Top-Down Proteomics of Human Saliva, Analyzed with Logistic Regression and Machine Learning Methods, Reveal Molecular Signatures of Ovarian Cancer.

Ovarian cancer (OC) is the most lethal of all gynecological cancers. Due to vague symptoms, OC is mostly detected at advanced stages, with a 5-year survival rate (SR) of only 30%; diagnosis at stage I increases the 5-year SR to 90%, suggesting that early diagnosis is essential to cure OC. Currently, the clinical need for an early, reliable diagnostic test for OC screening remains unmet; indeed, screening is not even recommended for healthy women with no familial history of OC for fear of post-screening adverse events. Salivary diagnostics is considered a major resource for diagnostics of the future. In this work, we searched for OC biomarkers (BMs) by comparing saliva samples of patients with various stages of OC, breast cancer (BC) patients, and healthy subjects using an unbiased, high-throughput proteomics approach. We analyzed the results using both logistic regression (LR) and machine learning (ML) for pattern analysis and variable selection to highlight molecular signatures for OC and BC diagnosis and possibly re-classification. Here, we show that saliva is an informative test fluid for an unbiased proteomic search of candidate BMs for identifying OC patients. Although we were not able to fully exploit the potential of ML methods due to the small sample size of our study, LR and ML provided patterns of candidate BMs that are now available for further validation analysis in the relevant population and for biochemical identification.

Profiling of differentially expressed proteins between fresh and frozen-thawed Duroc boar semen using ProteinChip CM10.

Many studies have been conducted to improve technology for semen cryopreservation in pigs. However, computer-assisted analysis of sperm motility and morphology is insufficient to predict the molecular function of frozen-thawed semen. More accurate expression patterns of boar sperm proteins may be derived using the isobaric tags for relative and absolute quantification (iTRAQ) technique. In this study, the iTRAQ-labeling system was coupled with liquid chromatography tandem-mass spectrometry (LC-MS/MS) analysis to identify differentially expressed CM10-fractionated proteins between fresh and frozen-thawed boar semen. A total of 76 protein types were identified to be differentially expressed, among which 9 and 67 proteins showed higher and lower expression in frozen-thawed than in fresh sperm samples, respectively. The classified functions of these proteins included oxidative phosphorylation, mitochondrial inner membrane and matrix, and pyruvate metabolic processes, which are involved in adenosine triphosphate (ATP) synthesis; and sperm flagellum and motile cilium, which are involved in sperm tail structure. These results suggest a possible network of biomarkers associated with survival after the cryopreservation of Duroc boar semen.

Selymatra: A web application for protein-profiling analysis of mass spectra.

Surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry is a variant of the matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. It is used in many cases especially for the analysis of protein profiling and for preliminary screening of biomarkers in complex samples. Unfortunately, these analyses are time consuming and protein identification is generally strictly limited. SELDI-TOF analysis of mass spectra (SELYMATRA) is a web application (WA) developed to reduce these limitations by (i) automating the identification processes and (ii) introducing the possibility to predict proteins in complex mixtures from cells and tissues. The WA architectural pattern is the model-view-controller, commonly used in software development. The WA compares the mass value between two mass spectra (sample vs. control) to extract differences, and, according to the set parameters, it queries a local database to predict most likely proteins based on their masses and different expression amplification. The WA was validated in a cellular model overexpressing a tagged NURR1 receptor, being able to recognize the tagged protein in the profiling of transformed cells. A help page, including a description of parameters for WA use, is available on the website.

Screening of serum protein biomarkers in hemorrhagic cerebral infarction by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology.

BACKGROUND: Serum samples of patients with hemorrhagic cerebral infarction (HCI), cerebral infarction (CI), and healthy controls (HCs) were used to screen statistically different protein peaks as potential biomarkers and to establish a decision tree classification model. METHODS: The serum samples from clinically confirmed patients with HCI and CI from November 2018 to October 2019 were collected, along with those of HCs who visited our hospital during the same period. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) with CM10 ProteinChip was used to analyze the differences in serum protein expression profiles of 30 patients with HCI, 32 patients with CI, and 31 HCs in the training group, and a decision tree classification model was established. At the same time, the blind test group (18 patients with HCI, 21 patients with CI, and 17 HCs) was tested by a blind method. RESULTS: Model 1 was successfully established by software analysis with a mass-to-charge ratio of 3,495.2, 8,941.0, and 15,890.4 as a differential protein peak. The sensitivity, specificity, and accuracy of model 1 in distinguishing HCI from HCs were 86.8%, 87.1%, and 86.9%, respectively. After verification of model 1 by the blind test group, the results showed that the sensitivity, specificity, and accuracy were 88.9%, 94.1%, and 91.4%, respectively. The sensitivity, specificity, and accuracy of model 2 with a mass-to-charge ratio of 2,941.3 as a differential protein peak were 86.7%, 75.0%, and 80.6%, respectively. After verification of model 2 by the blind test group, the results showed that the sensitivity, specificity, and accuracy were 83.3%, 90.4%, and 87.2%, respectively. CONCLUSIONS: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and CM10 ProteinChip can be used to screen serum protein markers in patients with HCI. Mass-to-charge ratio of 3,495.2, 8,941.0, 15,890.4, and 2,941.3 may be potential protein biomarkers of HCI and used to distinguish HCI patients from HCs and CI.

Serum protein expression patterns in detecting a new viral protein in HBeAg-negative chronic hepatitis B.

We analysed the changes in viral protein expression in HBeAg-negative chronic hepatitis B (CHB). In total, 160 samples were obtained from individuals infected by hepatitis B virus (HBV) and divided into four groups. Group A included 71 cases of hepatitis B e antigen (HBeAg)-negative CHB, Group B included 58 cases of inactive seroconverters and Group C included 31 cases of HBeAg-positive CHB. Group D included 22 normal healthy individuals as a control. All serum samples were examined using surface enhance laser desorption/ionization time of flight-mass spectrometry (SELDI-TOF-MS). The results indicated that a peak with 4140 m/z increased markedly in Group A at 1295.55 ± 745.87, which was significantly different from that in Group B at 896.99 ± 534.86 (P = 0.013). This peak indicated a close relationship with HBV DNA replication and may contribute to pathogenesis of HBeAg-negative chronic hepatitis.

Identification of diagnostic upper gastrointestinal cancer tissue type-specific urinary biomarkers.

Several potential urinary biomarkers exhibiting an association with upper gastrointestinal tumour growth have been previously identified, of which S100A6, S100A9, rabenosyn-5 and programmed cell death 6-interacting protein (PDCD6IP) were further validated and found to be upregulated in malignant tumours. The cancer cohort from our previous study was subclassified to assess whether distinct molecular markers can be identified for each individual cancer type using a similar approach. Urine samples from patients with cancers of the stomach, oesophagus, oesophagogastric junction or pancreas were analysed by surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry using both CM10 and IMAC30 (Cu2+-complexed) chip types and LC-MS/MS-based mass spectrometry after chromatographic enrichment. This was followed by protein identification, pattern matching and validation by western blotting. We found 8 m/z peaks with statistical significance for the four cancer types investigated, of which m/z 2447 and 2577 were identified by pattern matching as fragments of cathepsin-B (CTSB) and cystatin-B (CSTB); both molecules are indicative of pancreatic cancer. Additionally, we observed a potential association of upregulated α-1-antichymotrypsin with pancreatic and gastric cancers, of PDCD6IP, vitelline membrane outer layer protein 1 homolog (VMO1) and triosephosphate isomerase (TPI1) with oesophagogastric junctional cancers, and of complement C4-A, prostatic acid phosphatase, azurocidin and histone-H1 with oesophageal cancer. Furthermore, the potential pancreatic cancer biomarkers CSTB and CTSB were validated independently by western blotting. Therefore, the present study identified two new potential urinary biomarkers that appear to be associated with pancreatic cancer. This may provide a simple, non-invasive screening test for use in the clinical setting.

SELDI-TOF MS Analysis of Hepatocellular Carcinoma in an Australian Cohort.

BACKGROUND: Hepatocellular carcinoma (HCC) is a common cause of cancer death worldwide. Resection offers the best chance of long-term survival, but a consistent adverse prognostic factor is the presence of microvascular invasion (MVI). In this study, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), a high throughput method of analyzing complex samples, was used to explore differentially expressed proteins between HCC and adjacent nontumour liver tissue (ANLT). These findings were correlated with clinical outcomes. MATERIALS AND METHODS: From 2002 to 2011, tumor and ANLT were collected from patients who underwent liver resection and these samples were later prepared for SELDI-TOF MS. Output data were then used to identify proteins capable of discriminating HCC from ANLT. Proteins from the multivariate analysis were then analyzed to determine prognostic factors and the m/z ratios of these proteins were entered into the ExPASy database to infer potential candidates. RESULTS: During the study period, 30 patients had SELDI-TOF MS performed on their HCC and ANLT samples. On multivariate analysis, a panel of four proteins-m/z 5840, m/z 8921, m/z 9961, and m/z 25,872-discriminated HCC from ANLT with an area under the ROC curve of 0.954 (P < 0.001). On prognostic factor assessment, decreased m/z 9961 was significantly associated with the presence of MVI (P = 0.025) and shorter disease-free survival (P = 0.045) in our patients. A potential candidate for this protein was coxsackievirus and adenovirus receptor, isoform 3 (CAR 3/7), which helps maintain tight junction integrity. CONCLUSIONS: Using SELDI TOF-MS, we identified a panel of four proteins with excellent discriminative capacity between HCC and ANLT. Of these, m/z 9961 was the only protein significantly associated with a known poor prognostic factor (presence of MVI) and survival (shorter disease-free survival). While loss of CAR 3/7 could lead to MVI, further research is warranted to validate the identity of protein m/z 9961.

Urinary diagnostic proteomic markers for dynapenia in cancer patients.

Dynapenia is defined as the age-related loss of muscle strength, and plays a significant role in the loss of physical function and increased risk of disability among older individuals. The need for an early diagnosis supports the search for a biomarker that reflects muscle 'weakening'. This has previously proven difficult due to patient heterogeneity at presentation and lack of understanding of the underlying molecular mechanisms. The aim of the present study was to identify potential urinary biomarkers of dynapenia in patients undergoing potentially curative surgery for upper gastrointestinal cancer. Maximum isometric knee extensor strength (strain gauge) and maximum leg extensor power (Nottingham power rig) measurements were taken. Cut-off values for dynapenia were based on the Allied Dunbar national fitness survey. Values below the 5th percentile for the population matched for age and sex on the Allied Dunbar national fitness survey were used to stratify the cohort into dynapenic or normal. Urine samples taken at induction of anaesthesia were analysed by SELDI-TOF mass spectrometry using CM10 and IMAC30 chip-types to establish statistically significant m/z peak fingerprint patterns, followed by in-gel LC-MS/MS to identify molecular constituents. Statistical analysis of decision-tree calculations using Biomarker Pattern software resulted in models with sensitivities of 86 and 96%, specificities of 81 and 89%, and overall correctness of 84 and 93%, when applied to the entire cohort for power and strength measurement-based stratifications using the IMAC30 chip-type and the CM10 chip-type, respectively. The molecular identities of 10 peaks of interest were further investigated. After subtraction of potentially unrelated proteins, they were identified as fragments of Annexin A1, collagen α-1 (XV), perlecan and myotrophin. These results demonstrate that urinary screening can be used to define cancer-associated muscle weakness, and the identification of potential biomarkers could be invaluable in establishing a rapid test to measure and assess dynapenia in the clinical setting.

Proteomic identification of potential markers of myosteatosis in human urine.

Myosteatosis, the infiltration of fat in skeletal muscle, is associated with lower skeletal muscle density (SMD) as detected by computed tomography (CT). It increases with aging and obesity and is thought to play a role in the aetiology of insulin resistance and type II diabetes. The clinical significance of myosteatosis in cancer cachexia, however, remains to be determined. Along with demonstrable subcutaneous and visceral lipolysis, myosteatosis may also be a key component of the syndrome. We aimed to investigate the use of human urine as a non-invasive way to screen for molecular biomarkers of myosteatosis/reduced SMD using SELDI-TOF mass spectrometry. Pre-operative CT scans of patients undergoing surgery for upper gastrointestinal or hepatopancreaticobiliary cancer were analysed at the level of the third lumbar vertebrae. Myosteatosis was inferred as the presence of reduced SMD, which was defined as Hounsfield units for skeletal muscle <39.5 (two standard deviations below a normal healthy cohort). Urine was analysed by mass spectrometry using CM10 and IMAC30 SELDI-chips. Peaks observed in the CM10 and IMAC30 chip types, showed marked expressional differences between control and myosteatosis, were further investigated by mascot SELDI matrix matching. A total of 55 patients was recruited; 31 patients were found to be myosteatotic on CT scan. Application of the IMAC30-derived model to the entire cohort showed a sensitivity of 97%, specificity of 71% and an overall correctness of 85%. Application of the CM10 chipset-based model to the entire cohort, showed a 77% sensitivity, 67% specificity and 73% overall correctness. Analysis of the peaks of interest resulted in the identification of significant fragments of cathepsin C, argin, arylsulfatase A and glial fibrillary acidic protein. We identified several potential urinary molecular biomarkers associated with reduced SMD in cancer. Such markers are potentially useful in deriving a clinical screening test for myosteatosis.

Proteomic Protocol in Esophageal Adenocarcinoma.

The technique of surface-enhanced laser desorption/ionization time-of-flight SELDI-TOF mass spectrometry could be used to establish serum or plasma proteomic profiles in esophageal adenocarcinoma. The protein profiles in patients may be used to predict survival and monitor response to chemotherapy in patients with esophageal adenocarcinoma. Here, a protocol for sample preparation from esophageal adenocarcinoma, analysis of proteomic profiles, and collection of protein fractions for identification of significant peaks is presented.

Differential proteome profile in ischemic heart disease: Prognostic value in chronic angina versus myocardial infarction. A proof of concept.

The initial clinical manifestation of ischemic heart disease (IHD) i.e. unheralded myocardial infarction (MI) versus chronic angina pectoris (AP) is statistically associated with adverse or mild disease progression respectively in the long-term follow-up. Here, we subjected AP and MI patients to blood proteomic analysis by Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS) in order to investigate putative new prognostic biomarkers of IHD manifestation. We found several differentially expressed peaks but four of them (4176, 4475, 14,158m/z and 8922m/z for AP and MI, respectively) were most reliable. Two of them were identified; 14,158m/z peak was the double-charged form of Apolipoprotein A-I and its vasoprotective action accords with prominence in AP. The 4176m/z peak was related to FAM83C protein, while neither the 4475m/z peak nor the MI-linked 8922m/z peak could be identified. We conclude that SELDI-TOF-MS analysis may yield a panel of molecular signals able to retrospectively classify patients according to their clinical and molecular features, exploitable for predicting the natural course of IHD.

Serum Protein Profile in Women With Pregnancy Morbidity Associated With Antiphospholipid Syndrome.

CONTEXT: Antiphospholipid antibodies (aPL) are related with a high risk of pregnancy morbidity (PM) and also of vascular thrombosis. On the basis of recent studies, we expect that in women with PM associated with antiphospholipid syndrome (APS), further factors may be deregulated and involved in pathophysiology of the disease. Such factors may have the potential to become novel biomarkers for APS and its stages. SETTINGS AND DESIGN: Descriptive study from a recurrent pregnancy loss program. AIMS: To study the protein expression in sera from women with PM with or without aPL. MATERIALS AND METHODS: Protein profiles were determined by surface enhanced laser desorption and ionization - time of flight mass spectrometry (SELDI-TOF MS) in the serum samples from women with PM, 10 of them with aPL and 12 without aPL. On the basis of the mass-to-charge ratio (m/z) of the protein, signals differentially expressed between the two groups were compared with data banks to approach candidate proteins. STATISTICAL ANALYSIS USED: To determine the differential expression of each protein, a no paired t-test was performed using Ciphergen Express Client 3.1 software. RESULTS: SELDI-TOF analysis makes it possible to discriminate between several proteins in women with PM with and without aPL, although it does not allow protein identification. Nine proteins were found in significantly higher levels in aPL-positive women. CONCLUSION: The results underline that further factors beyond autoantibodies are involved in PM associated with APS and might lead to the development of new biomarkers.

Novel possibilities in the study of the salivary proteomic profile using SELDI-TOF/MS technology.

There is currently an increasing interest in exploring human saliva to identify salivary diagnostic and prognostic biomarkers, since the collection of saliva is rapid, non-invasive and stress-free. Diagnostic tests on saliva are common and cost-effective, particularly for patients who need to monitor their hormone levels or the effectiveness of undergoing therapies. Furthermore, salivary diagnostics is ideal for surveillance studies and in situations where fast results and inexpensive technologies are required. The most important constituents of saliva are proteins, the expression levels of which may be modified due to variations of the cellular conditions. Therefore, the different profile of proteins detected in saliva, including their absence, presence or altered levels, is a potential biomarker of certain physiological and/or pathological conditions. A promising novel approach to study saliva is the global analysis of salivary proteins using proteomic techniques. In the present study, surface-enhanced laser desorption/ionization-time-of-flight/mass spectrometry (SELDI-TOF/MS), one of the most recent proteomic tools for the identification of novel biomarkers, is reviewed. In addition, the possible use of this technique in salivary proteomic studies is discussed, since SELDI technology combines the precision of matrix-assisted laser desorption/ionization-TOF/MS proteomic analysis and the high-throughput nature of protein array analysis.

Application of SELDI-TOF in N-glycopeptides profiling of the urine from patients with endometrial, ovarian and cervical cancer.

PURPOSE: Endometrial (ECa), ovarian (OCa) and cervical (CCa) cancers are among 10 of the most common cancers affecting women worldwide. Cancers are known to cause some proteins to be differentially glycosylated or aberrantly excreted in the urine, which can be used as biomarkers. Since ECa, OCa and CCa are difficult to diagnose at the early stage, the aim of the present study was to identify a panel of new biomarkers for early detection of the cancers using surface-enhanced laser desorption/ionization-time-of-flight (SELDI-TOF) technology. Identification of early biomarkers that are specific and efficient can increase the survival rate of the patients. EXPERIMENTAL DESIGN: Digested urinary proteins from patients with ECa, OCa and CCa were incubated on the champedak mannose-binding (CMB) lectin-immobilized PS10 chip. The lectin-captured glycopeptides were detected with SELDI-TOF mass spectrometry and followed by biomarker wizard analysis. RESULTS: Peaks m/z 1201 and 1449 were detected as potential group discriminators. The peak m/z 1201 could distinguish OCa from CCa and ECa and its sensitivity and specificity were 100%. For m/z 1449, it was able to differentiate ECa from the other two types of cancer. CONCLUSIONS: The findings of this study suggest urinary glycopeptides m/z 1201 and 1449 may serve as potential biomarkers for the early detection of ECa, OCa and CCa, although this requires further extensive validation on clinically representative populations.

Platelet proteomics in diagnostic differentiation of primary immune thrombocytopenia using SELDI-TOF-MS.

BACKGROUND: Primary immune thrombocytopenic purpura (pITP) is defined as isolated autoimmune thrombocytopenia with idiopathic low platelet count, normal bone marrow, and unexplained causes of thrombocytopenia. Currently there is no definite criterion for ITP diagnosis. METHODS: We conducted proteomic screen of patients with pITP, secondary immune thrombocytopenia (sITP), and healthy controls using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The proteomic profiles were obtained from platelet lysate samples of 82 healthy adult controls, 64 pITP, and 70 sITP patients, from which we screened marker proteins with significant differences, and constructed a diagnosis model using the artificial neural network (ANN) technique. RESULTS: We identified 6 marker proteins in the platelet lysates of pITP patients. This diagnosis method differentiated pITP patients from sITP effectively with a sensitivity of 96.9% (31/32), a specificity of 71.0% (54/76), and the area under the ROC curve of 0.864 in the training set, and a sensitivity of 87.5% (28/32), a specificity of 69.7% (53/76), and a positive predictive value of 75.0% (81/108) in the test set. CONCLUSION: The artificial neural network model based on platelet protein profiling established a potential pITP diagnosis platform.

Expression of salivary biomarkers in patients with oral mucositis: evaluation by SELDI-TOF/MS.

OBJECTIVE: This study aims to evaluate changes in proteomic salivary profile of patients with oral mucositis after adjuvant cancer treatments. MATERIALS AND METHODS: Samples were collected from patients after adjuvant cancer therapies, and were analyzed by means of SELDI/TOF. Patients were separated in two groups: patients affected by mucositis (MUCOSITIS) and patient without mucositis (NO MUCOSITIS). All patients were divided in function of the anticancer treatment: patients who had radiotherapy (MUCOSITIS RADIO), had not radiotherapy (MUCOSITIS NO RADIO), had chemotherapy (MUCOSITIS CHEMO), and those who had not chemotherapy (MUCOSITIS NO CHEMO). Statistical evaluation PCA (Principal Component Analysis) was conducted with the software BIO-RAD Data Manager(™) (Version 3.5). RESULTS: We found the increased peaks of 3443, 3487, and 4135 m/z in MUCOSITIS group, while 6237 m/z was reduced. These same peaks would the same modifications in MUCOSITIS RADIO, while in MUCOSITIS CHEMIO are increased 3443 and 6237 m/z but 3487, 4135 m/z are reduced. These data were confirmed by the PCA. CONCLUSION: Anticancer therapy influenced the level expression of many salivary biomarkers in mucositis with a good significance. Therefore, 3443, 3487, 4135, and 6237 m/z are good biomarker candidates of oral mucositis.

Protein expression in dairy cows with and without subclinical hypocalcaemia.

AIM: To determine differences in plasma proteomic profiles between healthy cows and those with subclinical hypocalcaemia within 12 hours after calving, and thereby explore the underlying biological mechanism of subclinical hypocalcaemia in dairy cows. METHODS: Plasma samples were collected within 6 hours of calving from Holstein cows on a farm in Heilongjiang, China; 32 with subclinical hypocalcaemia (plasma calcium concentration 1.38-2.00 mmol/L and no clinical signs) and 59 control cows (plasma calcium concentration 2.10-2.8 mmol/L). Plasma samples were applied to weak cationic exchange protein chips for protein profiling by surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS), and the data were analysed using the PBS-IIC system. The amplitude of peaks for the two groups were compared using the Wilcoxon sum-rank test, and the mass-to-charge ratio of the peaks that differed was used to identify peptide fragments using the Swiss-Prot protein database. RESULTS: Seven peaks were identified in the subclinical hypocalcaemia group that differed from those of the control group (p<0.001), that represented six unique proteins. Expression of serum albumin, fibrinogen alpha chain, amyloid beta A4 proteins and neurosecretory protein VGF were increased, and expression of apolipoprotein A-II and serum amyloid A proteins were decreased in the subclinical hypocalcaemic cows compared with control cows. CONCLUSION: Use of SELDI-TOF-MS technology can effectively identify differences in plasma protein expression patterns in cows with subclinical hypocalcaemia. Neurosecretory protein VGF and amyloid beta A4 protein might represent useful biomarkers for diagnosis of subclinical hypocalcaemia.

Potential Salivary Proteomic Markers of Oral Squamous Cell Carcinoma.

AIM: The aim of the present study was to investigate the diagnostic and prognostic potential of proteomic signatures in saliva of patients with oral squamous cell carcinoma (OSCC). MATERIALS AND METHODS: Data from SELDI-TOF mass spectrometry of saliva from 45 OSCC patients and 30 healthy controls were analyzed by means of univariate and multivariate statistical approaches, in order to identify proteomic OSCC signatures, reduce dimensionality and build models for discriminating between OSCC and controls, as well as predict nodal status. RESULTS: The saliva proteome presents significant modifications in OSCC patients; some of them seem to be related to nodal involvement, and may be useful for knowledge advancement regarding oral carcinogenesis and definition of diagnostic and prognostic biomarkers. Our attempt to create a predictive model using different artificial neural networks (i.e. feed-forward (FF), radial basis function (RBF), vector quantization (VQ)) demonstrated that such biostatistical tools are powerful but not all network architectures have similar performance. RBF architecture showed the best diagnostic performance (91.89%), whereas FF had the best (77.27%) prognostic accuracy (distinguishing between N(-) and N(+)). DISCUSSION: Searching for potential biomarkers among differently expressed peptides is a challenge requiring for appropriate strategies that still remain to be defined. A number of factors may potentially impair results, e.g.: (i) a group's definition for adequate comparison; (ii) reduction of data dimensionality and selection of variables to be tested in predictive models; (iii) selection of the biostatistical tool for predictive models.

A SELDI-TOF approach to ecotoxicology: comparative profiling of low molecular weight proteins from a marine diatom exposed to CdSe/ZnS quantum dots.

Quantum dots (QDs), namely semiconductor nanocrystals, due to their particular optical and electronic properties, have growing applications in device technology, biotechnology and biomedical fields. Nevertheless, the possible threat to human health and the environment have attracted increasing attention as the production and applications of QDs increases rapidly while standard evaluation of safety lags. In the present study we performed proteomic analyses, by means of 2D gel electrophoresis and Surface Enhanced Laser Desorption Ionization-Time of Flight-Mass Spectrometry (SELDI-TOF-MS). We aimed to identify potential biomarkers of exposure to CdSe/ZnS quantum dots. The marine diatom Phaeodactylum tricornutum exposed to 2.5nM QDs was used as a model system. Both 2DE and SELDI showed the presence of differentially expressed proteins. By Principal Component Analysis (PCA) we were able to show that the differentially expressed proteins can discriminate between exposed and not exposed cells. Furthermore, a protein profile specific for exposed cells was obtained by SELDI analysis. To our knowledge, this is the first example of the application of SELDI technology to the analysis of microorganisms used as biological sentinel model of marine environmental pollution.

Mirror Image of the Amyloid-ß Species in Cerebrospinal Fluid and Cerebral Amyloid in Alzheimer's Disease.

Alzheimer's disease (AD) is characterized by amyloid-ß (Aß) accumulation in brain that is paralleled by Aß(1-42) reduction in cerebrospinal fluid (CSF). We analyzed the pattern of Aß peptides, including the N- and C-terminal truncated fragments, in brain and CSF from two familial and one sporadic AD cases. We found that (i) each patient is characterized by a distinct Aß profile in CSF and brain deposits and (ii) the CSF Aß pattern mirrors the Aß profile of cerebral amyloid. These results suggest the existence of different molecular AD subtypes which can be recognized by CSF analysis, enabling patient stratification.