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.

Nanoparticle-based surface assisted laser desorption ionization mass spectrometry: a review.

Great endeavors are undertaken to find effective nanoparticles to replace organic matrices for the analysis of small molecules using laser desorption ionization mass spectrometry (LDI-MS). Nanoparticles offer high sensitivity and better selectivity compared to conventional organic matrices. Surface assisted LDI-MS (SALDI-MS), and surface enhanced LDI-MS (SELDI-MS) provide clear background spectra without observable interferences peaks, and cause no fragmentation (soft ionization) of thermal and acidity labile molecules. This review article (with 460 references) summarizes the recent applications of nanoparticles including metallic, metal oxides, silicon, quantum dots, metal-organic frameworks and covalent organic frameworks, for the analysis of small molecules. Nanoparticles serve not only as surface for LDI-MS, but they can be also used as probe or pseudo-stationary phase for separation, enrichment, and microextraction. Hopefully, the knowledge and learning points gained from this review will deepen the understanding of nanoparticles applications for LDI-MS. Graphical Abstract Schematic representation of laser desorption ionization mass spectrometry using various nanoparticles (such as metallic nanoparticles, carbon nanomaterials, silicon based nanomaterials, metal oxides, quantum dots, metal-organic frameworks, and covalent organic frameworks). Advanced technologies using nanoparticles are also reviewed.

Peptidyl-prolyl cis-trans isomerase A - A novel biomarker of multi-episodic (recurrent) ocular toxoplasmosis.

Ocular toxoplasmosis (OT) is the most common etiology of posterior uveitis. The high incidence of macular scarring associated with OT is a leading cause of visual morbidity. Serum biomarkers of the disease would aid in its diagnosis. This study sought, for the first time, to elucidate serum biomarkers for OT by mass spectrometry. Blood samples were collected from four groups of nine patients each; toxoplasmosis IgG-with no history of uveitis, non-toxoplasmosis uveitis, first episode OT, and symptomatic recurrent OT. Serum was isolated and subjected to proteomics analysis using 2-dimensional gel electrophoresis (2D-GE) and surface-enhanced laser desorption ionization mass spectrometry (SELDI-MS). Selected proteins were further separated by SDS-PAGE and sequenced using tandem MS. Results were cross-validated with a T. gondii outbreak biomarker database that occurred in Brazil. Fifty markers of OT and 46 markers of recurrent disease were discovered by SELDI-MS of which 30 and 15, respectively, were cross-validated. 2D-GE analysis yielded 57 bands, selected based on the intensity of the bands, leading to the identification of 20 proteins. Eleven of those identified candidates were also found by SELDI-MS. Four candidates were chosen for immunoblotting. One serum protein, peptidyl-prolyl cis-trans isomerase A (PPIA), was confirmed as a biomarker of multi-episodic OT by immunoblotting in patients. PPIA can identify the patient with active recurrent OT from acute OT, other forms of uveitis and other parasitic infections. A validated PPIA assay may have a role in the diagnosis of the atypical OT patient before more invasive anterior chamber or vitreous tap is performed for PCR analysis or for Goldmann-Witner coefficient calculations. Base-line PPIA levels need to be studied to understand its possible use when deciding for prophylactic antibiotic use in the immunosuppressed sero-positive patient.

Surface tuning laser desorption/ionization mass spectrometry (STLDI-MS) for the analysis of small molecules using quantum dots.

In most applications of quantum dots (QDs) for surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS), one side of QDs is supported by a solid substrate (stainless - steel plate), whereas the other side is in contact with the target analytes. Therefore, the surface capping agent of QDs is a key parameter for laser desorption/ionization mass spectrometry (LDI-MS). Cadmium telluride quantum dots (CdTe QDs) modified with different capping agents are synthesized, characterized, and applied for surface tuning laser desorption/ionization mass spectrometry (STLDI-MS). Data shows that CdTe quantum dot modified cysteine (cys@CdTe QDs) has an absorption that matches with the wavelength of the N2 laser (337 nm). The synergistic effect of large surface area and absorption of the laser irradiation of cys@CdTe QDs enhances the LDI-MS process for small - molecule analysis, including α-, ß-, and γ-cyclodextrin, gramicidin D, perylene, pyrene, and triphenylphosphine. Cys@CdTe QDs are also applied using Al foils as substrates. Aluminum foil combined with cys@CdTe QDs enhances the ionization efficiency and is cheap compared to traditional matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) with a stainless - steel plate.

Biomarkers of inflammation and innate immunity in atrophic nonunion fracture.

BACKGROUND: Nonunion is a failure of healing following a bone fracture. Its physiopathology remains partially unclear and the discovery of new mediators could promote the understanding of bone healing. METHODS: Thirty-three atrophic nonunion (NU) patients that failed to demonstrate any radiographic improvement for 6 consecutive months were recruited for providing serum samples. Thirty-five healthy volunteers (HV) served as the control group. Proteomics studies were performed using SELDI-TOF-MS and 2D-DIGE approaches, associated or not with Proteominer® preprocessing, to highlight biomarkers specific to atrophic nonunion pathology. Peak intensities were analyzed by two statistical approaches, a nonparametric Mann-Whitney U tests (univariate approach) and a machine-learning algorithm called extra-trees (multivariate approach). Validation of highlighted biomarkers was performed by alternative approaches such as microfluidic LC-MS/MS, nephelometry, western blotting or ELISA assays. RESULTS: From the 35 HV and 33 NU crude serum samples and Proteominer® eluates, 136 spectra were collected by SELDI-TOF-MS using CM10 and IMAC-Cu(2+) ProteinChip arrays, and 665 peaks were integrated for extra-trees multivariate analysis. Accordingly, seven biomarkers and several variants were identified as potential NU biomarkers. Their levels of expression were found to be down- or up-regulated in serum of HV vs NU. These biomarkers are inter-α-trypsin inhibitor H4, hepcidin, S100A8, S100A9, glycated hemoglobin ß subunit, PACAP related peptide, complement C3 α-chain. 2D-DIGE experiment allowed to detect 14 biomarkers as being down- or up-regulated in serum of HV vs NU including a cleaved fragment of apolipoprotein A-IV, apolipoprotein E, complement C3 and C6. Several biomarkers such as hepcidin, complement C6, S100A9, apolipoprotein E, complement C3 and C4 were confirmed by an alternative approach as being up-regulated in serum of NU patients compared to HV controls. CONCLUSION: Two proteomics approaches were used to identify new biomarkers up- or down-regulated in the nonunion pathology, which are involved in bone turn-over, inflammation, innate immunity, glycation and lipid metabolisms. High expression of hepcidin or S100A8/S100A9 by myeloid cells and the presence of advanced glycation end products and complement factors could be the result of a longstanding inflammatory process. Blocking macrophage activation and/or TLR4 receptor could accelerate healing of fractured bone in at-risk patients.

Identification of carboxyl terminal peptide of Fibrinogen as a potential serum biomarker for gastric cancer.

Gastric cancer (GC) is a very common disease worldwide where new serum biomarkers are urgently needed to improve their early diagnosis. In this study, we aim to search for the potential serum protein/peptide biomarkers of GC by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). We first obtained the serum protein/peptide profiles from a training dataset including 30 patients with GC, 16 cases with chronic benign gastric disease (CGD), and 30 normal controls (CON) where 15 protein peaks were identified to exhibit the obvious deviation (P < 0.001, Wilcoxon rank sum test) among GC, CGD, and CON analyzed by Biomarker Wizard 3.1 software with three protein peaks with mass-to-charge (m/z) ratio 5910, 5342, and 6439 further confirmed in the validation dataset. Among the three protein peaks, peak 5910 displayed the most significantly different which could distinguish GC patients from CGD and CON with a sensitivity of 86.3 %, a specificity of 91.3 %, and the area under the receiver operating characteristic curve (AUC) of 0.89 by using the optimal cutoff value of 17.3. We further identified peak 5910 as the carboxyl terminal fraction of Fibrinogen α by LC-MS and validated its identity by antiserum-mediated SELDI-based immunodepletion assays. In sum, SELDI-TOF-MS method could effectively generate serum peptidome in cancer patients and provide a new approach to identify potentially diagnostic and prognostic biomarkers for cancer. The carboxyl terminal fraction of Fibrinogen α may be a potential serological biomarker for GC diagnosis.

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.

Mass spectrometry-based serum and plasma peptidome profiling for prediction of treatment outcome in patients with solid malignancies.

INTRODUCTION: Treatment selection tools are needed to enhance the efficacy of targeted treatment in patients with solid malignancies. Providing a readout of aberrant signaling pathways and proteolytic events, mass spectrometry-based (MS-based) peptidomics enables identification of predictive biomarkers, whereas the serum or plasma peptidome may provide easily accessible signatures associated with response to treatment. In this systematic review, we evaluate MS-based peptide profiling in blood for prompt clinical implementation. METHODS: PubMed and Embase were searched for studies using a syntax based on the following hierarchy: (a) blood-based matrix-assisted or surface-enhanced laser desorption/ionization time-of-flight MS peptide profiling (b) in patients with solid malignancies (c) prior to initiation of any treatment modality, (d) with availability of outcome data. RESULTS: Thirty-eight studies were eligible for review; the majority were performed in patients with non-small cell lung cancer (NSCLC). Median classification prediction accuracy was 80% (range: 66%-93%) in 11 models from 14 studies reporting an MS-based classification model. A pooled analysis of 9 NSCLC studies revealed clinically significant median progression-free survival in patients classified as "poor outcome" and "good outcome" of 2.0 ± 1.06 months and 4.6 ± 1.60 months, respectively; median overall survival was also clinically significant at 4.01 ± 1.60 months and 10.52 ± 3.49 months, respectively. CONCLUSION: Pretreatment MS-based serum and plasma peptidomics have shown promising results for prediction of treatment outcome in patients with solid tumors. Limited sample sizes and absence of signature validation in many studies have prohibited clinical implementation thus far. Our pooled analysis and recent results from the PROSE study indicate that this profiling approach enables treatment selection, but additional prospective studies are warranted.

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.

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.

Laser ionization mass spectrometry in oral squamous cell carcinoma.

Biomarker research in oral squamous cell carcinoma (OSCC) aims for screening/early diagnosis and in predicting its recurrence, metastasis and overall prognosis. This article reviews the current molecular perspectives and diagnosis of oral cancer with proteomics using matrix-assisted laser desorption ionization (MALDI) and surface-enhanced laser desorption ionization (SELDI) mass spectrometry (MS). This method shows higher sensitivity, accuracy, reproducibility and ability to handle complex tissues and biological fluid samples. However, the data interpretation tools of contemporary mass spectrometry still warrant further improvement. Based on the data available with laser-based mass spectrometry, biomarkers of OSCC are classified as (i) diagnosis and prognosis, (ii) secretory, (iii) recurrence and metastasis, and (iv) drug targets. Majority of these biomarkers are involved in cell homeostasis and are either physiologic responders or enzymes. Therefore, proteins directly related to tumorigenesis have more diagnostic value. Salivary secretory markers are another group that offers a favourable and easy strategy for non-invasive screening and early diagnosis in oral cancer. Key molecular inter-related pathways in oral carcinogenesis are also intensely researched with software analysis to facilitate targeted drug therapeutics. The review suggested the need for incorporating 'multiple MS or tandem approaches' and focusing on a 'group of biomarkers' instead of single protein entities, for making early diagnosis and treatment for oral cancer a reality.