Use Of Surface-enhanced Laser Research Articles

Use of Surface-Enhanced Laser Desorption/Ionization with Time of Flight (SELDI-TOF) of the Urine in the Assessment of Acute Kidney Injury (AKI)

Background: Urinalysis is an important component in the assessment of acute kidney injury (AKI). Proteonomics is a rapidly developing approach in the analysis of physiological states. Several techniques have been developed to screen for protein populations. In this regard SELDI-TOF is a technique based on mass spectroscopy that is being utilized in proteonomics research. Methods: For this study, clean catch or catheterized urine was collected from normals (n=18) and patients referred to the renal service with AKI. Based upon urine and serum chemistries, clinical parameters, and microscopic urinalysis, the urines were separated into those consistent with prerenal azotemia (n=17) and acute tubular necrosis (ATN) (n=29). Initially, 5 samples each were chosen from the pre-renal and ATN who had no preexisting renal disease. Other etiologies of AKI were not included in this analysis. The urine specimens were diluted 1:5 and deposited onto an H4 ProteinChip array using 50% acetonitrile as the binding buffer. This system captured the greatest spectral range with the SELDI-TOF evaluation (compared to SAX, WCX2, IMAC, and NP1 ProteinChips). Low (250) and high (300) laser intensities were utilized to ionize and desorb the protein molecules; the spectra were collected in a positive ion mode and analyzed with Ciphergen Peaks software (v 3.0). Results: Five peaks with the high laser power were identified as potential candidates to discriminate between AKI due to prerenal or ATN causes. Those urines from the prerenal subjects were associated with detectable masses at 22.6 and 44.8 kilodaltons (KD); whereas subjects with ATN were noted to have urine with substantial masses at 11, 11.7, and 14.6 KD. The intensity of these peaks were then added together and normalized with the individual components of the discriminate peaks representing a percentage of the total. The prerenal and ATN subjects were then randomized in a training set consisting of 23 subjects and a testing set consisting of 23 subjects. Multiple linear regression was performed on the training set, and this allowed for 65% accuracy when applied to the testing set. Feed forward neural networks with hidden neuron layers ranging from 2-10 achieved similar predictive capability on the training set and testing sets. Conclusions: Although the SELDI-TOF methodology may be a useful adjunct in the assessment of AKI and renal disease, we suggest that larger training sets will be necessary to effectively exploit this strategy.

Evaluation of endometrial biomarkers for semi-invasive diagnosis of endometriosis

To test the hypothesis that specific proteins and peptides are expressed differentially in eutopic endometrium of women with and without endometriosis and at specific stages of the disease (minimal, mild, moderate, or severe) during the secretory phase. Patients with endometriosis were compared with controls. University hospital. A total of 29 patients during the secretory phase were selected for this study on the basis of cycle phase and presence or absence of endometriosis. Endometriosis was confirmed laparoscopically and histologically in 19 patients with endometriosis of revised American Society for Reproductive Medicine stages (9 minimal-mild and 10 moderate-severe), and the presence of a normal pelvis was documented by laparoscopy in 10 controls. Protein expression of endometrium was evaluated with use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. The differential expression of protein mass peaks was analyzed with use of support vector machine algorithms and logistic regression models. Data preprocessing resulted in differential expression of 73, 30, and 131 mass peaks between controls and patients with endometriosis (all stages), with minimal-mild endometriosis, and with moderate-severe endometriosis, respectively. Endometriosis was diagnosed with high sensitivity (89.5%) and specificity (90%) with use of five down-regulated mass peaks (1.949 kDa, 5.183 kDa, 8.650 kDa, 8.659 kDa, and 13.910 kDa) obtained after support vector machine ranking and logistic regression classification. With use of a similar analysis, minimal-mild endometriosis was diagnosed with four mass peaks (two up-regulated: 35.956 kDa and 90.675 kDa and two down-regulated: 1.924 kDa and 2.504 kDa) with maximal sensitivity (100%) and specificity (100%). The 90.675-kDa and 35.956-kDa mass peaks were identified as T-plastin and annexin V, respectively. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry analysis of secretory phase endometrium combined with bioinformatics puts forward a prospective panel of potential biomarkers with sensitivity of 100% and specificity of 100% for the diagnosis of minimal to mild endometriosis.

Use of surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS) to detect breast cancer markers in serum

e22133 Background: Breast cancer is one of the most frequent and deadly cancers worldwide. Although the survival of patients has increased over the last decades, many patients die from metastatic relapse. Progresses in screening or early diagnosis will improve survival of breast cancer. Breast cancer has never had any good serum tumor markers. Therefore, we developed and evaluated a proteomics approach to search for new biomarkers in serum of breast cancer patients. Methods: Blood samples of 50 women with breast cancer (CA) and 50 healthy women (CTRL), matched to the age, were drawn prior to surgery. We used SELDI-TOF-MS for protein profiling with three different active surfaces of the protein chips: cationic exchanger (CM-10), hydrophobic surface (H50) and a strong anion exchange surface (Q10) with different binding properties. Data were analyzed by multivariate statistical techniques and artificial neural networks. Results: SELDI-TOF- MS could discriminate between serum of breast cancer patients and healthy women. We could generate a statistic significant (p<0.001) panel with 15 biomarkers resulting of multiple peaks with different molecular weights. The diagnostic pattern could differentiate CA from CRTL with specificity of 77% and sensitivity of 85% in serum. Conclusions: In this study we could exemplify SELDI-TOF-MS as a potential screening method to detect breast cancer patients by serum analysis. The protein chip technology could greatly facilitate the discovery of new and better biomarkers in breast cancer patients. This promising approach provides a high sensitivity and specificity by a less invasive method similar to mammography that is used in screening programs. No significant financial relationships to disclose.

Combined use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry and empirical proteomic ontology knowledge base for identification of serum biomarkers for colorectal cancer

目的：探讨表面增强激光解析离子化飞行时间质谱仪（SELDI-TOF-MS）联合蛋白质组学实验数据库方法研究结直肠癌患者血清标志物的可行性.方法：应用SELDI-TOF-MS对169例结直肠癌患者与83例正常人血清进行了蛋白质谱检测,通过Biomarker WizardTM与Biomarker PatternsTM软件分析发现差异蛋白,建立结直肠癌诊断模型;用蛋白质组学实验数据库检索鉴定出有意义的差异蛋白,并用ELISA法对结直肠癌患者及正常人血清样本中差异蛋白表达进行验证.结果：发现34种差异蛋白,以质荷比（m/z）为2873,3163,6121,7778的4种差异蛋白组成的分类树诊断模型,在学习模式下其诊断结直肠癌的灵敏度为91.57%,特异度为90.53%;在测试模式下分别为82.25%,80.72%.其中m/z为7778的蛋白峰强度在结直肠癌患者血清中明显高于正常人（P〈0.01）,数据库检索结果提示该蛋白为血小板因子4（PF4）.ELISA法测定结直肠癌患者血清PF4水平显著高于正常人（P〈0.01）,其灵敏度及特异度分别为61.1%,76.9%.结论：SELDI-TOF-MS联合蛋白质组学实验数据库的方法简便可行,可为蛋白芯片研究提供新思路;PF4（m/z=7778）在结直肠癌患者血清中明显升高,是结直肠癌患者新的血清学标志物.

The potential biomarkers for thromboembolism detected by SELDI-TOF-MS

Introduction Few studies were concerned about searching for specific biomarkers for thromboembolic (arterial and venous) diseases by the use of Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS). Materials and Methods We screened for potential biomarkers in 69 plasma samples, including samples from 20 patients with idiopathetic deep vein thrombosis (DVT), 20 patients with acute myocardial infarction (AMI), and 29 healthy controls without a history of thromboembolism. Pretreated plasma samples were analyzed on the Protein Biology System IIc plus SELDI-TOF-MS (Ciphergen Biosystems, Fremont, CA). Proteomic spectra of mass to charge ratio ( m/z) were generated by the application of plasma to immobilized metal affinity capture (IMAC-3) ProteinChip arrays activated with copper. Results A pattern of three biomarkers ( m/z: 2 667, 5 914, and 6 890 Da, respectively) with a total accuracy of 100% was selected based on their collective contribution to the optimal separation between patients with AMI and healthy controls. Another spattern consisting of only one biomarker ( m/z: 5 914 Da) could totally discriminate patients with DVT and control subjects. For further analysis between patients with AMI and those with DVT, a pattern of four biomarkers ( m/z: 3 418, 5 271, 33 378, and 68 125 Da, respectively) was selected with a total accuracy of 82.5%. Conclusions Plasma proteomic profiling with SELDI-TOF-MS and ProteinChip technologies provides high sensitivity and specificity in discriminating patients with thrombosis and healthy subjects. The discovered biomarkers might show great potential for early diagnosis of thromboembolic diseases.

Surface enhanced laser desorption/ionization time-of-flight mass spectrometry profiling of serum in detection of laryngeal squamous cell carcinoma and the progression to lymph node metastasis

To assess the use of surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) to identify multiple serum protein biomarkers for early detection of laryngeal squamous cell carcinoma (LSCC), to establish predictive model, and to accurately distinguish LSCC patients with or without lymph node metastasis. Serum samples were collected from 142 LSCC patients and 110 normal controls, totally 252, and randomly divided into 2 groups: model establishment group (including 89 patients with LSCC at the stages I and II, 30 of which had lymph node metastasis, and 65 normal controls) and blind test group (including 53 patients with LSCC at the stages III and IV and 45 normal controls). Serum protein profiling on weak cationic exchange (WCX2) was performed by SELDI-TOF MS and the results were analyzed by Biomarker Wizard software. The Decision Tree classification algorithm and blind validation were determined by Biomarker Pattern software (BPS). A panel of 18 biomarkers ranging from 2,000 to 50,000 was selected based on their collective contribution to the optimal separation between the LSCC patients and healthy controls. Among them 1 candidate protein peak with the M/Z value of 4,176 was selected to establish predictive model by BPS with the sensitivity of 86.52% and the specificity of 84.62%. The ability to detect LSCC patients was evaluated using blind test data in cancer patients. The sensitivity of the blind test was 84.91%, and the specificity was 82.22%. 14 potential biomarkers were found to differentiate the LSCC patients with or without lymph node metastasis (P < 0.05). The high sensitivity and specificity achieved by the serum protein biomarkers show great potential for the early detection of LSCC. SELDI-TOF MS serum profiling is able to distinguish LSCC patients with or without lymph node metastasis.

The use of surface‐enhanced laser desorption/ionization time‐of‐flight mass spectrometry to detect putative breast cancer markers in saliva: a feasibility study

Technologies are now available enabling saliva to be used to diagnose disease, predict disease progression, and monitor therapeutic efficacy. This pilot study describes the use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI) to detect putative breast cancer markers in saliva. Salivary specimens were analyzed as either pooled cancer saliva specimens, or individual specimens from healthy women and women diagnosed with carcinoma of the breast. The specimens were applied to a variety of protein chip arrays, washed extensively to remove unbound analytes and analyzed on a SELDI mass spectrometer. The results of this initial study suggest that the WCX protein chip array prepared and washed at pH 3.5 yielded the most promising results. Additionally, the analyses revealed a number of proteins that were higher in intensity among the cancer subjects when compared with controls. These salivary proteins were present at the 18, 113, 170, 228 and 287 km/z ranges using SELDI analyses. The study suggests that saliva may be useful for high-throughput biomarker discovery.

Proteomic profiling of cholangiocarcinoma: Diagnostic potential of SELDI-TOF MS in malignant bile duct stricture

Proteomic techniques promise to improve the diagnosis of cholangiocarcinoma (CC) in both tissue and serum as histological diagnosis and existing serum markers exhibit poor sensitivities. We explored the use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) to identify potential protein biomarkers of CC. Twenty-two resected CC samples were compared with adjacent noninvolved bile duct tissue. Serum from patients with CC (n=20) was compared with patients with benign disease (n=20), and healthy volunteers (n=25). Samples were analyzed on hydrophobic protein chips via SELDI-TOF MS, and classification models were developed using logistic regression and cross-validation analysis. Univariate analysis revealed 14 individual peaks differentially expressed between CC and bile duct tissue, 4 peaks between CC and benign disease, and 12 peaks between CC and sera of healthy volunteers. The 4,462 mass-to-charge serum peak had superior discriminatory ability to carbohydrate antigen 19.9 (CA19.9) and carcinoembryonic antigen (CEA) (P=.004; receiver operating characteristic [ROC] area under the curve [AUC]=0.76, 0.73, and 0.70, respectively). The training models developed panels of peaks that distinguished CC from bile duct tissue (92.5% sensitivity, 92.3% specificity; ROC AUC=0.96), CC from benign serum (65.0% sensitivity, 70.0% specificity; ROC AUC=0.83), and CC from sera of healthy volunteers (75.0% sensitivity, 100% specificity; ROC AUC=0.92). Serum results were further improved with the inclusion of CA19.9 and CEA (ROC AUC=0.86 and 0.99 for CC vs benign and healthy volunteer serum, respectively). In conclusion, biomarker panels are capable of distinguishing CC from nonmalignant tissue; serum markers have important diagnostic implications for unknown bile duct stricture.

SELDI-TOF MS profiling of serum for detection of the progression of chronic hepatitis C to hepatocellular carcinoma

Proteomic profiling of serum is an emerging technique to identify new biomarkers indicative of disease severity and progression. The objective of our study was to assess the use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) to identify multiple serum protein biomarkers for detection of liver disease progression to hepatocellular carcinoma (HCC). A cohort of 170 serum samples obtained from subjects in the United States with no liver disease (n = 39), liver diseases not associated with cirrhosis (n = 36), cirrhosis (n = 38), or HCC (n = 57) were applied to metal affinity protein chips for protein profiling by SELDI-TOF MS. Across the four test groups, 38 differentially expressed proteins were used to generate multiple decision classification trees to distinguish the known disease states. Analysis of a subset of samples with only hepatitis C virus (HCV)-related disease was emphasized. The serum protein profiles of control patients were readily distinguished from each HCV-associated disease state. Two-way comparisons of chronic hepatitis C, HCV cirrhosis, or HCV-HCC versus healthy had a sensitivity/specificity range of 74% to 95%. For distinguishing chronic HCV from HCV-HCC, a sensitivity of 61% and a specificity of 76% were obtained. However, when the values of known serum markers alpha fetoprotein, des-gamma carboxyprothrombin, and GP73 were combined with the SELDI peak values, the sensitivity and specifity improved to 75% and 92%, respectively. In conclusion, SELDI-TOF MS serum profiling is able to distinguish HCC from liver disease before cirrhosis as well as cirrhosis, especially in patients with HCV infection compared with other etiologies.

Proteomic patterns: their potential for disease diagnosis

Alterations in proteins abundance, structure, or function, act as useful indicators of pathological abnormalities prior to development of clinical symptoms and as such are often useful diagnostic and prognostic biomarkers. The underlying mechanism of diseases such as cancer are, however, quite complicated in that often multiple dysregulated proteins are involved. It is for this reason that recent hypotheses suggest that detection of panels of biomarkers may provide higher sensitivities and specificities for disease diagnosis than is afforded with single markers. Recently, a novel approach based on the analysis of protein patterns has emerged that may provide a more effective means to diagnose diseases, such as ovarian and prostate cancer. The method is based on the use of surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry (TOF-MS) to detect differentially captured proteins from clinical samples, such as serum and plasma. This analysis results in the detection of “proteomic” patterns that have been shown in recent investigations to distinguish diseased and unaffected subjects to varying degrees. This review will discuss the basics of SELDI protein chip technology and highlight its recent applications in disease biomarker discovery with emphasis on cancer diagnosis.

Protein profiling in urine for the diagnosis of bladder cancer.

At present, the most reliable means of diagnosis and surveillance of bladder cancer are cystoscopic examination and bladder biopsy for histologic confirmation. The invasive and labor-intensive nature of this procedure underscores the need to develop better, less costly, and nonsurgical diagnostic tools (1)(2). Use of surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry has been successful in facilitating protein profiling of complex biological mixtures. This technology uses chemical affinity platforms to capture protein molecules from various biological sources. Retained proteins are subsequently analyzed by mass spectrometry [reviewed in Ref. ((3))]. Recent reports provide evidence that analysis of SELDI data by “learning” algorithms can lead to the identification of serum protein “fingerprints” for prostate, ovarian, and breast cancers (4)(5)(6)(7)(8)(9) and urinary fingerprints for kidney cancer (10). We recently reported the application of the SELDI system for detection of potential bladder cancer-associated biomarkers in urine (11). In this earlier study, we showed that combination of five transitional cell carcinoma (TCC)-associated protein peaks by simple statistical methods provided 87% sensitivity and 66% specificity in disease detection. The objectives of the current study were ( a ) to evaluate a commercial available data-mining classification algorithm for the analysis of the SELDI mass spectral data, and ( b ) assessing the clinical utility of this assay in detecting bladder cancer from a geographically and clinically mixed population. Fresh spot-voided urine specimens from 230 individuals were included in the study. Specimens were collected from patients …

Structural similarity between the bone marrow extracellular matrix protein and neurokinin 1 could be the limiting factor in the hematopoietic effects of substance P.

In the adult bone marrow (BM), immune cells are replenished through the process of definitive hematopoiesis, which is regulated by a complex process of cellular and humoral interactions. The latter include substance P (SP), a neurotransmitter that is produced by neural and nonneural cells. Neurokinin-1 (NK-1), the high-affinity SP receptor, shares structural similarity with fibronectin, a component of the BM extracellular matrix proteins. This study examines how such similarity could alter the effects of SP on the proliferation of the immature BM progenitors. In vitro studies show that 1 ng fibronectin/mL enhanced the stimulatory effect of SP on the proliferation of primitive BM progenitors. This finding was studied by computational studies: proteomics and three-dimensional molecular modeling. Use of surface-enhanced laser desorption/ionization ProteinChip technology showed that despite the induction of neutral endopeptidase, exogenous fibronectin hindered the degradation of SP to SP(1-4). These findings support a protective role for fibronectin in the digestion of SP. Since SP(1-4) is a negative regulator of hematopoiesis, this report indicates that the structural similarity between fibronectin and NK-1 could be important for maintaining hematopoietic stimulation. These studies could be extrapolated to hematological disorders that are associated with SP-fibronectin complexes.