1,101 research outputs found
Programmed cell death 6 interacting protein (PDCD6IP) and Rabenosyn-5 (ZFYVE20) are potential urinary biomarkers for upper gastrointestinal cancer
PURPOSE:
Cancer of the upper digestive tract (uGI) is a major contributor to cancer-related death worldwide. Due to a rise in occurrence, together with poor survival rates and a lack of diagnostic or prognostic clinical assays, there is a clear need to establish molecular biomarkers.
EXPERIMENTAL DESIGN:
Initial assessment was performed on urine samples from 60 control and 60 uGI cancer patients using MS to establish a peak pattern or fingerprint model, which was validated by a further set of 59 samples.
RESULTS:
We detected 86 cluster peaks by MS above frequency and detection thresholds. Statistical testing and model building resulted in a peak profiling model of five relevant peaks with 88% overall sensitivity and 91% specificity, and overall correctness of 90%. High-resolution MS of 40 samples in the 2-10 kDa range resulted in 646 identified proteins, and pattern matching identified four of the five model peaks within significant parameters, namely programmed cell death 6 interacting protein (PDCD6IP/Alix/AIP1), Rabenosyn-5 (ZFYVE20), protein S100A8, and protein S100A9, of which the first two were validated by Western blotting.
CONCLUSIONS AND CLINICAL RELEVANCE:
We demonstrate that MS analysis of human urine can identify lead biomarker candidates in uGI cancers, which makes this technique potentially useful in defining and consolidating biomarker patterns for uGI cancer screening
Optimization and evaluation of surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry for protein profiling of cerebrospinal fluid
Cerebrospinal fluid (CSF) potentially carries an archive of peptides and small proteins relevant to pathological processes in the central nervous system (CNS) and surrounding brain tissue. Proteomics is especially well suited for the discovery of biomarkers of diagnostic potential in CSF for early diagnosis and discrimination of several neurodegenerative diseases. ProteinChip surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is one such approach which offers a unique platform for high throughput profiling of peptides and small proteins in CSF. In this study, we evaluated methodologies for the retention of CSF proteins < 20 kDa in size, and identify a strategy for screening small proteins and peptides in CSF. ProteinChip array types, along with sample and binding buffer conditions, and matrices were investigated. By coupling the processing of arrays to a liquid handler reproducible and reliable profiles, with mean peak coefficients of variation < 20%, were achieved for intra- and inter-assays under selected conditions. Based on peak m/z we found a high degree of overlap between the tested array surfaces. The combination of CM10 and IMAC30 arrays was sufficient to represent between 80–90% of all assigned peaks when using either sinapinic acid or α-Cyano-4-hydroxycinnamic acid as the energy absorbing matrices. Moreover, arrays processed with SPA consistently showed better peak resolution and higher peak number across all surfaces within the measured mass range. We intend to use CM10 and IMAC30 arrays prepared in sinapinic acid as a fast and cost-effective approach to drive decisions on sample selection prior to more in-depth discovery of diagnostic biomarkers in CSF using alternative but complementary proteomic strategies
Identification of a novel biomarker candidate, a 4.8-kDa peptide fragment from a neurosecretory protein VGF precursor, by proteomic analysis of cerebrospinal fluid from children with acute encephalopathy using SELDI-TOF-MS
<p>Abstract</p> <p>Background</p> <p>Acute encephalopathy includes rapid deterioration and has a poor prognosis. Early intervention is essential to prevent progression of the disease and subsequent neurologic complications. However, in the acute period, true encephalopathy cannot easily be differentiated from febrile seizures, especially febrile seizures of the complex type. Thus, an early diagnostic marker has been sought in order to enable early intervention. The purpose of this study was to identify a novel marker candidate protein differentially expressed in the cerebrospinal fluid (CSF) of children with encephalopathy using proteomic analysis.</p> <p>Methods</p> <p>For detection of biomarkers, CSF samples were obtained from 13 children with acute encephalopathy and 42 children with febrile seizure. Mass spectral data were generated by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) technology, which is currently applied in many fields of biological and medical sciences. Diagnosis was made by at least two pediatric neurologists based on the clinical findings and routine examinations. All specimens were collected for diagnostic tests and the remaining portion of the specimens were used for the SELDI-TOF MS investigations.</p> <p>Results</p> <p>In experiment 1, CSF from patients with febrile seizures (n = 28), patients with encephalopathy (n = 8) (including influenza encephalopathy (n = 3), encephalopathy due to rotavirus (n = 1), human herpes virus 6 (n = 1)) were used for the SELDI analysis. In experiment 2, SELDI analysis was performed on CSF from a second set of febrile seizure patients (n = 14) and encephalopathy patients (n = 5). We found that the peak with an m/z of 4810 contributed the most to the separation of the two groups. After purification and identification of the 4.8-kDa protein, a 4.8-kDa proteolytic peptide fragment from the neurosecretory protein VGF precursor (VGF4.8) was identified as a novel biomarker for encephalopathy.</p> <p>Conclusions</p> <p>Expression of VGF4.8 has been reported to be decreased in pathologically degenerative changes such as Alzheimer's disease, amyotrophic lateral sclerosis (ALS), frontotemporal dementia, and encephalopathy. Thus, the VGF4.8 peptide might be a novel marker for degenerative brain conditions.</p
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
Biomarkers for Ovarian Cancer
The present invention provides protein-based biomarkers and biomarker combinations that are useful in qualifying ovarian cancer status in a patient. In particular, the biomarkers of this invention are useful to classify a subject sample as ovarian cancer, ovarian cancer of low malignant potential, benign ovarian disease or other malignant condition. The biomarkers can be detected by SELDI mass spectrometry
Laboratory methods to improve SELDI peak detection and quantitation
Abstract Background Protein profiling with surface-enhanced laser desorption-ionisation time-of-flight mass spectrometry (SELDI-TOF MS) is a promising approach for biomarker discovery. Some candidate biomarkers have been identified using SELDI-TOF, but validation of these can be challenging because of technical parameters that effect reproducibility. Here we describe steps to improve the reproducibility of peak detection. Methods SELDI-TOF mass spectrometry was performed using a system manufactured by Ciphergen Biosystems along with their ProteinChip System. Serum from 10 donors was pooled and used for all experiments. Serum was fractionated with Expression Difference Mapping kit-Serum Fractionation from the same company and applied to three different ProteinChips. The fractionations were run over a one month period to examine the contribution of sample batch and time to peak detection variability. Spectra were processed and peaks detected using the Ciphergen Express software and variance measured. Results Experimental parameters specific to the serum fraction and ProteinChip, including spot protocols (laser intensity and detector sensitivity) were optimized to decrease peak detection variance. Optimal instrument settings, regular calibration along with controlled sample handling and processing nearly doubled the number of peaks detected and decreased intensity variance. Conclusion This report assesses the variation across fractionated sera processed over a one-month period. The optimizations reported decreased the variance and increased the number of peaks detected.</p
Liquid Tissue: Proteomic Profiling of Formalin-Fixed Tissues
Identification and quantitation of candidate biomarker proteins in large numbers of individual tissues is required to validate specific proteins, or panels of proteins, for clinical use as diagnostic, prognostic, toxicological, or therapeutic markers. Mass spectrometry (MS) provides an exciting analytical methodology for this purpose. Liquid Tissue MS protein preparation allows researchers to utilize the vast, already existing, collections offormalin-fixed paraffin-embedded (FFPE) tissues for the procurement of peptides and the analysis across a variety of MS platforms
Effect of Turkish propolis extracts on proteome of prostate cancer cell line
<p>Abstract</p> <p>Background</p> <p>Propolis is a natural, resinous hive product that has several pharmacological activities. Its composition varies depending on the vegetation, climate, season and environmental conditions of the area from where it was collected. Surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF MS) is a proteomic approach which has been used in cancer proteomics studies. Prostate cancer is one of the most commonly diagnosed cancers in men. It has shown that nutritional supplements rich in polyphenolic compounds such as propolis play a significant role in prostate cancer chemoprevention. The aim of this study is to evaluate if protein expression profile in PC-3 prostate cancer cell lines could be differentiated when incubated with dimethyl sulfoxide and water extracts of Turkish propolis.</p> <p>Results</p> <p>The antioxidant potentials of dimethyl sulfoxide and water extracts of propolis were found in correlation with the amount of total phenolic compounds of them. Dimethyl sulfoxide and water extracts of propolis of 20 μg/mL reduced the cell viability to 24.5% and 17.7%, respectively. Statistically significant discriminatory peaks between control PC-3 cells and dimethyl sulfoxide extract of propolis-treated PC-3 cells were found to be the proteomic features at m/z 5143, 8703, 12661, 20184 and 32794, detected by CM10 ProteinChip, and the peak at m/z 3772, detected by Q10 ProteinChip. Between control PC-3 cells and water extract of propolis-treated PC-3 cells, statistically significant discriminatory peaks were found to be the proteomic features at m/z 15846, 16052 and 24658, detected by CM10 ProteinChip and the peaks at m/z 10348, 10899 and 11603, detected by Q10 ProteinChip.</p> <p>Conclusions</p> <p>It was concluded that dimethyl sulfoxide and water extracts of Turkish propolis may have anti-proliferative activity through differentiating protein expression profile in PC-3 prostate cancer cell lines along with their antioxidant capacity.</p
A method for improving SELDI-TOF mass spectrometry data quality
<p>Abstract</p> <p>Background</p> <p>Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) is a powerful tool for rapidly generating high-throughput protein profiles from a large number of samples. However, the events that occur between the first and last sample run are likely to introduce technical variation in the results.</p> <p>Methods</p> <p>We fractionated and analyzed quality control and investigational serum samples on 3 Protein Chips and used statistical methods to identify poor-quality spectra and to identify and reduce technical variation.</p> <p>Results</p> <p>Using diagnostic plots, we were able to visually depict all spectra and to identify and remove those that were of poor quality. We detected a technical variation associated with when the samples were run (referred to as batch effect) and corrected for this variation using analysis of variance. These corrections increased the number of peaks that were reproducibly detected.</p> <p>Conclusion</p> <p>By removing poor-quality, outlier spectra, we were able to increase peak detection, and by reducing the variance introduced when samples are processed and analyzed in batches, we were able to increase the reproducibility of peak detection.</p
Identification of proteins in laser-microdissected small cell numbers by SELDI-TOF and Tandem MS
BACKGROUND: Laser microdissection allows precise isolation of specific cell types and compartments from complex tissues. To analyse proteins from small cell numbers, we combine laser-microdissection and manipulation (LMM) with mass spectrometry techniques. RESULTS: Hemalaun stained mouse lung sections were used to isolate 500–2,000 cells, enough material for complex protein profiles by SELDI-TOF MS (surface enhanced laser desorption and ionization/time of flight mass spectrometry), employing different chromatographic ProteinChip(® )Arrays. Initially, to establish the principle, we identified specific protein peaks from 20,000 laser-microdissected cells, combining column chromatography, SDS-PAGE, tryptic digestion, SELDI technology and Tandem MS/MS using a ProteinChip(® )Tandem MS Interface. Secondly, our aim was to reduce the labour requirements of microdissecting several thousand cells. Therefore, we first defined target proteins in a few microdissected cells, then recovered in whole tissue section homogenates from the same lung and applied to these analytical techniques. Both approaches resulted in a successful identification of the selected peaks. CONCLUSION: Laser-microdissection may thus be combined with SELDI-TOF MS for generation of protein marker profiles in a cell-type- or compartment-specific manner in complex tissues, linked with mass fingerprinting and peptide sequencing by Tandem MS/MS for definite characterization
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