Article

Comparison of plasma from healthy nonsmokers, smokers, and lung cancer patients: pattern-based differentiation profiling of low molecular weight proteins and peptides by magnetic bead technology with MALDI-TOF MS.

Dr. Panjwani Center for Molecular Medicine and Drug Research, University of Karachi, Karachi, Pakistan.
Biomarkers (Impact Factor: 1.88). 02/2012; 17(3):223-30. DOI:10.3109/1354750X.2012.657245
Source: PubMed

ABSTRACT Smoking is the major contributor of lung cancer (LC), which accounts for millions of death.
This study focused on the correlation between the proteomic profiling of LC patients, and healthy nonsmokers and smokers.
Pattern-based peptide profiling of 186 plasma samples was performed through reversed-phase chromatography-18 magnetic bead fractionation coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis and resulted data were evaluated statistically by ClinProTool.
Marker peaks at m/z 1760, 5773, 5851, 2940, and 7172 were found with an excellent statistical figure.
Selected marker peaks can be served as a differentiated tool of LC patients with high sensitivity and specificity.

0 0
 · 
1 Bookmark
 · 
64 Views
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: Lung cancer remains the leading cause of cancer-related mortality worldwide. Currently known serum markers do not efficiently diagnose lung cancer at early stage. In the present study, we developed a serum proteomic fingerprinting approach coupled with a three-step classification method to address two important clinical questions: (i) to determine whether or not proteomic profiling differs between lung cancer and benign lung diseases in a population of smokers and (ii) to assess the prognostic impact of this profiling in lung cancer. Proteomic spectra were obtained from 170 pathologically confirmed lung cancer or smoking patients with benign chronic lung disease serum samples. Among the 228 protein peaks differentially expressed in the whole population, 88 differed significantly between lung cancer patients and benign lung disease, with area under the curve diagnostic values ranging from 0.63 to 0.84. Multiprotein classifiers based on differentially expressed peaks allowed the classification of lung cancer and benign disease with an area under the curve ranging from 0.991 to 0.994. Using a cross-validation methodology, diagnostic accuracy was 93.1% (sensitivity 94.3%, specificity 85.9%), and more than 90% of the stage I/II lung cancers were correctly classified. Finally, in the prognosis part of the study, a 4628 Da protein was found to be significantly and independently associated with prognosis in advanced stage non-small cell lung cancer patients (p = 0.0005). The potential markers that we identified through proteomic fingerprinting could accurately classify lung cancers in a high-risk population and predict survival in a non-small cell lung cancer population.
    Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer 09/2008; 3(8):840-50. · 4.55 Impact Factor
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: Serum peptidomics is a special form of functional proteomics. The small number of blood proteins that are the source of most prominent peptides in human serum serve as a substrate pool for commonly occurring and/or cancer-derived proteases. Exoprotease activities in particular, when superimposed on the ex vivo coagulation and complement degradation pathways, contribute to generation of not only cancer-specific but also "cancer type"-specific serum peptides. Following development of a unique, semiautomated serum peptide profiling platform and after completing investigations to eliminate common experimental bias, we have now studied possible effects of gender and age on serum peptidomes of 200 healthy men and women, ages 20-80, and of 60 patients (30 men and 30 women) with metastatic thyroid carcinomas. Extensive MALDI-TOF MS and data analysis suggested negligible contributions of both age and gender to the serum peptidome patterns except that healthy men and women under 35 years, but not older individuals, could be distinguished with approximately 70% accuracy. Considering the more advanced age of most patients, this finding is unlikely to interfere with peptidomics analysis of most cancers. By examining patient samples and age/gender-matched controls followed by variability analysis of either demographic or disease (versus control) groups, we could conclusively rule out demographic bias. An optimized, 12-peptide ion thyroid cancer signature was then developed, enabling classification of an independent validation set with 95% sensitivity and 95% specificity (binomial confidence intervals, 75.1-99.9%). Ten of these peptides had previously been assigned to signature patterns of other solid tumor cancers. One of the two newly discovered peptides was dehydro-Ala(3)-fibrinopeptide A. As we expand this study to include hundreds of thyroid cancer patients, the peptide signature will be adjusted, further validated, and then evaluated in a clinical setting used either independently or in combination with existing markers.
    Molecular &amp Cellular Proteomics 11/2006; 5(10):1840-52. · 7.25 Impact Factor
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: Magnetic bead purification for the analysis of low-abundance proteins in body fluids facilitates the identification of potential new biomarkers by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The aims of our study were to establish a proteome fractionation technique and to validate a standardized blood sampling, processing, and storage procedure for proteomic pattern analysis. We used magnetic bead separation for proteome profiling of human blood by MALDI-TOF MS (mass range, 1000-10,000 Da) and studied the effects on the quality and reproducibility of the proteome analysis of anticoagulants, blood clotting, time and temperature of sample storage, and the number of freeze-thaw cycles of samples. The proteome pattern of human serum was characterized by approximately 350 signals in the mass range of 1000-10,000 Da. The proteome profile showed time-dependent dynamic changes before and after centrifugation of the blood samples. Serum mass patterns differed between native samples and samples frozen once. The best reproducibility of proteomic patterns was with a single thawing of frozen serum samples. Application of the standardized preanalytical blood sampling and storage procedure in combination with magnetic bead-based fractionation decreases variability of proteome patterns in human serum assessed by MALDI-TOF MS.
    Clinical Chemistry 07/2005; 51(6):973-80. · 7.15 Impact Factor