Monomeric calgranulins measured by SELDI-TOF mass spectrometry and calprotectin measured by ELISA as biomarkers in arthritis

BACKGROUND: SELDI-TOF mass spectrometry (MS) is a high-throughput proteomic approach with potential for identifying novel forms of serum biomarkers of arthritis. METHODS: We used SELDI-TOF MS to analyze serum samples from patients with various forms of inflammatory arthritis. Several protein profiles were collected on different Bio-Rad Laboratories ProteinChip arrays (CM10 and IMAC-Cu(2+)) and were evaluated statistically to select potential biomarkers. RESULTS: SELDI-TOF MS analyses identified several calgranulin proteins [S100A8 (calgranulin A), S100A9 (calgranulin B), S100A9*, and S100A12 (calgranulin C)], serum amyloid A (SAA), SAA des-Arg (SAA-R), and SAA des-Arg/des-Ser (SAA-RS) as biomarkers and confirmed the results with other techniques, such as western blotting, immunoprecipitation, and nano-LC-MS/MS. The S100 proteins were all able to significantly differentiate samples from patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and ankylosing spondylitis (AS) from those of patients with inflammatory bowel diseases used as an inflammatory control (IC) group, whereas the SAA, SAA-R, and SAA-RS proteins were not, with the exception of AS. The 4 S100 proteins were coproduced in all of the pathologies and were significantly correlated with the plasma calprotectin concentration; however, these S100 proteins were correlated with the SAA peak intensities only in the RA and IC patient groups. In RA, these S100 proteins (except for S100A12) were significantly correlated with the serum concentrations of C-reactive protein, matrix metalloproteinase 3, and anti-cyclic citrullinated peptide and with the Disease Activity Score (DAS(28)). CONCLUSIONS: The SELDI-TOF MS technology is a powerful approach for analyzing the status of monomeric, truncated, or posttranslationally modified forms of arthritis biomarkers, such as the S100A8, S100A9, S100A12, and SAA proteins. The fact that the SELDI-TOF MS data were correlated with results obtained with the classic calprotectin ELISA test supports the reliability of this new proteomic technique.     

SELDI-TOF MS whole serum proteomic profiling with IMAC surface does not reliably detect prostate cancer

BACKGROUND: The analysis of bodily fluids using SELDI-TOF MS has been reported to identify signatures of spectral peaks that can be used to differentiate patients with a specific disease from normal or control patients. This report is the 2nd of 2 companion articles describing a validation study of a SELDI-TOF MS approach with IMAC surface sample processing to identify prostatic adenocarcinoma. METHODS: We sought to derive a decision algorithm for classification of prostate cancer from SELDI-TOF MS spectral data from a new retrospective sample cohort of 400 specimens. This new cohort was selected to minimize possible confounders identified in the previous study described in the companion paper. RESULTS: The resulting new classifier failed to separate patients with prostate cancer from biopsy-negative controls; nor did it separate patients with prostate cancer with Gleason scores <7 from those with Gleason scores > or =7. CONCLUSIONS: In this, the 2nd stage of our planned validation process, the SELDI-TOF MS-based protein expression profiling approach did not perform well enough to advance to the 3rd (prospective study) stage. We conclude that the results from our previous studies-in which differentiation between prostate cancer and noncancer was demonstrated-are not generalizable. Earlier study samples likely had biases in sample selection that upon removal, as in the present study, resulted in inability of the technique to discriminate cancer from noncancer cases.     

Direct-tissue SELDI-TOF mass spectrometry analysis: a new application for clinical proteomics

BACKGROUND: New molecular profiling technologies can aid in analysis of small pathologic samples obtained by minimally invasive biopsy and may enable the discovery of key biomarkers synergistic with anatomopathologic analysis related to prognosis, therapeutic response, and innovative target validation. Thus proteomic analysis at the histologic level in healthy and pathologic settings is a major issue in the field of clinical proteomics. METHODS: We used surface-enhanced laser desorption ionization-time-of-flight mass spectrometry (SELDI-TOF MS) technology with surface chromatographic subproteome enrichment and preservation of the spatial distribution of proteomic patterns to detect discrete modifications of protein expression. We performed in situ proteomic profiling of mouse tissue and samples of human cancer tissue, including brain and lung cancer. RESULTS: This approach permitted the discrimination of glioblastomas from oligodendrogliomas and led to the identification of 3 potential markers. CONCLUSION: Direct tissue proteomic analysis is an original application of SELDI-TOF MS technology that can expand the use of clinical proteomics as a complement to the anatomopathological diagnosis.     

检测子宫内膜异位症患者血清中差异表达蛋白的研究

目的：检测子宫内膜异位症（内异症）患者血清中差异表达的蛋白。方法：采用表面增强激光解吸／离子化飞行时间质谱（SELDI—TOF—MS）技术，选用WCX2蛋白质芯片对50例内异症及48例对照组血清标本进行检测以筛选内异症血清中差异表达的蛋白。结果：在Mr 0～50000范围内，检测出106个蛋白峰。内异症患者血清中差异表达的蛋白峰有4个。将发现的差异蛋白峰在Swiss蛋白数据库中搜索，发现Mr 9280蛋白峰与玻璃粘连蛋白Vitronectin相符。Vitronectin属于整合素家族，在内异症的粘附、侵袭、血管形成过程中起重要作用。其他的蛋白峰没有发现与之相匹配的蛋白，提示可能为新的蛋白质。结论：内异症患者血清中存在差异表达的蛋白，其对内异症的早期诊断具有一定的临床意义。SELDI蛋白芯片技术是一种快速、简单易行、样本用量少、高通量、重复性好的分析方法，具有广阔的临床应用前景。     

Down-regulated expression of complement factor I: a potential suppressive protein for gastric cancer identified by serum proteome analysis

BACKGROUND: Screening tests are needed for gastric cancer. In order to find serologic biomarkers for gastric cancer screening, we used proteomics to search for protein biomarkers that may be detected in serum of gastric cancer patients. METHODS: Four groups of serum samples (from 20 gastric cancer patients) included pTNM stages I to IV were compared with two control groups of serum samples. The serum samples were first chromatographed using an immunoaffinity column to selectively remove albumin and IgG. Then serum proteins separated by 2-DE and identified by MALDI-TOF/TOF-MS. RESULTS: There were 3 proteins including complement C4-B precursor, complement factor I (CFI) precursor and haptoglobin precursor were found significantly different between the healthy and gastric cancer patients. Further validation study by Western blot showed that the detection of CFI precursor was under-expressed in gastric cancer sera compared to normal sera (p<0.05), in addition to a declining expression with the advanced pTNM stage from stage I to IV of gastric cancer patients. Area under the receiver operating characteristic (ROC) curve was 0.78 for the expression of CFI precursor (p<0.01). CONCLUSIONS: 2-DE-based serum proteome analysis may be useful in the screening of serum biomarkers for gastric cancer. CFI precursor could aid in the diagnosis and indicate the advancement of gastric cancer.     

A novel, high-throughput workflow for discovery and identification of serum carrier protein-bound peptide biomarker candidates in ovarian cancer samples

BACKGROUND: Most cases of ovarian cancer are detected at later stages when the 5-year survival is approximately 15%, but 5-year survival approaches 90% when the cancer is detected early (stage I). To use mass spectrometry (MS) of serum proteins for early detection, a seamless workflow is needed that provides an opportunity for rapid profiling along with direct identification of the underpinning ions. METHODS: We used carrier protein-bound affinity enrichment of serum samples directly coupled with MALDI orthagonal TOF MS profiling to rapidly search for potential ion signatures that contained discriminatory power. These ions were subsequently directly subjected to tandem MS for sequence identification. RESULTS: We discovered several biomarker panels that enabled differentiation of stage I ovarian cancer from unaffected (age-matched) patients with no evidence of ovarian cancer, with positive results in >93% of samples from patients with disease-negative results and in 97% of disease-free controls. The carrier protein-based approach identified additional protein fragments, many from low-abundance proteins or proteins not previously seen in serum. CONCLUSIONS: This workflow system using a highly reproducible, high-resolution MALDI-TOF platform enables rapid enrichment and profiling of large numbers of clinical samples for discovery of ion signatures and integration of direct sequencing and identification of the ions without need for additional offline, time-consuming purification strategies.     

Breast cancer diagnosis and prognosis through quantitative measurements of serum glycan profiles

BACKGROUND: Glycosylated proteins play important roles in cell-to-cell interactions, immunosurveillance, and a variety of receptor-mediated and specific protein functions through a highly complex repertoire of glycan structures. Aberrant glycosylation has been implicated in cancer for many years. METHODS: We performed specific MALDI mass spectrometry (MS)-based glycomic profile analyses of permethylated glycans in sera from breast cancer patients (12, stage I; 11, stage II; 9, stage III; and 50, stage IV) along with sera from 27 disease-free women. The serum glycoproteins were enzymatically deglycosylated, and the released glycans were purified and quantitatively permethylated before their MALDI-MS analyses. We applied various statistical analysis tools, including ANOVA and principal component analysis, to evaluate the MS profiles. RESULTS: Two statistical procedures implicated several sialylated and fucosylated N-glycan structures as highly probable biomarkers. Quantitative changes according to a cancer stage resulted when we categorized the glycans according to molecular size, number of oligomer branches, and abundance of sugar residues. Increases in sialylation and fucosylation of glycan structures appeared to be indicative of cancer progression. Different statistical evaluations confirmed independently that changes in the relative intensities of 8 N-glycans are characteristic of breast cancer (P < 0.001), whereas other glycan structures might contribute additionally to distinctions in the statistically recognizable patterns (different stages). CONCLUSIONS: MS-based N-glycomic profiling of serum-derived constituents appears promising as a highly sensitive and informative approach for staging the progression of cancer.     

Detection and significance of serum protein markers of small-cell lung cancer

Currently, no satisfactory biomarkers are available to screen for small-cell lung cancer (SCLC). We applied a surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) ProteinChip system to detect 150 serum samples (including 54 SCLC patients, 24 non-small cell lung cancer [NSCLC] patients, 32 pneumonia patients, and 40 healthy individuals). The spectra data were analyzed by support vector machine (SVM) and potential biomarkers were chosen for the system training and used to construct diagnostic model. Pattern 1, constructed of four protein peaks with mass/charge (m/z) of 4,293 Da, 4,612 Da, 6,455 Da, and 7,582 Da, separated SCLC patients from the healthy individuals with a sensitivity of 88.9% and a specificity of 85.7%. This pattern performed significantly better than the current marker, neuron-specific enolase (NSE) (P<0.05). Pattern 2, constructed of protein peaks with mass/charge (m/z) of 2,764 Da and 1,7368 Da, separated SCLC from pneumonia with a sensitivity of 88.9% and a specificity of 91.7%. Pattern 3, constructed of another three protein peaks with m/z of 3,912 Da, 7,562 Da, and 13,777 Da, separated SCLC from NSCLC. The sensitivity and specificity were 83.3% and 75.0%, respectively. These results suggested that SELDI-TOF MS combined with support vector machine yields significantly higher sensitivity and specificity for the detection of serum protein of SCLC.     

Preanalytic influence of sample handling on SELDI-TOF serum protein profiles

BACKGROUND: High-throughput proteomic methods for disease biomarker discovery in human serum are promising, but concerns exist regarding reproducibility of results and variability introduced by sample handling. This study investigated the influence of different preanalytic handling methods on surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) protein profiles of prefractionated serum. We investigated whether older collections with longer sample transit times yield useful protein profiles, and sought to establish the most feasible collection methods for future clinical proteomic studies. METHODS: To examine the effect of tube type, clotting time, transport/incubation time, temperature, and storage method on protein profiles, we used 6 different handling methods to collect sera from 25 healthy volunteers. We used a high-throughput, prefractionation strategy to generate anion-exchange fractions and examined their protein profiles on CM10, IMAC30-Cu, and H50 arrays by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. RESULTS: Prolonged transport and incubation at room temperature generated low mass peaks, resulting in distinctions among the protocols. The most and least stringent methods gave the lowest overall peak variances, indicating that proteolysis in the latter may have been nearly complete. For samples transported on ice there was little effect of clotting time, storage method, or transit time. Certain proteins (TTR, ApoCI, and transferrin) were unaffected by handling, but others (ITIH4 and hemoglobin beta) displayed significant variability. CONCLUSIONS: Changes in preanalytical handling variables affect profiles of serum proteins, including proposed disease biomarkers. Proteomic analysis of samples from serum banks collected using less stringent protocols is applicable if all samples are handled identically.     

Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer

BACKGROUND: Surface-enhanced laser desorption/ionization (SELDI) is an affinity-based mass spectrometric method in which proteins of interest are selectively adsorbed to a chemically modified surface on a biochip, whereas impurities are removed by washing with buffer. This technology allows sensitive and high-throughput protein profiling of complex biological specimens. METHODS: We screened for potential tumor biomarkers in 169 serum samples, including samples from a cancer group of 103 breast cancer patients at different clinical stages [stage 0 (n = 4), stage I (n = 38), stage II (n = 37), and stage III (n = 24)], from a control group of 41 healthy women, and from 25 patients with benign breast diseases. Diluted serum samples were applied to immobilized metal affinity capture Ciphergen ProteinChip Arrays previously activated with Ni2+. Proteins bound to the chelated metal were analyzed on a ProteinChip Reader Model PBS II. Complex protein profiles of different diagnostic groups were compared and analyzed using the ProPeak software package. RESULTS: A panel of three biomarkers was selected based on their collective contribution to the optimal separation between stage 0-I breast cancer patients and noncancer controls. The same separation was observed using independent test data from stage II-III breast cancer patients. Bootstrap cross-validation demonstrated that a sensitivity of 93% for all cancer patients and a specificity of 91% for all controls were achieved by a composite index derived by multivariate logistic regression using the three selected biomarkers. CONCLUSIONS: Proteomics approaches such as SELDI mass spectrometry, in conjunction with bioinformatics tools, could greatly facilitate the discovery of new and better biomarkers. The high sensitivity and specificity achieved by the combined use of the selected biomarkers show great potential for the early detection of breast cancer.     

Protein chip array profiling analysis in patients with severe acute respiratory syndrome identified serum amyloid a protein as a biomarker potentially useful in monitoring the extent of pneumonia

BACKGROUND: A new strain of coronavirus (CoV) has caused an outbreak of severe acute respiratory syndrome (SARS), with 8098 individuals being infected and 774 deaths worldwide. We carried out protein chip array profiling analysis in an attempt to identify biomarkers that might be useful in monitoring the clinical course of SARS patients. METHODS: We performed surface-enhanced laser desorption ionization time-of-flight mass spectrometry on 89 sera collected from 28 SARS patients, 72 sera from 51 control patients with various viral or bacterial infections, and 10 sera from apparently healthy individuals. RESULTS: Nine significantly increased and three significantly decreased serum biomarkers were discovered in the SARS patients compared with the controls. Among these biomarkers, one (11,695 Da) was identified to be serum amyloid A (SAA) protein by peptide mapping and tandem mass spectrometric analysis. When we monitored the SAA concentrations longitudinally in 45 sera from four SARS patients, we found a good correlation of SAA concentration with the extent of pneumonia as assessed by a serial chest x-ray opacity score. Increased SAA occurred in three of four patients at the time of extensive pneumonia as indicated by high x-ray scores. Over the course of gradual recovery in two patients, as assessed clinically and radiologically, SAA concentrations gradually decreased. In the third patient, the concentrations were initially increased, but were further increased with superimposed multiple bacterial infections. SAA was not markedly increased in the fourth patient, who had low x-ray scores and whose clinical course was relatively mild. CONCLUSIONS: Protein chip array profiling analysis could be potentially useful in monitoring the severity of disease in SARS patients.     

Analytical validation of serum proteomic profiling for diagnosis of prostate cancer: sources of sample bias

BACKGROUND: This report and a companion report describe a validation of the ability of serum proteomic profiling via SELDI-TOF mass spectrometry to detect prostatic cancer. Details of this 3-stage process have been described. This report describes the development of the algorithm and results of the blinded test for stage 1. METHODS: We derived the decision algorithm used in this study from the analysis of serum samples from patients with prostate cancer (n = 181) and benign prostatic hyperplasia (BPH) (n = 143) and normal controls (n = 220). We also derived a validation test set from a separate, geographically diverse set of serum samples from 42 prostate cancer patients and 42 controls without prostate cancer. Aliquots were subjected to randomization and blinded analysis, and data from each laboratory site were subjected to the decision algorithm and decoded. RESULTS: Using the data collected from the validation test set, the decision algorithm was unsuccessful in separating cancer from controls with any predictive utility. Analysis of the experimental data revealed potential sources of bias. CONCLUSION: The ability of the decision algorithm to successfully differentiate between prostate cancer, BPH, and control samples using data derived from serum protein profiling was compromised by bias.     

Serum peptidome for cancer detection: spinning biologic trash into diagnostic gold

The low molecular weight region of the serum peptidome contains protein fragments derived from 2 sources: (a) high-abundance endogenous circulating proteins and (b) cell and tissue proteins. While some researchers have dismissed the serum peptidome as biological trash, recent work using mass spectrometry-based (MS-based) profiling has indicated that the peptidome may reflect biological events and contain diagnostic biomarkers. In this issue of the JCI, Villanueva et al. report on MS-based peptide profiling of serum samples from patients with advanced prostate, bladder, or breast cancer as well as from healthy controls. Surprisingly, the peptides identified as cancer-type-specific markers proved to be products of enzymatic breakdown generated after patient blood collection. The impact of these results on cancer biomarker discovery efforts is significant because it is widely believed that proteolysis occurring ex vivo should be suppressed because it destroys endogenous biomarkers. Villanueva et al. now suggest that this suppression may in fact be preventing biomarker generation.     

Effects of pretreatment protocols on human amniotic fluid protein profiling with SELDI-TOF MS using protein chips and magnetic beads

BackgroundThere is increasing interest in the use of human amniotic fluid (AF) proteomics with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) for diagnosing pregnancy-associated abnormalities. A critical parameter of diagnostic biomarkers is the accuracy and reproducibility of protein patterns. We evaluated the effects of common pretreatment protocols on protein patterns generated using SELDI mass spectrometry with two different protein capture strategies (including functional protein chips and functionalized magnetic beads prior to MS analysis) in AF.MethodVarious extrinsic factors involved in processing and storing amniotic fluid, including matrix composition, sample storage time, temperature and freeze–thaw cycles, were analyzed regarding their impact on AF protein patterns using SELDI mass spectrometry with 2 different protein capture strategies.ResultsThree extrinsic factors (sample storage for 3 days at either room temperature or 4 °C or freeze–thawing the sample 5 times) significantly decreased the number or intensities of protein peaks detected in AF. Matrix dilutions also changed the spectra of AF, with more peaks and higher intensities observed with 50% α-cyano-4-hydroxycinnamic acid (CHCA). Moreover, protein chips captured more proteins or peptides than magnetic beads on SELDI-TOF MS profiling of AF.ConclusionsThese results suggest that extrinsic factors must be taken into account for valid data interpretation to ensure good reproducibility of AF profiling by SELDI mass spectrometry.     

非小细胞肺癌预后相关评价标志物的筛选

目的利用生物芯片技术和非小细胞肺癌（non-small cell lung cancer,NSCLC）患者血清及随访结果,筛选出新型NSCLC高敏感性和特异性的血清自身免疫抗体作为分子标志物用于NSCLC的预后评价。方法（1）提取NSCLC组织总mRNA构建T7噬菌体cDNA文库;（2）用NSCLC预后良好和不良患者血清对T7文库进行生物淘洗;（3）构建蛋白芯片,分别用预后良好和不良患者血清孵育芯片进行CyS／Cy3双荧光标记并分析芯片结果;（4）对挑选出的标志物进行测序及分析。结果筛选得到最佳评价组合含6个NSCLC预后相关标志物,其联合诊断准确率80．7％,敏感性85．3％,特异性73．9％,AUC为0．825;测序及BLAST分析显示,abl—interactor 1、pleiotrophin、surfactantprotein B 3个标志物是已知癌细胞转移和预后相关分子。结论成功筛选得到1个含有6个标志物的最佳评价组合,可对NSCLC预后进行较准确诊断。     

Protein profiling of microdissected pancreas carcinoma and identification of HSP27 as a potential serum marker

BACKGROUND: Patients with pancreatic adenocarcinomas have a poor prognosis because of late clinical manifestation and the tumor's aggressive nature. We used proteomic techniques to search for markers of pancreatic carcinoma. METHODS: We performed protein profiling of microdissected cryostat sections of 9 pancreatic adenocarcinomas and 10 healthy pancreatic tissue samples using ProteinChip technology (surface-enhanced laser desorption/ionization). We identified proteins by use of 2-dimensional gel electrophoresis, peptide fingerprint mapping, and immunodepletion and used immunohistochemistry for in situ localization of the proteins found. We used ELISA to quantify these proteins in preoperative serum samples from 35 patients with pancreatic cancer and 37 healthy individuals. RESULTS: From among the differentially expressed signals that were detected by ProteinChip technology, we identified 2 proteins, DJ-1 and heat shock protein 27 (HSP27). We then detected HSP27 in sera of patients by use of ELISA, indicating a sensitivity of 100% and a specificity of 84% for the recognition of pancreatic cancer. CONCLUSIONS: The detection of DJ-1 and HSP27 in pure defined tissue and the retrieval of HSP27 in serum by antibody-based methods identifies a potential marker for pancreatic cancer.     

采用血清蛋白质组学方法筛选能诱发自身抗体的鼻咽癌相关抗原

目的 采用血清蛋白质组学方法筛选能诱发机体产生自身抗体的鼻咽癌(NPC)相关抗原,以便为NPC诊断和治疗提供候选标志.方法 收集19份NPC组织,采用二维凝胶电泳(2-DE)技术分离组织总蛋白质,每份组织样本同时做3块2-DE胶,其中将1块2-DE胶作为制备胶进行考马斯亮蓝染色,另2块2-DE胶采用半干式电转法将胶中的蛋白转至PVDF膜上,并分别与NPC患者自身的血清和健康人血清进行2-DE免疫印迹分析,识别能与多数NPC患者血清反应而不与或很少与健康人血清反应的蛋白质点,再从制备2-DE胶中切取相应蛋白质点,进行基质辅助激光解吸电离飞行时问质谱(MOLDI-TOF MS)和电喷雾电离四级杆飞行时间质谱(ESI-Q-TOF MS/MS)分析,获取肽质量指纹图和肽序列标签,数据库搜索鉴定蛋白质.结果 鉴定了13个能诱发机体产生自身抗体的NPC相关抗原:热休克蛋白70(HSP70)、人血清白蛋白(HAS)、热休克蛋白60(HSP60)、细胞角蛋白15(CK 15)、亮氨酸氨基肽酶(LAP 3)、α-烯醇化酶(α-enolase)、ErbB3结合蛋白(EBP1)、细胞角蛋白19(CK 19)、核糖体蛋白P0(RPP 0)、丙酮酸脱氢酶E1(PDE 1)、GTP结合调节蛋白(GNBP)、抗增殖蛋白(prohibitin)和Rho GDP解离抑制因子2(Rho-GDI 2),13种蛋白质点在21%的鼻咽癌患者中可见,而健康人中缺乏或出现频率较低.结论 本研究筛选到13个NPC相关抗原,这些抗原能诱导患者产生自身抗体,这些抗体有可能成为NPC诊断标志和治疗靶标.     

Novel neutrophil-derived proteins in bronchoalveolar lavage fluid indicate an exaggerated inflammatory response in pediatric cystic fibrosis patients

BACKGROUND: Airway inflammation in cystic fibrosis (CF) is exaggerated and characterized by neutrophil-mediated tissue destruction, but its genesis and mechanisms remain poorly understood. To further define the pulmonary inflammatory response, we conducted a proteome-based screen of bronchoalveolar lavage fluid (BALF) collected from young children with and without CF experiencing endobronchial infection. METHODS: We collected BALF samples from 45 children younger than 5 years and grouped them according to the presence of respiratory pathogens: > or = 1 x 10(5) colony-forming units (CFU)/mL BALF (18 and 12 samples with and without CF, respectively) and <1 x 10(5) CFU/mL (23 and 15 samples). BALF proteins were analyzed with SELDI-TOF mass spectrometry (MS) and H4 ProteinChips. Proteins were identified and characterized using trypsin digestion, tandem MS, Fourier transform ion cyclotron resonance MS, immunoblotting, and ELISA. RESULTS: The SELDI-TOF MS BALF profiles contained 53 unique, reliably detected proteins. Peak intensities of 24 proteins differed significantly between the CF and non-CF samples. They included the neutrophil proteins, alpha-defensin 1 and 2, S100A8, S100A9, and S100A12, as well as novel forms of S100A8 and S100A12 with equivalent C-terminal deletions. Peak intensities of these neutrophil proteins and immunoreactive concentrations of selected examples were significantly higher in CF than non-CF samples. CONCLUSIONS: Small neutrophil-derived BALF proteins, including novel C-terminal truncated forms of S100A proteins, are easily detected with SELDI-TOF MS. Concentrations of these molecules are abnormally high in early CF lung disease. The data provide new insights into CF lung disease and identify novel proteins strongly associated with CF airway inflammation.     

Analysis of albumin-associated peptides and proteins from ovarian cancer patients

BACKGROUND: Albumin binds low-molecular-weight molecules, including proteins and peptides, which then acquire its longer half-life, thereby protecting the bound species from kidney clearance. We developed an experimental method to isolate albumin in its native state and to then identify [mass spectrometry (MS) sequencing] the corresponding bound low-molecular-weight molecules. We used this method to analyze pooled sera from a human disease study set (high-risk persons without cancer, n = 40; stage I ovarian cancer, n = 30; stage III ovarian cancer, n = 40) to demonstrate the feasibility of this approach as a discovery method. METHODS: Albumin was isolated by solid-phase affinity capture under native binding and washing conditions. Captured albumin-associated proteins and peptides were separated by gel electrophoresis and subjected to iterative MS sequencing by microcapillary reversed-phase tandem MS. Selected albumin-bound protein fragments were confirmed in human sera by Western blotting and immunocompetition. RESULTS: In total, 1208 individual protein sequences were predicted from all 3 pools. The predicted sequences were largely fragments derived from proteins with diverse biological functions. More than one third of these fragments were identified by multiple peptide sequences, and more than one half of the identified species were in vivo cleavage products of parent proteins. An estimated 700 serum peptides or proteins were predicted that had not been reported in previous serum databases. Several proteolytic fragments of larger molecules that may be cancer-related were confirmed immunologically in blood by Western blotting and peptide immunocompetition. BRCA2, a 390-kDa low-abundance nuclear protein linked to cancer susceptibility, was represented in sera as a series of specific fragments bound to albumin. CONCLUSION: Carrier-protein harvesting provides a rich source of candidate peptides and proteins with potential diverse tissue and cellular origins that may reflect important disease-related information.     

Epitomics: serum screening for the early detection of cancer on microarrays using complex panels of tumor antigens

Efforts toward the development of early detection assays for cancers have traditionally depended on single biomarker molecules. Current technologies have been disappointing and have not resulted in diagnostic tests suitable for clinical practice. Using a high-throughput cloning method, a panel of epitopes/antigens that react with autoantibodies to tumor proteins in the serum of patients with ovarian cancer have been isolated. Discovery of biomarker panels was directed in an unbiased fashion by cloning a large panel of epitopes or tumor antigens, rather than individual biomarkers without a previous notion of their function. The binding properties of these serum antitumor antibodies on microarrays and advanced bioinformatics tools led to a panel of diagnostic antigens. The sequences that were identified using this new technology will lead to the discovery of novel disease-related proteins that have diagnostic value for the presymptomatic detection of cancer. It has been demonstrated that this approach can detect these autoantibodies in the sera of Stage I ovarian cancer patients. There are numerous advantages of employing serum antibodies as the analytes, not the least of which is the ability to rapidly adapt these assays to standard clinical platforms. This technology of global epitope/antigen profiling is referred to as 'epitomics'.