Biomarker identification in human pancreatic cancer sera

Blood-Based Multiomics-Guided Detection of a Precancerous Pancreatic Tumor

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

Protein Arginine Methylation Patterns in Plasma Small Extracellular Vesicles Are Altered in Patients with Early-Stage Pancreatic Ductal Adenocarcinoma

Small extracellular vesicles (sEVs) contain lipids, proteins and nucleic acids, which often resemble their cells of origin. Therefore, plasma sEVs are considered valuable resources for cancer biomarker development. However, previous efforts have been largely focused on the level of proteins and miRNAs in plasma sEVs, and the post-translational modifications of sEV proteins, such as arginine methylation, have not been explored. Protein arginine methylation, a relatively stable post-translational modification, is a newly described molecular feature of PDAC. The present study examined arginine methylation patterns in plasma sEVs derived from patients with early-stage PDAC (n = 23) and matched controls. By utilizing the arginine methylation-specific antibodies for western blotting, we found that protein arginine methylation patterns in plasma sEVs are altered in patients with early-stage PDAC. Specifically, we observed a reduction in the level of symmetric dimethyl arginine (SDMA) in plasma sEV proteins derived from patients with early- and late-stage PDAC. Importantly, immunoprecipitation followed by proteomics analysis identified a number of arginine-methylated proteins exclusively present in plasma sEVs derived from patients with early-stage PDAC. These results indicate that arginine methylation patterns in plasma sEVs are potential indicators of PDAC, a new concept meriting further investigation.

Hydrophilic Peptide and Glycopeptide as Immobilized Sorbents for Glycosylation Analysis

Hydrophilic interaction liquid chromatography (HILIC) is widely used for glycopeptide enrichment in shot-gun glycoproteomics to enhance the glycopeptide signal and minimize the ionization competition of peptides. In this work, we have developed a novel hydrophilic material (glycoHILIC) based on glycopeptides and peptides to provide hydrophilic properties. GlycoHILIC was synthesized by oxidizing cotton and then reacting the resulting aldehyde with the N-terminus of the glycopeptide or peptide by reductive amination. Due to the large amount of hydrophilic carbohydrates and hydrophilic amino acids contained in glycopeptides, glycoHILIC showed significantly better enrichment of glycopeptides than cotton itself. Our results demonstrate that glycoHILIC has high selectivity, a low detection limit, and good stability. Over 257 unique N-linked glycosylation sites in 1477 intact N-glycopeptides from 146 glycoproteins were identified from 1 μL of human serum using glycoHILIC. Serum analysis of pancreatic cancer patients found that 38 N-glycopeptides among 21 glycoproteins changed significantly, of which 7 N-glycopeptides increased and 31 N-glycopeptides decreased. These results demonstrate that glycoHILIC can be used for glycopeptide enrichment and analysis.

Phaseolus vulgaris Erythroagglutinin (PHA-E)-Positive Ceruloplasmin Acts as a Potential Biomarker in Pancreatic Cancer Diagnosis

Pancreatic cancer (PC) remains one of the top 10 causes of cancer-related death in recent years. Approximately 80% of PC patients are diagnosed at the middle or advanced stage and miss the opportunity for surgery. The demand for early diagnostic methods and reliable biomarkers is increasing, although a number of tumor markers such as CA19-9 and CEA have already been utilized in clinics. In this study, we analyzed the alteration of N-glycan of serum glycoproteins by mass spectrometry and lectin blotting. The results showed that bisecting GlcNAc structures of glycoproteins are significantly increased in PC patients' sera. With Phaseolus vulgaris Erythroagglutinin (PHA-E) lectin that specifically recognizes bisecting GlcNAc N-glycans, the serum glycoproteins bearing bisecting GlcNAc in PC patients' sera were pulled down and identified by nano-LC-MS/MS. Among them, ceruloplasmin (Cp) was screened out with a satisfied sensitivity and specificity in identifying PC from acute pancreatitis patients (AUC: 0.757) and normal healthy persons (AUC: 0.972), suggesting a close association between Cp and PC development and diagnosis. To prove that, the Cp expression in tumor tissues of PC patients was examined. The results showed that Cp was significantly upregulated in PC tissues compared to that in adjacent normal tissues. All these results suggested that PHA-E-positive Cp could be a potential PC-specific glycoprotein marker to distinguish PC patients from acute pancreatitis patients and normal persons.

Bioinformatic Analysis and Integration of Transcriptome and Proteome Results Identify Key Coding and Noncoding Genes Predicting Malignancy in Intraductal Papillary Mucinous Neoplasms of the Pancreas

BACKGROUND

Intraductal papillary mucinous neoplasms (IPMNs) are precursor lesions of pancreatic ductal adenocarcinoma (PDAC). IPMNs are generally associated with high risk of developing malignancy and therefore need to be diagnosed and assessed accurately, once detected. Existing diagnostic methods are inadequate, and identification of efficient biomarker capable of detecting high-risk IPMNs is necessitated. Moreover, the mechanism of development of malignancy in IPMNs is also elusive.

METHODS

Gene expression meta-analysis conducted using 12 low-risk IPMN and 23 high-risk IPMN tissue samples. We have also listed all the altered miRNAs and long noncoding RNAs (lncRNAs), identified their target genes, and performed pathway analysis. We further enlisted cyst fluid proteins detected to be altered in high-risk or malignant IPMNs and compared them with fraction of differentially expressed genes secreted into cyst fluid.

RESULTS

Our meta-analysis identified 270 upregulated and 161 downregulated genes characteristically altered in high-risk IPMNs. We further identified 61 miRNAs and 14 lncRNAs and their target genes and key pathways contributing towards understanding of the gene regulation during the progression of the disease. Most importantly, we have detected 12 genes altered significantly both in cystic lesions and cyst fluid.

CONCLUSION

Our study reports, for the first time, a meta-analysis identifying key changes in gene expression between low-risk and high-risk IPMNs and also explains the regulatory aspect through construction of a miRNA-lncRNA-mRNA interaction network. The 12-gene-signature could function as potential biomarker in cyst fluid for detection of IPMN with a high risk of developing malignancy.

Label-free proteomics reveals serum proteins whose levels differ between pancreatic ductal adenocarcinoma patients with short or long survival

Pancreatic ductal adenocarcinoma is the most common and aggressive type of pancreatic cancer, with a 5-year survival rate that is less than 10%. New biomarkers to aid in predicting the prognosis of pancreatic ductal adenocarcinoma patients are needed. Previous proteomic studies have to a great extent focused on finding proteins of value for the diagnosis of pancreatic ductal adenocarcinoma. There is a lack of studies that have profiled the serum or plasma proteome in order to discover candidates for new prognostic biomarkers. In this study, we have used ultra-performance liquid chromatography-ultra-definition mass spectrometry to analyze the serum samples of 21 pancreatic ductal adenocarcinoma patients with short or long survival. Statistical analysis discovered 31 proteins whose expression differed significantly between pancreatic ductal adenocarcinoma patients with short or long survival. Pathway analysis discovered multiple canonical pathways enriched in this data set, with several pathways having roles in inflammation and lipid metabolism. The serum proteins identified here, which include complement components and several enzymes, could be of value as candidates for new noninvasive prognostic markers.

Markers of Inflammation

Inflammation is a complex and necessary component of the response to biological, chemical, or physical stimuli, and the cellular and molecular events that initiate and regulate the interactions between the various players in the inflammatory process remain a source of ongoing investigation. In the acute phase of the inflammatory response, cells of the immune system migrate to the site of injury in a carefully orchestrated sequence of events that is facilitated by soluble mediators such as cytokines, chemokines, and acute-phase proteins. Depending on the degree of injury, this acute phase may be sufficient to resolve the damage and initiate healing processes. Persistent inflammation, either as a result of prolonged exposure to stimulation or an inappropriate reaction against self-molecules, can lead to the chronic phase, in which tissue damage and fibrosis can occur. Chronic inflammation has been reported to contribute to numerous diseases, including arthritis, asthma, atherosclerosis, autoimmune diseases, diabetes, and cancer, and to conditions of aging. Hematology and clinical chemistry data from standard toxicology studies can provide an initial indication of the presence and sometimes the location of inflammation. These data may suggest more specific immune function assays that are necessary to determine the presence and/or mechanism(s) of immunomodulation. Although changes in hematology dynamics, acute-phase proteins, complement factors, and cytokines are common to virtually all inflammatory conditions, and can be measured by a variety of techniques, individual biomarkers have yet to be strongly associated with specific pathologic events. Thus, although sensitive indicators of inflammation, these factors generally lack the specificity to identify the offending cause. The profile seen in a given inflammatory condition is dependent on the severity, chronicity, and mechanisms involved in the inflammatory process, as well as the species and the capacity of the individual's immune system to respond and adapt.

Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination

AIM

Pancreatic cancer is one of the worst malignant tumors in prognosis. Therefore, to reduce the mortality rate of pancreatic cancer, early diagnosis and prompt treatment are particularly important.

RESULTS

We put forward a new feature-selection method that was used to find clinical markers for pancreatic cancer by combination of Support Vector Machine Recursive Feature Elimination (SVM-RFE) and Large Margin Distribution Machine Recursive Feature Elimination (LDM-RFE) algorithms. As a result, seven differentially expressed genes were predicted as specific biomarkers for pancreatic cancer because of their highest accuracy of classification on cancer and normal samples.

CONCLUSION

Three (MMP7, FOS and A2M) out of the seven predicted gene markers were found to encode proteins secreted into urine, providing potential diagnostic evidences for pancreatic cancer.

Distinguishing neurocysticercosis epilepsy from epilepsy of unknown etiology using a minimal serum mass profiling platform

Neurocysticercosis is associated with epilepsy in pig-raising communities with poor sanitation. Current internationally recognized diagnostic guidelines for neurocysticercosis rely on brain imaging, a technology that is frequently not available or not accessible in areas endemic for neurocysticercosis. Minimally invasive and low-cost aids for diagnosing neurocysticercosis epilepsy could improve treatment of neurocysticercosis. The goal of this study was to test the extent to which patients with neurocysticercosis epilepsy, epilepsy of unknown etiology, idiopathic headaches and among different types of neurocysticercosis lesions could be distinguished from each other based on serum mass profiling. For this, we collected sera from patients with neurocysticercosis-associated epilepsy, epilepsy of unknown etiology, recovered neurocysticercosis, and idiopathic headaches then performed binary group comparisons among them using electrospray ionization mass spectrometry. A leave one [serum sample] out cross validation procedure was employed to analyze spectral data. Sera from neurocysticercosis patients was distinguished from epilepsy of unknown etiology patients with a p-value of 10^-28. This distinction was lost when samples were randomized to either group (p-value = 0.22). Similarly, binary comparisons of patients with neurocysticercosis who has different types of lesions showed that different forms of this disease were also distinguishable from one another. These results suggest neurocysticercosis epilepsy can be distinguished from epilepsy of unknown etiology based on biomolecular differences in sera detected by mass profiling.

Can the Acute-Phase Reactant Proteins be Used as Cancer Biomarkers?

The association between the acute-phase reactant proteins (APRPs) and cancer has long been established. There have been numerous reports correlating altered levels of various APRPs with different types of cancers. However, researchers are often quick to dismiss the use of these APRPs as potential biomarkers for the diagnosis and monitoring of cancer because alterations in APRP concentrations are observed in a wide range of diseases. Recent progress in proteomics studies which profiled the serum proteins of cancer patients and those of normal individuals indicated that the altered APRP expressions were different for distinct types, subtypes, and even stages of cancer. Interestingly, these data are in agreement with those observed earlier using immunochemical and biochemical assays. In view of this compelling association of different patterns of APRPs with various types of cancers and in an apparent shift of paradigm, we present in this review some indications that APRP fingerprinting may be used as complementary cancer biomarkers.

Complement in cancer: untangling an intricate relationship

In tumour immunology, complement has traditionally been considered as an adjunctive component that enhances the cytolytic effects of antibody-based immunotherapies, such as rituximab. Remarkably, research in the past decade has uncovered novel molecular mechanisms linking imbalanced complement activation in the tumour microenvironment with inflammation and suppression of antitumour immune responses. These findings have prompted new interest in manipulating the complement system for cancer therapy. This Review summarizes our current understanding of complement-mediated effector functions in the tumour microenvironment, focusing on how complement activation can act as a negative or positive regulator of tumorigenesis. It also offers insight into clinical aspects, including the feasibility of using complement biomarkers for cancer diagnosis and the use of complement inhibitors during cancer treatment.

Serum Monitoring and Phenotype Identification of Stage I Non-Small Cell Lung Cancer Patients

A stage I non-small cell lung cancer (NSCLC) serum profiling platform is presented which is highly efficient and accurate. Test sensitivity (0.95) for stage I NSCLC is the highest reported so far. Test metrics are reported for discriminating stage I adenocarcinoma vs squamous cell carcinoma subtypes. Blinded analysis identified 23 out of 24 stage I NSCLC and control serum samples. Group-discriminating mass peaks were targeted for tandem mass spectrometry peptide/protein identification, and yielded a lung cancer phenotype. Bioinformatic analysis revealed a novel lymphocyte adhesion pathway involved with early-stage lung cancer.

Gprc5a-knockout mouse lung epithelial cells predicts ceruloplasmin, lipocalin 2 and periostin as potential biomarkers at early stages of lung tumorigenesis

Lung cancer is the leading cause of cancer death. As most of lung cancer patients were diagnosed with the advanced stage, early detection is considered as the most effective strategy to reduce high mortality. Thus, it is desirable to identify specific biomarkers at early stages of lung tumorigenesis. GPRC5A is a lung tumor suppressor gene. GPRC5A deficiency is linked to lung cancer development. We hyposthesized that, dysregulated gene expression that results from Gprc5a deficiency may provide potential biomarkers at early stages of lung tumorigenesis. By analysis of top 20 upregulated genes in mouse tracheal epithelial cells (MTEC) of Gprc5a knockout (KO) vs wild-type (WT), we found that ceruloplasmin, lipocalin-2, and periostin are not only upregulated in lung epithelial cells of Gprc5a-ko mice, but also expressed at high levels in lung tumor tissues of Gprc5a-ko mice. This suggests that increased expression of these genes is associated with lung tumorigenesis. Importantly, expression of ceruloplasmin, lipocalin-2, and periostin has also been found to be significantly increased, both at mRNA and protein levels, in the lung tissues from NSCLC patients, which is correlated with repressed GPRC5A. Thus, dysregulated ceruloplasmin, lipocalin-2, and periostin may be used as potential biomarkers at early stages of lung tumorigenesis.

Protein biomarkers for early detection of diseases: The decisive contribution of combinatorial peptide ligand libraries

The present review deals with biomarker discovery, especially in regard to sample treatment via combinatorial peptide ligand libraries, perhaps the only technique at present allowing deep exploration of biological fluids and tissue extracts in search for low- to very-low-abundance proteins, which could possibly mark the onset of most pathologies. Early-stage biomarkers, in fact, might be the only way to detect the beginning of most diseases thus permitting proper intervention and care. The following cancers are reviewed, with lists of potential biomarkers suggested in various reports: hepatocellular carcinoma, ovarian cancer, breast cancer and pancreatic cancer, together with some other interesting applications. Although panels of proteins have been presented, with robust evidence, as potential early-stage biomarkers in these different pathologies, their approval by FDA as novel biomarkers in routine clinical chemistry settings would require plenty of additional work and efforts from the pharma industry. The science environment in universities could simply not afford such heavy monetary investments.

SIGNIFICANCE

After more than 16years of search for novel biomarkers, to be used in a clinical chemistry set-up, via proteomic analysis (mostly in biological fluids) it was felt a critical review was due. In the present report, though, only papers reporting biomarker discovery via combinatorial peptide ligand libraries are listed and assessed, since this methodology seems to be the most advanced one for digging in depth into low-to very-low-abundance proteins, which might represent important biomarkers for the onset of pathologies. In particular, a large survey has been made for the following diseases, since they appear to have a large incidence on human population and/or represent fatal diseases: ovarian cancer, breast cancer, pancreatic cancer and hepatocellular carcinoma.

Comparative proteomic profiling of the serum differentiates pancreatic cancer from chronic pancreatitis

Finland ranks sixth among the countries having highest incidence rate of pancreatic cancer with mortality roughly equaling incidence. The average age of diagnosis for pancreatic cancer is 69 years in Nordic males, whereas the average age of diagnosis of chronic pancreatitis is 40–50 years, however, many cases overlap in age. By radiology, the evaluation of a pancreatic mass, that is, the differential diagnosis between chronic pancreatitis and pancreatic cancer is often difficult. Preoperative needle biopsies are difficult to obtain and are demanding to interpret. New blood based biomarkers are needed. The accuracy of the only established biomarker for pancreatic cancer, CA 19‐9 is rather poor in differentiating between benign and malignant mass of the pancreas. In this study, we have performed mass spectrometry analysis (High Definition MS^E) of serum samples from patients with chronic pancreatitis (13) and pancreatic cancer (22). We have quantified 291 proteins and performed detailed statistical analysis such as principal component analysis, orthogonal partial least square discriminant analysis and receiver operating curve analysis. The proteomic signature of chronic pancreatitis versus pancreatic cancer samples was able to separate the two groups by multiple statistical techniques. Some of the enriched pathways in the proteomic dataset were LXR/RXR activation, complement and coagulation systems and inflammatory response. We propose that multiple high‐confidence biomarker candidates in our pilot study including Inter‐alpha‐trypsin inhibitor heavy chain H2 (Area under the curve, AUC: 0.947), protein AMBP (AUC: 0.951) and prothrombin (AUC: 0.917), which should be further evaluated in larger patient series as potential new biomarkers for differential diagnosis.

Complement in Pancreatic Disease-Perpetrator or Savior?

The complement system is a major pillar of the humoral innate immune system. As a first line of defense against pathogens, it mediates early inflammatory response and links different branches of humoral and cellular immunity. Disorders affecting the exocrine pancreas, such as acute pancreatitis, potentially lead to a life-threatening systemic inflammatory response with aberrant activation of complement and coagulation cascades. Pancreatic proteases can activate key effectors of the complement system, which in turn drive local and systemic inflammation. Beyond that, the extent of pancreas–complement interaction covers complex pro- and anti-inflammatory mechanisms, which to this day remain to be fully elucidated. This review provides a comprehensive overview of the pathophysiological role of complement in diseases of the exocrine pancreas, based on existing experimental and clinical data. Participation of complement in acute and chronic pancreatitis is addressed, as well as its role in tumor immunology. Therapeutic strategies targeting complement in these diseases have long been proposed but have not yet arrived in the clinical setting.

Secretome protein signature of human pancreatic cancer stem-like cells

Emerging research has demonstrated that pancreatic ductal adenocarcinoma (PDAC) contains a sub-population of cancer stem cells (CSCs) characterized by self-renewal, anchorage-independent-growth, long-term proliferation and chemoresistance. The secretome analysis of pancreatic CSCs has not yet been performed, although it may provide insight into tumour/microenvironment interactions and intracellular processes, as well as to identify potential biomarkers. To characterize the secreted proteins of pancreatic CSCs, we performed an iTRAQ-based proteomic analysis to compare the secretomes of Panc1 cancer stem-like cells (Panc1 CSCs) and parental cell line. A total of 72 proteins were found up-/down-regulated in the conditioned medium of Panc1 CSCs. The pathway analysis revealed modulation of vital physiological pathways including glycolysis, gluconeogenesis and pentose phosphate. Through ELISA immunoassays we analysed the presence of the three proteins most highly secreted by Panc1 CSCs (ceruloplasmin, galectin-3, and MARCKS) in sera of PDAC patient. ROC curve analysis suggests ceruloplasmin as promising marker for patients negative for CA19-9. Overall, our study provides a systemic secretome analysis of pancreatic CSCs revealing a number of secreted proteins which participate in pathological conditions including cancer differentiation, invasion and metastasis. They may serve as a valuable pool of proteins from which biomarkers and therapeutic targets can be identified.

BIOLOGICAL SIGNIFICANCE

The secretome of CSCs is a rich reservoir of biomarkers of cancer progression and molecular therapeutic targets, and thus is a topic of great interest for cancer research. The secretome analysis of pancreatic CSCs has not yet been performed. Recently, our group has demonstrated that Panc-1 CSCs isolated from parental cell line by using the CSC selective medium, represent a model of great importance to deepen the understanding of the biology of pancreatic adenocarcinoma. To our knowledge, this is the first proteomic study of pancreatic CSC secretome. We performed an iTRAQ-based analysis to compare the secretomes of Panc1 CSCs and Panc1 parental cell line and identified a total of 43 proteins secreted at higher level by pancreatic cancer stem cells. We found modulation of different vital physiological pathways (such as glycolysis and gluconeogenesis, pentose phosphate pathway) and the involvement of CSC secreted proteins (for example 72kDa type IV collagenase, galectin-3, alpha-actinin-4, and MARCKS) in pathological conditions including cancer differentiation, invasion and metastasis. By ELISA verification we found that MARCKS and ceruloplasmin discriminate between controls and PDAC patients; in addition ROC curve analyses indicate that MARCKS does not have diagnostic accuracy, while ceruloplasmin could be a promising marker only for patients negative for CA19-9. We think that the findings reported in our manuscript advance the understanding of the pathways implicated in tumourigenesis, metastasis and chemoresistance of pancreatic cancer, and also identify a pool of proteins from which novel candidate diagnostic and therapeutic biomarkers could be discovered.

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.

Expression analysis of apolipoprotein E and its associated genes in gastric cancer

Gastric cancer is a common type of cancer worldwide, and has a poor prognosis, in part due to the low rates of early diagnosis and the limited treatment methods available. Apolipoprotein E (ApoE) is involved in exogenous cholesterol transport and may be important in enabling tumor cells to fulfill their high cholesterol requirements. A number of reports have indicated that ApoE affects the development and prognosis of gastric cancer. Therefore, the aim of the present study was to investigate the genes and transcription factors that interact with ApoE during the development of gastric cancer. Using gene expression profiling, the BioGRID database and the transcriptional regulatory element database, gene expression and regulatory networks in gastric cancer tissues and adjacent normal tissues were analyzed. The data demonstrated that eight genes associated with ApoE were differentially expressed, with six of these upregulated and two downregulated. Functionally, these genes were involved in the JAK-STAT cascade, acute-phase response, acute inflammatory response, and the steroid hormone response. Among these ApoE-associated genes, expression of the signal transducer and activator of transcription 2 (STAT2) and STAT3 transcription factors was upregulated. To the best of our knowledge, this is the first study to demonstrate the network of ApoE-related genes and transcription factors in gastric cancer. Additional studies are required in order to confirm these data and to translate the results into the identification of clinical biomarkers and novel treatment strategies for gastric cancer.

Discriminating patients with early-stage pancreatic cancer or chronic pancreatitis using serum electrospray mass profiling

Blood tests are needed to aid in the early detection of pancreatic ductal adenocarcinoma (PDAC), and monitoring pancreatitis development into malignancy especially in high risk patients. This study exhibits efforts and progress toward developing such blood tests, using electrospray-mass spectrometry (MS) serum profiling to distinguish patients with early-stage PDAC or pancreatitis from each other and from controls. Identification of significant serum mass peak differences between these individuals was performed using t tests and "leave one out" cross validation. Serum mass peak distributions of control individuals were distinguished from those of patients with chronic pancreatitis or early-stage PDAC with P values <10(-15), and patients with chronic pancreatitis were distinguished from those of patients with early-stage PDAC with a P value <10(-12). Sera from 12 out of 12 patients with PDAC stages I, IIA and IIB were blindly validated from controls. Tandem MS/MS identified a cancer phenotype with elements of PDAC involved in early-stage PDAC/control discrimination. These studies indicate electrospray-MS mass profiling can detect serum changes in patients with pancreatitis or early-stage pancreatic cancer. Such technology has the potential to aid in early detection of pancreatic cancer, biomarker development, and in monitoring development of pancreatitis into PDAC.

Mass-selected site-specific core-fucosylation of ceruloplasmin in alcohol-related hepatocellular carcinoma

A mass spectrometry-based methodology has been developed to study changes in core-fucosylation of serum ceruloplasmin that are site-specific between cirrhosis and hepatocellular carcinoma (HCC). The serum samples studied for these changes were from patients affected by cirrhosis or HCC with different etiologies, including alcohol, hepatitis B virus, or hepatitis C virus. The methods involved trypsin digestion of ceruloplasmin into peptides followed by Endo F3 digestion, which removed most of the glycan structure while retaining the innermost N-acetylglucosamine (GlcNAc) and/or core-fucose bound to the peptide. This procedure simplified the structures for further analysis by mass spectrometry, where four core-fucosylated sites (sites 138, 358, 397, and 762) were detected in ceruloplasmin. The core-fucosylation ratio of three of these sites increased significantly in alcohol-related HCC samples (sample size = 24) compared to that in alcohol-related cirrhosis samples (sample size = 18), with the highest AUC value of 0.838 at site 138. When combining the core-fucosylation ratio of site 138 in ceruloplasmin and the alpha-fetoprotein (AFP) value, the AUC value increased to 0.954 (ORsite138 = 12.26, p = 0.017; ORAFP = 3.64, p = 0.022), which was markedly improved compared to that of AFP (AUC = 0.867) (LR test p = 0.0002) alone. However, in HBV- or HCV-related liver diseases, no significant site-specific change in core-fucosylation of ceruloplasmin was observed between HCC and cirrhosis.

A1BG and C3 are overexpressed in patients with cervical intraepithelial neoplasia III

The present study aimed to analyze sera proteins in females with cervical intraepithelial neoplasia, grade III (CIN III) and in healthy control females, in order to identify a potential biomarker which detects lesions that have a greater probability of cervical transformation. The present study investigated five sera samples from females who were Human Papilloma Virus (HPV) 16⁺ and who had been histopathologically diagnosed with CIN III, as well as five sera samples from healthy control females who were HPV-negative. Protein separation was performed using two-dimensional (2D) gel electrophoresis and the proteins were stained with Colloidal Coommassie Blue. Quantitative analysis was performed using ImageMaster 2D Platinum 6.0 software. Peptide sequence identification was performed using a nano-LC ESIMS/MS system. The proteins with the highest Mascot score were validated using western blot analysis in an additional 55 sera samples from the control and CIN III groups. The eight highest score spots that were found to be overexpressed in the CIN III sera group were identified as α-1-B glycoprotein (A1BG), complement component 3 (C3), a pro-apolipoprotein, two apolipoproteins and three haptoglobins. Only A1BG and C3 were validated using western blot analysis, and the bands were compared between the two groups using densitometry analysis. The relative density of the bands of A1BG and C3 was found to be greater in all of the serum samples from the females with CIN III, compared with those of the individuals in the control group. In summary, the present study identified two proteins whose expression was elevated in females with CIN III, suggesting that they could be used as biomarkers for CIN III. However, further investigations are required in order to assess the expression of A1BG and C3 in different pre-malignant lesions.

Distinguishing patients with stage I lung cancer versus control individuals using serum mass profiling

Serum mass profiling can discern physiological changes associated with specific disease states and their progression. Sera (86 total) from control individuals and patients with stage I nonsmall cell lung cancer or benign small pulmonary nodules were discriminated retrospectively by serum changes discerned by mass profiling. Control individuals were distinguished from patients with Stage I lung cancer or benign nodules with test sensitivities of 89% and 83%. Lung cancer patients versus those with benign nodules were distinguished with 80% sensitivity. This study exhibits progress toward a minimally-invasive aid in early detection of lung cancer and monitoring small pulmonary nodules for malignancy.

Mass profiling of serum to distinguish mice with pancreatic cancer induced by a transgenic Kras mutation

Mass spectrometry (MS) has the unique ability to profile, in an easily accessible body tissue (peripheral blood/serum,) the sizes and relative amounts of a wide variety of biomolecules in a single platform setting. Using electrospray ionization (ESI)-MS, we distinguished individual serum from wild-type control mice from serum of mice containing an oncogenic Kras mutation, which leads to development of pancreatic ductal adenocarcinoma (PDAC) similar to that observed in humans. Identification of differences in significant ESI-MS sera mass peaks between Kras-activated mice and control mice was performed using t tests and a "nested leave one out" cross-validation procedure. Peak distributions in serum of control mice from mice with Kras-mutant-dependent PDAC were distinguished from those of pancreatic intraepithelial neoplasia (PanIN) lesions (p = 0.00024). In addition, Kras mutant mice with PDAC were distinguished from Kras mutant mice with PanIN alone (p = 0.0057). Test specificity, a measure of the false positives, was greater for the control vs. Kras mutated mice, and the test sensitivity, a measure of false negatives, was greater for the PDAC vs. PanIN containing mice. Receiver-operating characteristic (ROC) curve discriminatory values were 0.85 for both comparisons. These studies indicate ESI-MS serum mass profiling can detect physiological changes associated with pancreatic cancer initiation and development in a GEM (genetic engineered mouse) model that mimics pancreatic cancer development in humans. Such technology has the potential to aid in early detection of pancreatic cancer and in developing therapeutic drug interventions.

Usefulness of MALDI-TOF/MS identification of low-MW fragments in sera for the differential diagnosis of pancreatic cancer

OBJECTIVES

To identify new biomarkers of pancreatic cancer (PaCa), we performed MALDI-TOF/MS analysis of sera from 22 controls, 51 PaCa, 37 chronic pancreatitis, 24 type II diabetes mellitus (DM), 29 gastric cancer (GC), and 24 chronic gastritis (CG).

METHODS

Sera were purified by Sep-Pak C18 before MALDI-TOF/MS Anchorchip analysis.

RESULTS

Features present in at least 5% of all spectra were selected (n = 160, m/z range, 1200-5000). At univariate analysis, 2 features (m/z 2049 and 2305) correlated with PaCa, 3 (m/z 1449, 1605, and 2006) with DM. No feature characterized gastric cancer or chronic gastritis. Ten-fold cross-validation binary recursive partitioning trees were obtained for patients' classification. The tree (CA 19-9, age, m/z 2006, 2599, 2753, and 4997), built considering only patients with diabetes, allowed a distinction between DM [area under the receiver operating characteristic curve (AUC), 0.997], chronic pancreatitis (AUC, 0.968), and PaCa (AUC, 0.980), with an overall correct classification rate of 89%. The tree including CA 19-9, 1550, and 2937 m/z features, achieved an AUC of 0.970 in distinguishing localized from advanced PaCa. MALDI-TOF-TOF analysis revealed the 1550 feature as a fragment of Apo-A1, which was determined as whole protein and demonstrated to be closely correlated with PaCa.

CONCLUSIONS

The findings made demonstrate a role for serum peptides identified using MALDI-TOF/MS for addressing PaCa diagnosis.

Current status and advances in quantitative proteomic mass spectrometry

The accurate quantitation of proteins and peptides in complex biological systems is one of the most challenging areas of proteomics. Mass spectrometry-based approaches have forged significant in-roads allowing accurate and sensitive quantitation and the ability to multiplex vastly complex samples through the application of robust bioinformatic tools. These relative and absolute quantitative measures using label-free, tags, or stable isotope labelling have their own strengths and limitations. The continuous development of these methods is vital for increasing reproducibility in the rapidly expanding application of quantitative proteomics in biomarker discovery and validation. This paper provides a critical overview of the primary mass spectrometry-based quantitative approaches and the current status of quantitative proteomics in biomedical research.

N-glycoprotein SRMAtlas: a resource of mass spectrometric assays for N-glycosites enabling consistent and multiplexed protein quantification for clinical applications

Protein biomarkers have the potential to transform medicine as they are clinically used to diagnose diseases, stratify patients, and follow disease states. Even though a large number of potential biomarkers have been proposed over the past few years, almost none of them have been implemented so far in the clinic. One of the reasons for this limited success is the lack of technologies to validate proposed biomarker candidates in larger patient cohorts. This limitation could be alleviated by the use of antibody-independent validation methods such as selected reaction monitoring (SRM). Similar to measurements based on affinity reagents, SRM-based targeted mass spectrometry also requires the generation of definitive assays for each targeted analyte. Here, we present a library of SRM assays for 5568 N-glycosites enabling the multiplexed evaluation of clinically relevant N-glycoproteins as biomarker candidates. We demonstrate that this resource can be utilized to select SRM assay sets for cancer-associated N-glycoproteins for their subsequent multiplexed and consistent quantification in 120 human plasma samples. We show that N-glycoproteins spanning 5 orders of magnitude in abundance can be quantified and that previously reported abundance differences in various cancer types can be recapitulated. Together, the established N-glycoprotein SRMAtlas resource facilitates parallel, efficient, consistent, and sensitive evaluation of proposed biomarker candidates in large clinical sample cohorts.

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.

Discriminating experimental Listeria monocytogenes infections in mice using serum profiling

Serum profiling was used to distinguish mice infected with wild-type or mutant Listeria monocytogenes from noninfected control mice. Identifications of significant electrospray ionization mass spectrometry (ESI-MS) sera peak areas between Listeria-infected- and control mice were performed using t tests. ESI-MS cohort peak distributions differed from mice infected with wild-type or ∆actA Listeria versus control mice with p values of 0.00012 and 0.015, respectively. A "% wild-type Listeria peaks identified" assessment tool yielded values of 64 % for wild-type infection, 51 % for ∆actA infection, and 47 % for no infection. Receiver operator characteristic area discriminatory values were 0.97 (wild-type) and 0.82 (∆actA) versus controls. Predictive value measurements revealed overall test sensitivities of 88 % for wild-type infection and 63 % for ∆actA infection. These studies indicate that ESI-MS serum profiling holds promise for diagnosis of infection with intracellular pathogens such as Listeria and indicate that the technology could be useful in understanding the L. monocytogenes infection process.

Serum profiling to distinguish early- and late-stage ovarian cancer patients from disease-free individuals

Sera mass spectrometry (MS) peak differences were analyzed from 35 ovarian cancer patients and 16 disease-free individuals. "Leave one out" cross validation was used to assign "% cancer peaks" in control and ovarian cancer sera samples. Sera MS discriminated stage I/II and stage III/V ovarian cancer patients versus controls with ROC curve area values of 0.82 and 0.92. Test sensitivities for ovarian cancer stage I/II and III/V were 80% and 93% respectively. These results indicate that MS is useful for distinguishing sera from early-stage ovarian cancer patients, and has potential as a test for early detection of this disease.

Distinguishing non-small cell lung adenocarcinoma patients from squamous cell carcinoma patients and control individuals using serum profiling

Goals of this study were to analyze the ability of mass spectrometry serum profiling to distinguish non-small cell lung adenocarcinoma from squamous cell carcinoma patients and healthy controls. Sera were obtained from 19 adenocarcinoma patients, 24 squamous cell carcinoma patients, and 21 controls. Identifications of significant mass-to-charge ratio (m/z) peak differences between these groups were performed using t-tests. A "leave one out" cross-validation procedure yielded discriminatory lung adenocarcinoma versus squamous cell carcinoma p and ROC curve values of <.0001 and 0.92, respectively. Test sensitivity and specificity were 84% and 79%, respectively. This approach could aid in lung cancer diagnosis and sub-typing.

Integrated proteomic profiling of cell line conditioned media and pancreatic juice for the identification of pancreatic cancer biomarkers

Pancreatic cancer is one of the leading causes of cancer-related deaths, for which serological biomarkers are urgently needed. Most discovery-phase studies focus on the use of one biological source for analysis. The present study details the combined mining of pancreatic cancer-related cell line conditioned media and pancreatic juice for identification of putative diagnostic leads. Using strong cation exchange chromatography, followed by LC-MS/MS on an LTQ-Orbitrap mass spectrometer, we extensively characterized the proteomes of conditioned media from six pancreatic cancer cell lines (BxPc3, MIA-PaCa2, PANC1, CAPAN1, CFPAC1, and SU.86.86), the normal human pancreatic ductal epithelial cell line HPDE, and two pools of six pancreatic juice samples from ductal adenocarcinoma patients. All samples were analyzed in triplicate. Between 1261 and 2171 proteins were identified with two or more peptides in each of the cell lines, and an average of 521 proteins were identified in the pancreatic juice pools. In total, 3479 nonredundant proteins were identified with high confidence, of which ∼ 40% were extracellular or cell membrane-bound based on Genome Ontology classifications. Three strategies were employed for identification of candidate biomarkers: (1) examination of differential protein expression between the cancer and normal cell lines using label-free protein quantification, (2) integrative analysis, focusing on the overlap of proteins among the multiple biological fluids, and (3) tissue specificity analysis through mining of publically available databases. Preliminary verification of anterior gradient homolog 2, syncollin, olfactomedin-4, polymeric immunoglobulin receptor, and collagen alpha-1(VI) chain in plasma samples from pancreatic cancer patients and healthy controls using ELISA, showed a significant increase (p < 0.01) of these proteins in plasma from pancreatic cancer patients. The combination of these five proteins showed an improved area under the receiver operating characteristic curve to CA19.9 alone. Further validation of these proteins is warranted, as is the investigation of the remaining group of candidates.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Serum discrimination of early-stage lung cancer patients using electrospray-ionization mass spectrometry

The goal of this study was to evaluate the usefulness of electrospray ionization-mass spectrometry (ESI-MS) technology to distinguish sera of early-stage lung cancer patients from control individuals. ESI-MS m/z (mass divided by charge) data were generated from sera of 43 non-small cell lung cancer patients (pathological stages I and II) and 21 control individuals. Identifications of m/z peak area significances between cancer and control ESI-MS sera spectra were performed using t-tests. A "leave one out" cross validation procedure, which mimics blinded sera analysis and corrects for "over-fitting" of data, yielded discriminatory cancer versus control distribution p value and ROC curve area value of <0.001 and 0.87, respectively. Analysis without the "leave one out" cross validation procedure yielded a ROC curve area of 0.99 for discrimination of sera from lung cancer patients versus control individuals. Predictive value measurements revealed overall test efficiency and sensitivity for distinguishing sera from lung cancer patients from controls (using "leave one out" cross validation) of 80% and 84%, respectively. ESI-MS serum analysis between control individuals and lung cancer patients who smoked or did not smoke had p values in ranges indicating that smoking effects are not pronounced in our analysis. These studies indicate that ESI-MS analyses of sera from early stage non-small cell lung cancer patients were helpful in distinguishing these patients from control individuals.

Application of champedak mannose-binding lectin in the glycoproteomic profiling of serum samples unmasks reduced expression of alpha-2 macroglobulin and complement factor B in patients with nasopharyngeal carcinoma

The use of lectin affinity chromatography prior to 2-DE separation forms an alternative method to unmask the expression of targeted glycoproteins of lower abundance in serum samples. Reduced expression of alpha-2 macroglobulin (AMG) and complement factor B (CFB) was detected in sera of patients with nasopharyngeal carcinoma (NPC) when pooled serum samples of the patients and those of healthy individuals were subjected to affinity isolation using immobilized champedak mannose-binding lectin and analyzed by 2-DE and densitometry. The AMG and CFB spots were not detected in the 2-DE protein profiles when the same pooled serum samples were subjected to albumin and IgG depletion and neither were they detected when the depleted samples were analyzed by western blotting and lectin detection. Together with other acute-phase response proteins that were previously reported to be altered in expression in NPC patients, AMG and CFB may serve as useful complementary biomarkers for NPC.

Pancreatic cancer biomarkers and their implication in cancer diagnosis and epidemiology

Pancreatic cancer is the fourth most common cause of cancer-related mortality in the United States. Biomarkers are needed to detect this cancer early during the disease development and for screening populations to identify those who are at risk. In cancer, “biomarker” refers to a substance or process that is indicative of the presence of cancer in the body. A biomarker might be either a molecule secreted by a tumor or it can be a specific response of the body to the presence of cancer. Genetic, epigenetic, proteomic, glycomic, and imaging biomarkers can be used for cancer diagnosis, prognosis, and epidemiology. A number of potential biomarkers have been identified for pancreatic cancer. These markers can be assayed in non-invasively collected biofluids. These biomarkers need analytical and clinical validation so that they can be used for the purpose of screening and diagnosing pancreatic cancer and determining disease prognosis. In this article, the latest developments in pancreatic cancer biomarkers are discussed.

Aptamer microarray mediated capture and mass spectrometry identification of biomarker in serum samples

Sensitive detection of molecular biomarkers in clinical samples is crucially important in disease diagnostics. This paper reports the development of an aptamer microarray platform combined with sol-gel technology to identify low-abundance targets in complex serum samples. Because of the nanoporous structure of the sol-gel, a high capacity to immobilize the affinity specific aptamers is accomplished which allows binding and detection of target molecules with high sensitivity. The captured protein is digested in situ and the obtained digest was analyzed by ESI-MS without any interference from the affinity probe. TBP (TATA Box Protein) and its specific aptamers were chosen as a model system. A proof of concept with protein concentrations ranging between nanomolar to micromolar is reported, showing a good linearity up to 400 nM when characterized in an aptamer sandwich assay. Moreover, as low as 0.001% of target protein present in total serum proteins could be identified without any pretreatment step using ESI MS/MS mass spectrometry. We believe this novel strategy could become an efficient method for aptamer-based biomarker detection linked directly to mass spectrometry readout.

Systemic molecular and cellular changes induced in rats upon inhalation of JP-8 petroleum fuel vapor

Limited information is available regarding systemic changes in mammals associated with exposures to petroleum/hydrocarbon fuels. In this study, systemic toxicity of JP-8 jet fuel was observed in a rat inhalation model at different JP-8 fuel vapor concentrations (250, 500, or 1000 mg/m(3), for 91 days). Gel electrophoresis and mass spectrometry sequencing identified the alpha-2 microglobulin protein to be elevated in rat kidney in a JP-8 dose-dependent manner. Western blot analysis of kidney and lung tissue extracts revealed JP-8 dependent elevation of inducible heat shock protein 70 (HSP70). Tissue changes were observed histologically (hematoxylin and eosin staining) in liver, kidney, lung, bone marrow, and heart, and more prevalently at medium or high JP-8 vapor phase exposures (500-1000 mg/m(3)) than at low vapor phase exposure (250 mg/m(3)) or non-JP-8 controls. JP-8 fuel-induced liver alterations included dilated sinusoids, cytoplasmic clumping, and fat cell deposition. Changes to the kidneys included reduced numbers of nuclei, and cytoplasmic dumping in the lumen of proximal convoluted tubules. JP-8 dependent lung alterations were edema and dilated alveolar capillaries, which allowed clumping of red blood cells (RBCs). Changes in the bone marrow in response to JP-8 included reduction of fat cells and fat globules, and cellular proliferation (RBCs, white blood cells-WBCs, and megakaryocytes). Heart tissue from JP-8 exposed animals contained increased numbers of inflammatory and fibroblast cells, as well as myofibril scarring. cDNA array analysis of heart tissue revealed a JP-8 dependent increase in atrial natriuretic peptide precursor mRNA and a decrease in voltage-gated potassium (K+) ion channel mRNA.

Discovery of serum biomarkers for pancreatic adenocarcinoma using proteomic analysis

BACKGROUND AND AIMS

The serum/plasma proteome was explored for biomarkers to improve the diagnostic ability of CA19-9 in pancreatic adenocarcinoma (PC).

METHODS

A Training Set of serum samples from 20 resectable and 18 stage IV PC patients, 54 disease controls (DCs) and 68 healthy volunteers (HVs) were analysed by surface-enhanced laser desorption and ionisation time-of-flight mass spectrometry (SELDI-TOF MS). The resulting protein panel was validated on 40 resectable PC, 21 DC and 19 HV plasma samples (Validation-1 Set) and further by ELISA on 33 resectable PC, 28 DC and 18 HV serum samples (Validation-2 Set). Diagnostic panels were derived using binary logistic regression incorporating internal cross-validation followed by receiver operating characteristic (ROC) analysis.

RESULTS

A seven-protein panel from the training set PC vs DC and from PC vs HV samples gave the ROC area under the curve (AUC) of 0.90 and 0.90 compared with 0.87 and 0.91 for CA19-9. The AUC was greater (0.97 and 0.99, P<0.05) when CA19-9 was added to the panels and confirmed on the validation-1 samples. A simplified panel of apolipoprotein C-I (ApoC-I), apolipoprotein A-II (ApoA-II) and CA19-9 was tested on the validation-2 set by ELISA, in which the ROC AUC was greater than that of CA19-9 alone for PC vs DC (0.90 vs 0.84) and for PC vs HV (0.96 vs 0.90).

CONCLUSIONS

A simplified diagnostic panel of CA19-9, ApoC-I and ApoA-II improves the diagnostic ability of CA19-9 alone and may have clinical utility.

Implications of cancer-associated systemic inflammation for biomarker studies

Highly sensitive molecular technologies provide new capacities for cancer biomarker research, but with sensitivity improvements marker specificity is significantly decreased, and too many false-positive results should disqualify the measurement from clinical use. Hence, of the thousands of potential cancer biomarkers only a few have found their way to clinical application. Differentiating false-positive results from true-positive (cancer-specific) results can indeed be difficult, if validation of a marker is performed against inadequate controls. We present examples of accumulating evidence that not only local but also systemic inflammatory reactions are implicated in cancer development and progression and interfere with the molecular image of cancer disease. We analyze several modern strategies of tumor marker discovery, namely, proteomics, metabonomics, studies on circulating tumor cells and circulating free nucleic acids, or their methylation degree, and provide examples of scarce, methodologically correct biomarker studies as opposed to numerous methodologically flawed biomarker studies, that examine cancer patients' samples against those of healthy, inflammation-free persons and present many inflammation-related biomarker alterations in cancer patients as cancer-specific. Inflammation as a cancer-associated condition should always be considered in cancer biomarker studies, and biomarkers should be validated against their expression in inflammatory conditions.

Integrative proteomic analysis of serum and peritoneal fluids helps identify proteins that are up-regulated in serum of women with ovarian cancer

BACKGROUND

We used intensive modern proteomics approaches to identify predictive proteins in ovary cancer. We identify up-regulated proteins in both serum and peritoneal fluid. To evaluate the overall performance of the approach we track the behavior of 20 validated markers across these experiments.

METHODOLOGY

Mass spectrometry based quantitative proteomics following extensive protein fractionation was used to compare serum of women with serous ovarian cancer to healthy women and women with benign ovarian tumors. Quantitation was achieved by isotopically labeling cysteine amino acids. Label-free mass spectrometry was used to compare peritoneal fluid taken from women with serous ovarian cancer and those with benign tumors. All data were integrated and annotated based on whether the proteins have been previously validated using antibody-based assays.

FINDINGS

We selected 54 quantified serum proteins and 358 peritoneal fluid proteins whose case-control differences exceeded a predefined threshold. Seventeen proteins were quantified in both materials and 14 are extracellular. Of 19 validated markers that were identified all were found in cancer peritoneal fluid and a subset of 7 were quantified in serum, with one of these proteins, IGFBP1, newly validated here.

CONCLUSION

Proteome profiling applied to symptomatic ovarian cancer cases identifies a large number of up-regulated serum proteins, many of which are or have been confirmed by immunoassays. The number of currently known validated markers is highest in peritoneal fluid, but they make up a higher percentage of the proteins observed in both serum and peritoneal fluid, suggesting that the 10 additional markers in this group may be high quality candidates.

Soluble iC3b as an early marker for pancreatic adenocarcinoma is superior to CA19.9 and radiology

Pancreatic adenocarcinoma as an aggressive tumor still lacks specific markers. Resection offers the only potential cure, and earlier diagnosis could benefit many patients. Here, we analyzed siC3b as a potential diagnostic marker. Soluble iC3b is generated in the fluid phase after binding of autoantibodies to tumor cells and subsequent inactivation of the complement cascade by interaction with complement regulatory proteins. Two hundred thirty-two plasma samples from patients with adjuvant treatment after resection, from healthy volunteers, and from vulnerable patients were collected prospectively and analyzed for siC3b. Every 3 months, the patients underwent imaging and the results from siC3b enzyme-linked immunosorbent assay were categorized according to radiologically defined recurrence within 4 months after blood withdrawal. Furthermore, the regulatory factors of the complement system were analyzed in tumor cells and in urine. The most important finding was that up to 4 months before radiologically defined recurrence, siC3b plasma level is increased with a sensitivity and specificity resulting in an area under the curve of 0.85, which could be further increased by combining it with CA19.9 (area under the curve=0.92). Complement regulatory proteins are highly expressed in pancreatic carcinoma cells and detectable in the patient's urine. In summary, screening for siC3b in patients with an increased risk for pancreatic ductal adenocarcinoma (patients with chronic pancreatitis, hereditary pancreatitis, after curative resection, and patients with a variety of familial cancer syndromes) allows for early detection with high sensitivity, as siC3b plasma levels are increased up to 4 months before radiologic evidence. Sensitivity could be further increased by combining this approach with CA19.9.

Identification and confirmation of biomarkers using an integrated platform for quantitative analysis of glycoproteins and their glycosylations

Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver. However, accurate diagnosis can be difficult as most of the patients who develop this tumor have symptoms similar to those caused by longstanding liver disease. Herein we developed an integrated platform to discover the glycoprotein biomarkers in early HCC. At first, lectin arrays were applied to investigate the differences in glycan structures on serum glycoproteins from HCC and cirrhosis patients. The intensity for AAL and LCA was significantly higher in HCC, indicating an elevation of fucosylation level. Then serum from 10 HCC samples and 10 cirrhosis samples were used to screen the altered fucosylated proteins by a combination of Exactag labeling, lectin extraction and LC-MS/MS. Finally, 27 HCC and 27 cirrhosis serum samples were used for lectin-antibody arrays to confirm the change of these fucosylated proteins. C3, CE, HRG, CD14 and HGF were found to be biomarker candidates for distinguishing early HCC from cirrhosis, with a sensitivity of 72% and specificity of 79%. Our work gives insight to the detection of early HCC, and the application of this comprehensive strategy has the potential to facilitate biomarker discovery on a large scale.

Markers of inflammation

Inflammation is a complex and necessary component of an organism's response to biological, chemical or physical stimuli. In the acute phase, cells of the immune system migrate to the site of injury in a carefully orchestrated sequence of events that is mediated by cytokines and acute phase proteins. Depending upon the degree of injury, this acute phase may be sufficient to resolve the damage and initiate healing. Persistent inflammation as a result of prolonged exposure to stimulus or an inappropriate reaction to self molecules can lead to the chronic phase, in which tissue damage and fibrosis can occur. Chronic inflammation is reported to contribute to numerous diseases including allergy, arthritis, asthma, atherosclerosis, autoimmune diseases, diabetes, and cancer, and to conditions of aging. Hematology and clinical chemistry data from standard toxicology studies can provide an initial indication of the presence and sometimes location of inflammation in the absence of specific data on the immune tissues. These data may suggest more specific immune function assays are necessary to determine the existence or mechanism(s) of -immunomodulation. Although changes in hematology dynamics, acute phase proteins, complement factors and cytokines are common to virtually all inflammatory conditions and can be measured by a variety of techniques, individual biomarkers have yet to be strongly associated with specific pathologic events. The specific profile in a given inflammatory condition is dependent upon species, mechanisms, severity, chronicity, and capacity of the immune system to respond and adapt.

Precipitation and selective extraction of human serum endogenous peptides with analysis by quadrupole time-of-flight mass spectrometry reveals posttranslational modifications and low-abundance peptides

The endogenous peptides of human serum may have regulatory functions, have been associated with physiological states, and their modifications may reveal some mechanisms of disease. In order to correlate levels of specific peptides with disease alongside internal standards, the polypeptides must first be reliably extracted and identified. Endogenous blood peptides can be effectively enriched by precipitation of the serum with organic solvents followed by selective extraction of peptides using aqueous solutions modified with organic solvents. Polypeptides on filter paper were assayed with Coomasie brilliant blue binding. The polypeptides were resolved by detergent tricine polyacrylamide electrophoresis and visualized by diamine silver staining. Peptides in the extracts were collected by C18 and analyzed by matrix-assisted laser desorption/ionization and liquid chromatography-electrospray ionization-tandem mass spectrometry (MS/MS) quadrupole time-of-flight MS/MS. Peptides were resolved as multiple isotopic peaks in MS mode with mass deviation of 0.1 Da or less and similar accuracy for fragments. The sensitivity of MS and MS/MS analysis was estimated to be in the picomolar range or less. The peptide composition of the extracts was dependent on solvent formulation. Multiple peptides from apolipoproteins, complement proteins, coagulation factors, and many others were identified by X!Tandem with high mass accuracy of peptide ions and fragments from collision-induced dissociation. Many previously unreported posttranslational modifications of peptides including phosphorylations, oxidations, glycosylations, and others were detected with high mass accuracy and may be of clinical importance. About 4,630 redundant peptides were identified with 99% confidence separately, and together some 1,251 distinct proteins were identified with 99% confidence or greater using the Paragon algorithm.