Two up-regulated proteins were further validation by real time RT-PCR, Western blot analysis and Immunohistochemistry (IHC).

RESULTS

We identified fourteen differently expressed proteins in PDAC group compared with cancer-free control group, including 9 up-regulation and 5 down-regulation proteins. Increased Complement C3 and alpha-2-HS-glycoprotein (AHSG) were further confirmed by real time RT-PCR, Western blot analysis and IHC. The expressions of Complement C3 and AHSG were higher in PDAC than that in other groups.

CONCLUSIONS

These results suggest that Complement C3 and AHSG might be the potential tumor markers in PDAC screening and diagnosis. The finding of inflammation mediated factor Complement C3 revealed that inflammation might be closely related with the occurrence and development process of PDAC.

Two classifiers based on serum peptide pattern for prediction of HBV-induced liver cirrhosis using MALDI-TOF MS

Chronic infection with hepatitis B virus (HBV) is associated with the majority of cases of liver cirrhosis (LC) in China. Although liver biopsy is the reference method for evaluation of cirrhosis, it is an invasive procedure with inherent risk. The aim of this study is to discover novel noninvasive specific serum biomarkers for the diagnosis of HBV-induced LC. We performed bead fractionation/MALDI-TOF MS analysis on sera from patients with LC. Thirteen feature peaks which had optimal discriminatory performance were obtained by using support-vector-machine-(SVM-) based strategy. Based on the previous results, five supervised machine learning methods were employed to construct classifiers that discriminated proteomic spectra of patients with HBV-induced LC from those of controls. Here, we describe two novel methods for prediction of HBV-induced LC, termed LC-NB and LC-MLP, respectively. We obtained a sensitivity of 90.9%, a specificity of 94.9%, and overall accuracy of 93.8% on an independent test set. Comparisons with the existing methods showed that LC-NB and LC-MLP held better accuracy. Our study suggests that potential serum biomarkers can be determined for discriminating LC and non-LC cohorts by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. These two classifiers could be used for clinical practice in HBV-induced LC assessment.

Serum biomarkers identification by mass spectrometry in high-mortality tumors

Cancer affects millions of people worldwide. Tumor mortality is substantially due to diagnosis at stages that are too late for therapies to be effective. Advances in screening methods have improved the early diagnosis, prognosis, and survival for some cancers. Several validated biomarkers are currently used to diagnose and monitor the progression of cancer, but none of them shows adequate specificity, sensitivity, and predictive value for population screening. So, there is an urgent need to isolate novel sensitive, specific biomarkers to detect the disease early and improve prognosis, especially in high-mortality tumors. Proteomic techniques are powerful tools to help in diagnosis and monitoring of treatment and progression of the disease. During the last decade, mass spectrometry has assumed a key role in most of the proteomic analyses that are focused on identifying cancer biomarkers in human serum, making it possible to identify and characterize at the molecular level many proteins or peptides differentially expressed. In this paper we summarize the results of mass spectrometry serum profiling and biomarker identification in high mortality tumors, such as ovarian, liver, lung, and pancreatic cancer.

Investigation of Pokemon-regulated proteins in hepatocellular carcinoma using mass spectrometry-based multiplex quantitative proteomics

Pokemon is a transcription regulator involved in embryonic development, cellular differentiation and oncogenesis. It is aberrantly overexpressed in multiple human cancers including Hepatocellular carcinoma (HCC) and is considered as a promising biomarker for HCC. In this work, the isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy was used to investigate the proteomic profile associated with Pokemon in human HCC cell line QGY7703 and human hepatocyte line HL7702. Samples were labeled with four-plex iTRAQ reagents followed by two-dimensional liquid chromatography coupled with tandem mass spectrometry analysis. A total of 24 differentially expressed proteins were selected as significant. Nine proteins were potentially up-regulated by Pokemon while 15 proteins were potentially down-regulated and many proteins were previously identified as potential biomarkers for HCC. Gene ontology (GO) term enrichment revealed that the listed proteins were mainly involved in DNA metabolism and biosynthesis process. The changes of glucose-6-phosphate 1-dehydrogenase (G6PD, up-regulated) and ribonucleoside-diphosphate reductase large sub-unit (RIM1, down-regulated) were validated by Western blotting analysis and denoted as Pokemon's function of oncogenesis. We also found that Pokemon potentially repressed the expression of highly clustered proteins (MCM3, MCM5, MCM6, MCM7) which played key roles in promoting DNA replication. Altogether, our results may help better understand the role of Pokemon in HCC and promote the clinical applications.

Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer

Lung cancer is the leading cause of cancer deaths worldwide. Clinically, the treatment of non-small cell lung cancer (NSCLC) can be improved by the early detection and risk screening among population. To meet this need, here we describe the application of extensive peptide level fractionation coupled with label free quantitative proteomics for the discovery of potential serum biomarkers for lung cancer, and the usage of Tissue microarray analysis (TMA) and Multiple reaction monitoring (MRM) assays for the following up validations in the verification phase. Using these state-of-art, currently available clinical proteomic approaches, in the discovery phase we confidently identified 647 serum proteins, and 101 proteins showed a statistically significant association with NSCLC in our 18 discovery samples. This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood. Of these proteins, Alpha-1B-glycoprotein (A1BG) and Leucine-rich alpha-2-glycoprotein (LRG1), two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients. We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.