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.

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.

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.

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.

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.

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.

The secretome of myocardial telocytes modulates the activity of cardiac stem cells.

Telocytes (TCs) are interstitial cells that are present in numerous organs, including the heart interstitial space and cardiac stem cell niche. TCs are completely different from fibroblasts. TCs release extracellular vesicles that may interact with cardiac stem cells (CSCs) via paracrine effects. Data on the secretory profile of TCs and the bidirectional shuttle vesicular signalling mechanism between TCs and CSCs are scarce. We aimed to characterize and understand the in vitro effect of the TC secretome on CSC fate. Therefore, we studied the protein secretory profile using supernatants from mouse cultured cardiac TCs. We also performed a comparative secretome analysis using supernatants from rat cultured cardiac TCs, a pure CSC line and TCs-CSCs in co-culture using (i) high-sensitivity on-chip electrophoresis, (ii) surface-enhanced laser desorption/ionization time-of-flight mass spectrometry and (iii) multiplex analysis by Luminex-xMAP. We identified several highly expressed molecules in the mouse cardiac TC secretory profile: interleukin (IL)-6, VEGF, macrophage inflammatory protein 1α (MIP-1α), MIP-2 and MCP-1, which are also present in the proteome of rat cardiac TCs. In addition, rat cardiac TCs secrete a slightly greater number of cytokines, IL-2, IL-10, IL-13 and some chemokines like, GRO-KC. We found that VEGF, IL-6 and some chemokines (all stimulated by IL-6 signalling) are secreted by cardiac TCs and overexpressed in co-cultures with CSCs. The expression levels of MIP-2 and MIP-1α increased twofold and fourfold, respectively, when TCs were co-cultured with CSCs, while the expression of IL-2 did not significantly differ between TCs and CSCs in mono culture and significantly decreased (twofold) in the co-culture system. These data suggest that the TC secretome plays a modulatory role in stem cell proliferation and differentiation.

Ubiquitin: a potential cerebrospinal fluid progression marker in Huntington's disease.

BACKGROUND: Finding early and dynamic biomarkers in Huntington's disease is a key to understanding the early pathology of Huntington's disease and potentially to tracking disease progression. This would benefit the future evaluation of potential neuroprotective and disease-modifying therapies, as well as aid in identifying an optimal time point for initiating a potential therapeutic intervention. METHODS: This explorative proteomics study evaluated cerebrospinal fluid from 94 Huntington's disease gene-expansion carriers (39 premanifest and 55 manifest) and 27 Huntington's disease gene-expansion negative individuals using surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry. Differences in peak intensity from SELDI-TOF spectra were evaluated. RESULTS: Levels of 10 peaks were statistically significantly different between manifest gene-expansion carriers and controls. One of them identified as ubiquitin was shown to be dependent on the Unified Huntington Disease Rating Scale Total Functional Capacity, a pseudo-measure of disease severity (P = 0.001), and the Symbol Digit Modalities Test (0.04) in manifest and CAG-age product score (P = 0.019) in all gene-expansion carriers. CONCLUSIONS AND RELEVANCE: Multiple studies have shown that the ubiquitin-proteasome system is involved in Huntington's disease pathogenesis and understanding of this involvement may have therapeutic potential in humans. This is the first study on cerebrospinal fluid to confirm the involvement of the ubiquitin-proteasome system in Huntington's disease. Furthermore it is shown that ubiquitin increases with disease progression and CAG-age product score and therefore may have the potential as a Huntington's disease progression marker, also prior to motor onset.

Biomarker research for moyamoya disease in cerebrospinal fluid using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry.

Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by steno-occlusive change in bilateral internal carotid arteries with unknown etiology. To discover biomarker candidates in cerebrospinal fluid from MMD patients, proteome analysis was performed by the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Three peptides, 4473Da, 4475Da, and 6253Da, were significantly elevated in MMD group. A positive correlation between 4473Da peptide and postoperative angiogenesis was determined. Twenty MMD patients were enrolled in this pilot study, including 11 pediatric cases less than 18 years of age (mean age, 8.67 years) and 9 adult MMD patients (mean age, 38.1 years). This study also includes 17 control cases with the mean age of 27.9 years old. In conclusion, 4473Da peptide is supposed to be a reliable biomarker of MMD. 4473Da peptide showed higher intensity peaks especially in younger MMD patients, and it was proved to be highly related to postoperative angiogenesis. Further study is needed to show how 4473Da peptide is involved with the etiology and the onset of MMD.

Detection of Serum Protein Biomarkers for the Diagnosis and Staging of Hepatoblastoma.

The present study aimed to identify serum biomarkers for the detection of hepatoblastoma (HB). Serum samples were collected from 71 HB patients (stage I, n = 19; stage II, n = 19, stage III, n = 19; and stage IV, n = 14) and 23 age- and sex-matched healthy children. Differential expression of serum protein markers were screened using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), and the target proteins were isolated and purified using HPLC and identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), SEQUEST, and bioinformatics analysis. Differential protein expression was confirmed by enzyme-linked immunosorbent analysis (ELISA). SELDI-TOF-MS screening identified a differentially expressed protein with an m/z of 9348 Da, which was subsequently identified as Apo A-I; its expression was significantly lower in the HB group as compared to the normal control group (1546.67 ± 757.81 vs. 3359.21 ± 999.36, respectively; p < 0.01). Although the expression level decreased with increasing disease stage, pair-wise comparison revealed significant differences in Apo A-I expression between the normal group and the HB subgroups (p < 0.01). ELISA verified the reduced expression of Apo A-I in the HB group. Taken together, these results suggest that Apo A-I may represent a serum protein biomarker of HB. Further studies will assess the value of using Apo A-I expression for HB diagnosis and staging.

Determination of biomarkers for polycyclic aromatic hydrocarbons (PAHs) toxicity to earthworm (Eisenia fetida).

Polycyclic aromatic hydrocarbon (PAH) compounds are persistent, carcinogenic, and mutagenic. When PAHs enter agricultural soils through sewage sludge, they pose an environmental risk to soil organisms, including earthworms. Therefore, we aimed to determine the toxic effects of PAHs on earthworms. Five PAHs were used: fluorene, anthracene, phenanthrene, fluoranthene, and pyrene. Only fluorene and phenanthrene exhibited toxicity (LC50 values 394.09 and 114.02 g L(-1), respectively) against the earthworm Eisenia fetida. None of the other PAHs tested in this study enhanced the mortality of adult earthworm until the concentrations reached to 1000 g L(-1). After exposure to PAHs, acetylcholinesterase (AChE) activity in E. fetida decreased in a concentration-dependent manner, and phenanthrene exhibited the strongest inhibitory effect on AChE, followed by fluorene. Activity of a representative detoxifying enzyme, carboxylesterase, was dramatically reduced in E. fetida exposed to all tested PAHs in comparison with that observed in the control test. The remaining glutathione S-transferase activity significantly decreased in E. fetida after exposure to PAHs. To profile small proteins <20 kDa, SELDI-TOF MS with Q10 ProteinChips was used, and 54 proteins were identified as being significantly different from the control (p = 0.05). Among them, the expressions of three proteins at 4501.8, 4712.4, and 4747.9 m/z were only enhanced in E. fetida exposed to anthracene and pyrene. One protein with 16,174 m/z was selectively expressed in E. fetida exposed to fluorene, phenanthrene, and fluoranthene. These proteins may be potential biomarkers for the five PAHs tested in E. fetida.

Potential serum biomarkers for glioblastoma diagnostic assessed by proteomic approaches.

BACKGROUND: The rapid progress of proteomics over the past years has allowed the discovery of a large number of potential biomarker candidates to improve early tumor diagnosis and therapeutic response, thus being further integrated into clinical environment. High grade gliomas represent one of the most aggressive and treatment-resistant types of human brain cancer, with approximately 9-12 months median survival rate for patients with grade IV glioma (glioblastoma). Using state-of-the-art proteomics technologies, we have investigated the proteome profile for glioblastoma patients in order to identify a novel protein biomarker panel that could discriminate glioblastoma patients from controls and increase diagnostic accuracy. RESULTS: In this study, SELDI-ToF MS technology was used to screen potential protein patterns in glioblastoma patients serum; furthermore, LC-MS/MS technology was applied to identify the candidate biomarkers peaks. Through these proteomic approaches, three proteins S100A8, S100A9 and CXCL4 were selected as putative biomarkers and confirmed by ELISA. Next step was to validate the above mentioned molecules as biomarkers through identification of protein expression by Western blot in tumoral versus peritumoral tissue. CONCLUSIONS: Proteomic technologies have been used to investigate the protein profile of glioblastoma patients and established several potential diagnostic biomarkers. While it is unlikely for a single biomarker to be highly effective for glioblastoma diagnostic, our data proposed an alternative and efficient approach by using a novel combination of multiple biomarkers.

Inflammation: an important parameter in the search of prostate cancer biomarkers.

BACKGROUND: A more specific and early diagnostics for prostate cancer (PCa) is highly desirable. In this study, being inflammation the focus of our effort, serum protein profiles were analyzed in order to investigate if this parameter could interfere with the search of discriminating proteins between PCa and benign prostatic hyperplasia (BPH). METHODS: Patients with clinical suspect of PCa and candidates for trans-rectal ultrasound guided prostate biopsy (TRUS) were enrolled. Histological specimens were examined in order to grade and classify the tumor, identify BPH and detect inflammation. Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry (SELDI-ToF-MS) and two-dimensional gel electrophoresis (2-DE) coupled with Liquid Chromatography-MS/MS (LC-MS/MS) were used to analyze immuno-depleted serum samples from patients with PCa and BPH. RESULTS: The comparison between PCa (with and without inflammation) and BPH (with and without inflammation) serum samples by SELDI-ToF-MS analysis did not show differences in protein expression, while changes were only observed when the concomitant presence of inflammation was taken into consideration. In fact, when samples with histological sign of inflammation were excluded, 20 significantly different protein peaks were detected. Subsequent comparisons (PCa with inflammation vs PCa without inflammation, and BPH with inflammation vs BPH without inflammation) showed that 16 proteins appeared to be modified in the presence of inflammation, while 4 protein peaks were not modified. With 2-DE analysis, comparing PCa without inflammation vs PCa with inflammation, and BPH without inflammation vs the same condition in the presence of inflammation, were identified 29 and 25 differentially expressed protein spots, respectively. Excluding samples with inflammation the comparison between PCa vs BPH showed 9 unique PCa proteins, 4 of which overlapped with those previously identified in the presence of inflammation, while other 2 were new proteins, not identified in our previous comparisons. CONCLUSIONS: The present study indicates that inflammation might be a confounding parameter during the proteomic research of candidate biomarkers of PCa. These results indicate that some possible biomarker-candidate proteins are strongly influenced by the presence of inflammation, hence only a well-selected protein pattern should be considered for potential marker of PCa.

Mass spectrometric analysis of cerebrospinal fluid protein for glioma and its clinical application.

AIM OF THE STUDY: To establish and evaluate the fingerprint diagnostic models of cerebrospinal protein profile in glioma with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and bioinformatics analysis, in order to seek new tumor markers. MATERIAL AND METHODS: SELDI-TOF-MS was used to detect the cerebrospinal protein bond to ProteinChip H4. The cerebrospinal protein profiles were obtained and analyzed using the artificial neural network (ANN) method. Fingerprint diagnostic models of cerebrospinal protein profiles for distinguishing glioma from non-brain-tumor, and distinguishing glioma from benign brain tumor, were established. The support vector machine (SVM) algorithm was used for verification of established diagnostic models. The tumor markers were screened. RESULTS: In a fingerprint diagnostic model of cerebrospinal protein profiles for distinguishing glioma from non-brain tumor, the sensitivity and specificity of glioma diagnosis were 100% and 91.7%, respectively. Seven candidate tumor markers were obtained. In a fingerprint diagnostic model for distinguishing glioma from benign brain tumor, the sensitivity and specificity of glioma diagnosis were 88.9% and 100%, respectively, and 8 candidate tumor markers were gained. CONCLUSIONS: The combination of SELDI-TOF-MS and bioinformatics tools is a very effective method for screening and identifying new markers of glioma. The established diagnostic models have provided a new way for clinical diagnosis of glioma, especially for qualitative diagnosis.

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.

Search for breast cancer biomarkers in fractionated serum samples by protein profiling with SELDI-TOF MS.

BACKGROUND: Many high-abundant acute phase reactants have been previously detected as potential breast cancer biomar-kers. However, they are unlikely to be specific for breast cancer. Cancer-specific biomarkers are thought to be among the lower abundant proteins. METHODS: We aimed to detect lower abundant discriminating proteins by performing serum fractionation by strong anion exchange chromatography preceding protein profiling with SELDI-TOF MS. In a pilot study, we tested the different fractions resulting from fractionation, on several array types. Fraction 3 on IMAC30 and Fraction 6 on Q10 yielded the most discriminative proteins and were used for serum protein profiling of 73 incident breast cancer cases and 73 matched controls. RESULTS: Eight peaks showed statistically significantly different intensities between cases and controls (P⧁0.05), and had less than 10% chance to be a false-positive finding. Seven of these were tentatively identified as apolipoprotein C-II (m/z 8,909), oxidized apolipoprotein C-II (m/z 8,925), apolipoprotein C-III (m/z 8,746), fragment of coagulation factor XIIIa (m/z 3,959), heterodimer of apolipoprotein A-I and apolipoprotein A-II (m/z 45,435), hemoglobin B-chain (m/z 15,915), and post-translational modified hemoglobin (m/z 15,346). CONCLUSION: By extensive serum fractionation, we detected many more proteins than in previous studies without fractionation. However, discriminating proteins were still high abundant. Results indicate that either lower abundant proteins are less distinctive, or more rigorous fractionation and selective protein depletion, or a more sensitive assay, are needed to detect lower abundant discriminative proteins.

Proteomic serum biomarkers and their potential application in cancer screening programs.

Early diagnosis of cancer is of pivotal importance to reduce disease-related mortality. There is great need for non-invasive screening methods, yet current screening protocols have limited sensitivity and specificity. The use of serum biomarkers to discriminate cancer patients from healthy persons might be a tool to improve screening programs. Mass spectrometry based proteomics is widely applied as a technology for mapping and identifying peptides and proteins in body fluids. One commonly used approach in proteomics is peptide and protein profiling. Here, we present an overview of profiling methods that have the potential for implementation in a clinical setting and in national screening programs.

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.

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.

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.