Comparative profiling of plasma proteome from breast cancer patients reveals thrombospondin-1 and BRWD3 as serological biomarkers

Breast cancer is the most common cancer in women worldwide. It is necessary to identify biomarkers for early detection, to make accurate prognoses, and to monitor for any recurrence of the cancer. In order to identify potential breast cancer biomarkers, we analyzed the plasma samples of women diagnosed with breast cancer and age-matched normal healthy women by mTRAQ-based stable isotope-labeling mass spectrometry. We identified and quantified 204 proteins including thrombospondin-1 (THBS1) and bromodomain and WD repeat-containing protein 3 (BRWD3) which were increased by more than 5-fold in breast cancer plasma. The plasma levels of the two proteins were evaluated by Western blot assay to confirm for their diagnostic value as serum markers. A 1.8-fold increase in BRWD3 was observed while comparing the plasma levels of breast cancer patients (n = 54) with age-matched normal healthy controls (n = 30), and the area under the receiver operating characteristic curve (AUC) was 0.917. THBS1 was detected in pooled breast cancer plasma at the ratio similar to mTRAQ ratio (> 5-fold). The AUC value for THBS1 was 0.875. The increase of THBS1 was more prominent in estrogen receptor negative and progesterone receptor negative patients than receptor-positive patients. Our results are evidence of the diagnostic value of THBS1 in detecting breast cancer. Based on our findings, we suggest a proteomic method for protein identification and quantification lead to effective biomarker discovery.     

Comprehensive mass spectrometry based metabolic profiling of blood plasma reveals potent discriminatory classifiers of pancreatic cancer

Poor outcome of pancreatic cancer necessitates development of an early diagnostic method to reduce mortality. No reliable early diagnostic test for pancreatic cancer detection has been developed and validated to date. In the current study, metabolic profiling of plasma samples from selected cancer patients and noncancerous controls was performed to seek novel metabolic biomarkers of pancreatic cancer. A comprehensive mass spectrometry based analytical platform established at the Metabolomics Core of the UC Davis Genome Center allowed detection of multiple compounds previously unreported in plasma from pancreatic cancer patients. It was found that selective amino acids, bile acids, and polar lipids were detected with increased or decreased levels in pancreatic cancer samples compared to controls. These findings on blood plasma levels of the relevant metabolites might be very useful clinical parameters for early diagnosis of pancreatic cancer. Copyright © 2010 John Wiley & Sons, Ltd.     

Comprehensive native glycan profiling with isomer separation and quantitation for the discovery of cancer biomarkers

Glycosylation is highly sensitive to the biochemical environment and has been implicated in many diseases including cancer. Glycan compositional profiling of human serum with mass spectrometry has already identified potential biomarkers for several types of cancer and diseases; however, composition alone does not fully describe glycan stereo- and regioisomeric diversity. The vast structural heterogeneity of glycans presents a formidable analytical challenge. We have developed a method to identify and quantify isomeric native glycans using nanoflow liquid chromatography (nano-LC)/mass spectrometry. A microfluidic chip packed with graphitized carbon was used to chromatographically separate the glycans. To determine the utility of this method for structure-specific biomarker discovery, we analyzed serum samples from two groups of prostate cancer patients with different prognoses. More than 300 N-glycan species (including isomeric structures) were identified, corresponding to over 100 N-glycan compositions. Statistical tests established significant differences in glycan abundances between patient groups. This method provides comprehensive, selective, and quantitative glycan profiling.     

Lipidomic profiling of plasma in patients with chronic hepatitis C infection

Chronic hepatitis C virus (HCV) infection is a global health issue. Although its progression is reported to be closely associated with lipids, the way in which the plasma lipidome changes during the development of chronic HCV infection in humans is currently unknown. Using an improved quantitative high-throughput lipidomic platform, we profiled 284 lipids in human plasma samples obtained from healthy controls (n?=?11) and patients with chronic HCV infection (n?=?113). The intrahepatic inflammation grade (IG) of liver tissue was determined by biopsy. Two types of mass spectrometers were integrated into a single lipidomic platform with a wide dynamic range. Compared with previous methods, the performance of this method was significantly improved in terms of both the number of target sphingolipids identified and the specificity of the high-resolution mass spectrometer. As a result, 44 sphingolipids, one diacylglycerol, 43 triglycerides, 24 glycerophosphocholines, and 5 glycerophospho-ethanolamines were successfully identified and quantified. The lipid profiles of individuals with chronic HCV infection were significantly different from those of healthy individuals. Several lipids showed significant differences between mild and severe intrahepatic inflammation grades, indicating that they could be utilized as novel noninvasive indicators of intrahepatic IG. Using multivariate analysis, healthy controls could be discriminated from HCV patients based on their plasma lipidome; however, patients with different IGs were not well discriminated. Based on these results, we speculate that variations in lipid composition arise as a result of HCV infection, and are caused by HCV-related digestive system disorders rather than progression of the disease.

Discovery of lung squamous carcinoma biomarkers by profiling the plasma peptide with LC/MS/MS

Biomarkers can be used for the screening and clinical diagnosis of cancer, and peptidomics approach has been proven successful in the research of biomarkers. To develop better peptidomic technologies for fast, accurate, and reliable detection of peptides biomarkers for lung cancer, we have improved the procedures of blood collection to minimize the degradation of the blood proteins and optimize the extraction of peptidome peptides from plasma samples based on acetonitrile precipitation associated with size exclusion chromatography (SEC). Studies show that squamous cell carcinomas are found to express CAGE1, SPAT9 and TEX28 genes at significantly higher rates, and the results suggest that as tumors progress, the level of CAGE1, SPAT9 and TEX28 genes are likely to increase and lead to immunization. This suggests a potentially important therapeutic method for cancer testis-based cancer vaccines.     

Alpha 1-antitrypsin: a novel tumor-associated antigen identified in patients with early-stage breast cancer

Several studies have demonstrated that sera from patients with cancer contain antibodies that recognize a unique group of autologous antigens called tumor-associated antigens (TAA). In the current study, we employed an immunoproteomic approach, combining 2DE, Western blot, and MALDI-MS to identify TAA in the sera of patients diagnosed with infiltrating ductal or in situ carcinoma breast cancer. Sera obtained from 25 newly diagnosed patients with stage II breast cancer and 20 healthy volunteers was evaluated for the presence of novel TAA. Alpha 1-antitrypsin (A1AT) antibodies were detected in 24 of 25 patients with breast cancer (96%) and in 2 of 20 controls (10%). Sensitivity of detection of autoantibodies against A1AT in patients with breast cancer was 96%. Our preliminary results suggest that A1AT and autoantibodies against alpha 1 antitrypsin may be useful serum biomarkers for early-stage breast cancer screening and diagnosis.     

Stable isotopic labelling-assisted untargeted metabolic profiling reveals novel conjugates of the mycotoxin deoxynivalenol in wheat

An untargeted screening strategy for the detection of biotransformation products of xenobiotics using stable isotopic labelling (SIL) and liquid chromatography–high resolution mass spectrometry (LC-HRMS) is reported. The organism of interest is treated with a mixture of labelled and non-labelled precursor and samples are analysed by LC-HRMS. Raw data are processed with the recently developed MetExtract software for the automated extraction of corresponding peak pairs. The SIL-assisted approach is exemplified by the metabolisation of the Fusarium mycotoxin deoxynivalenol (DON) in planta. Flowering ears were inoculated with 100 μg of a 1?+?1 (v/v) mixture of non-labelled and fully labelled DON. Subsequent sample preparation, LC-HRMS measurements and data processing revealed a total of 57 corresponding peak pairs, which originated from ten metabolites. Besides the known DON and DON-3-glucoside, which were confirmed by measurement of authentic standards, eight further DON-biotransformation products were found by the untargeted screening approach. Based on a mass deviation of less than ±5 ppm and MS/MS measurements, one of these products was annotated as DON-glutathione (GSH) conjugate, which is described here for the first time for wheat. Our data further suggest that two DON-GSH-related metabolites, the processing products DON-S-cysteine and DON-S-cysteinyl-glycine and five unknown DON conjugates were formed in planta. Future MS/MS measurements shall reveal the molecular structures of the detected conjugates in more detail.     

Aberrant expression of acute-phase reactant proteins in sera and breast lesions of patients with malignant and benign breast tumors

We have analyzed unfractionated sera of newly diagnosed patients (n=10) with breast carcinoma (BC), prior to treatment, and patients (n=5) with fibrocystic disease of the breast (FDB) by two-dimensional gel electrophoresis (2-DE) and silver staining. The patients' 2-DE serum protein profiles obtained were then subjected to image analysis and compared to similar data generated from sera of normal healthy female controls (n=10) of the same range of age. The relative expression of alpha1-antichymotrypsin (ACT), clusterin, and complement factor B was significantly higher in all BC patients as compared to normal controls. However, the expression of alpha1-antitrypsin (AAT) in BC patients was apparently lower than that of the controls. Similar differential expression of ACT was detected in the FDB patients. The aberrant expression of the serum acute-phase proteins of patients with BC and FDB was confirmed by competitive enzyme-linked immunosorbent assay (ELISA). Similar altered proteins expression was also observed from immunohistochemical studies of malignant (n=5) and benign (n=5) breast lesions of the respective patients performed using antisera to the aberrantly expressed proteins. However, the malignant breast lesions were instead positively stained for AAT. The differential expression of the serum proteins was apparently abrogated when a six-month follow-up study was performed on nine of the BC patients subsequent to treatment.     

Serological proteome analysis of dogs with breast cancer unveils common serum biomarkers with human counterparts

Canine mammary tumor is being touted as a model for investigating the human breast cancer. Breast cancer of the both species has similar biological behavior, histopathologic characteristics, and metastatic pattern. In this study, we used the serological proteome analysis to detect autoantigens that elicit a humoral response in dogs with mammary tumor in order to identify serum biomarkers with potential usefulness as diagnostic markers and to better understand molecular mechanisms underlying canine breast cancer development. Protein extract from a cell line was subject to 2DE followed by Western blotting using sera from 15 dogs with mammary tumor and sera from 15 healthy control dogs. Immunoreactive autoantigens were subsequently identified by the MALDI‐TOF MS. Four autoantigens, including manganese‐superoxide dismutase, triose phosphate isomerase, alpha‐enolase, and phosphoglycerate mutase1, with significantly higher immunoreactivity in the tumor samples than in the normal samples were identified as biomarker candidates. Immunohistochemistry and Western blotting revealed higher expression of these biomarkers in the malignant tumors than in the normal or benign tumors. The autoantigens found in this study have been reported to elicit autoantibody response in the human breast cancer, indicating the similarity of breast cancer proteome profile in dogs with that in human beings.     

Nondigest liberation of biomarkers from plasma: a novel two-stage ultrafiltration approach

A simple procedure for sample preparation of human plasma by two stages of ultrafiltration using one device is described. Our approach is useful for nondigest liberation of biomarkers bound to albumin and other plasma proteins. The analyte contained in the ultrafiltrate can be directly analyzed without additional sample preparation, and quantified by 2-D RP-RP LC/MS.     

Metabolomic profiling of human plasma in pancreatic cancer using pressurized capillary electrochromatography

The application of pressurized capillary electrochromatography (pCEC) coupled with ultra violet (UV) detection has been investigated for the production of global metabolite profiles from human plasma, and its capabilities of classifying pancreatic cancer patients. The pCEC separation of plasma samples was performed on a RP column with gradient elution. The applied voltage, detection wavelength and type of acid modifiers on separation of plasma samples were optimized with pooled quality control (QC) sample. The stability and the repeatability of the methodology were also determined by the repeat analysis of QC sample. The effects of different scaling methods on the results of orthogonal partial least-squares discrimination analysis (OPLS-DA) based on pCEC-UV data set were also investigated. The results of the current study clearly showed the different phenotypes of metabolites of pancreatic cancer patients and healthy controls based on pCEC-UV plasma profiles. OPLS-DA data are shown to provide a valuable means of convenient classification. This work indicated that pCEC-UV method can be used as a cost-effective and information-rich, while relatively simple and inexpensive approach for plasma profiling on disease metabolomics studies.     

Influence of oxidative injury and monitoring of blood plasma by DSC on breast cancer patients

Damage caused by oxidative stress is involved in many types of diseases, including breast cancer. Our aim was to detect the oxidative stress parameters and blood plasma changes with differential scanning calorimetry (DSC) in breast cancer patients. The study included 40 adult breast cancer women who were grouped according to tumor diameter, regional lymph node metastases, proliferative activity, receptor status and postoperative chemotherapy. To monitor oxidative stress, malondialdehyde, oxygen free radicals (OFRs), activity of myeloperoxidase (MPO), superoxide dismutase (SOD) and catalase (CAT) were measured. Denaturation of plasma components was detected in Setaram Micro DSC-II calorimeter. The total production of OFRs, the MPO activity and lipidperoxidation were significantly increased in each breast cancer patients considering the tumor size, the metastatic lymph nodes, the proliferation activity and receptor status compared with healthy controls (p < 0.05). These pro-oxidants were slightly elevated without chemotherapy, but their values were increased significantly in chemotherapy-receiving group. The activity of SOD and CAT was significantly decreased in all groups, and in regard to the chemotherapy, they were changed significantly parallel to the severity of disease. Regarding to both the increased tumor diameter and the increased number of affected lymph nodes, DSC measurements showed a strong relationship between the maximum excess heat capacity (C_pmax) of the blood plasma and the severity of disease. The study demonstrated that oxidative stress is implicated in breast carcinoma and chemotherapy aggravates these changes which confirmed the plasma DSC measurements also.     

A multiplexed bead assay for profiling glycosylation patterns on serum protein biomarkers of pancreatic cancer

A multiplexed bead-based immunoassay was developed to simultaneously profile glycosylation patterns of serum proteins to investigate their usefulness as biomarkers for pancreatic cancer. The multiplex assay utilized protein-specific capture antibodies chemically coupled individually to beads labeled with specific amounts of fluorescent dye. Captured proteins were detected based on the extent and specific type of glycosylation as determined by successive binding of fluorescent lectin probes. Advantages to this technique include the fact that antibodies coupled to the beads had minimal nonspecific binding to the lectins ConA/SNA, avoiding the step of chemically blocking the antibody glycans and the bead assays were performed in a 96-well filter plate enabling high-throughput screening applications with improved reproducibility. The assay was tested with ConA and SNA lectins to examine the glycosylation patterns of α-1-β glycoprotein (A1BG) and serum amyloid p (SAP) component for use as potential biomarkers for the detection of pancreatic cancer based on the results from prior biomarker studies. The results showed that the SNA response on the captured A1BG protein could distinguish chronic pancreatitis samples from pancreatic cancer with a p-value of 0.035 and for the SAP protein with SNA, a p-value of 0.026 was found between the signal of normal controls and the pancreatic cancer samples. For the ConA response, a decline in the signal for both proteins in the serum samples was found to distinguish pancreatic cancer from normal controls and renal cell carnoma samples (A1BG, p<0.05; and SAP, p<0.0001).     

An enzyme that regulates ether lipid signaling pathways in cancer annotated by multidimensional profiling

Hundreds, if not thousands, of uncharacterized enzymes currently populate the human proteome. Assembly of these proteins into the metabolic and signaling pathways that govern cell physiology and pathology constitutes a grand experimental challenge. Here, we address this problem by using a multidimensional profiling strategy that combines activity-based proteomics and metabolomics. This approach determined that KIAA1363, an uncharacterized enzyme highly elevated in aggressive cancer cells, serves as a central node in an ether lipid signaling network that bridges platelet-activating factor and lysophosphatidic acid. Biochemical studies confirmed that KIAA1363 regulates this pathway by hydrolyzing the metabolic intermediate 2-acetyl monoalkylglycerol. Inactivation of KIAA1363 disrupted ether lipid metabolism in cancer cells and impaired cell migration and tumor growth in vivo. The integrated molecular profiling method described herein should facilitate the functional annotation of metabolic enzymes in any living system.     

Screening for biomarkers in plasma from patients with gangrenous and phlegmonous appendicitis using CE and CEC in combination with MS

Today a high degree of "false" appendicitis diagnoses are occurring. In this study, a screening experiment of biomarkers of two different kinds of appendicitis, gangrenous and phlegmonous, were conducted with CE and CEC coupled to MS. Plasma samples were obtained from patients pre- and post-surgery. A large amount of data was generated to be able to compare them, and chemometrics tools were utilized to visualize the differences. Indicative patterns were found for both pre- and post-surgery of the two types of inflammation as well as between them. The divergences were traced back to the MS peaks obtained in the CE- and CEC-MS setups as possible biomarkers for the two forms of appendicitis.