Nanoprobe-Based Affinity Mass Spectrometry for Cancer Marker Protein Profiling

2007 ◽  
Author(s):  
Li-Shing Huang ◽  
Yuh-Yih Chien ◽  
Shu-Hua Chen ◽  
Po-Chiao Lin ◽  
Kai-Yi Wang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Profiling ◽  
Marker Protein ◽  
Cancer Marker

Suzuki–Miyaura cross-coupling for chemoproteomic applications

2020 ◽  
Author(s):  
Jian Cao ◽  
Ernest Armenta ◽  
Lisa Boatner ◽  
Heta Desai ◽  
Neil Chan ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Cross Coupling ◽  
Protein Profiling ◽  
Protein Labeling ◽  
Caspase 8 ◽  
Complex Cell ◽  
Bioorthogonal Chemistry ◽  
Reaction Conditions ◽  
Target Deconvolution ◽  
Palladium Catalyzed

Bioorthogonal chemistry is a mainstay of chemoproteomic sample preparation workflows. While numerous transformations are now available, chemoproteomic studies still rely overwhelmingly on copper-catalyzed azide –alkyne cycloaddition (CuAAC) or 'click' chemistry. Here we demonstrate that gel-based activity-based protein profiling (ABPP) and mass-spectrometry-based chemoproteomic profiling can be conducted using Suzuki–Miyaura cross-coupling. We identify reaction conditions that proceed in complex cell lysates and find that Suzuki –Miyaura cross-coupling and CuAAC yield comparable chemoproteomic coverage. Importantly, Suzuki–Miyaura is also compatible with chemoproteomic target deconvolution, as demonstrated using structurally matched probes tailored to react with the cysteine protease caspase-8. Uniquely enabled by the observed orthogonality of palladium-catalyzed cross-coupling and CuAAC, we combine both reactions to achieve dual protein labeling.

Comparison of Supervised Classification Methods for Protein Profiling in Cancer Diagnosis

2007 ◽  
Vol 3 ◽  
pp. 117693510700300 ◽  
Author(s):  
Nadège Dossat ◽  
Alain Mangé ◽  
Jérôme Solassol ◽  
William Jacot ◽  
Ludovic Lhermitte ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Supervised Classification ◽  
Protein Profiling ◽  
Clinical Proteomics ◽  
High Dimensional ◽  
Classification Methods ◽  
Linear Discriminant ◽  
Supervised Classification Methods

A key challenge in clinical proteomics of cancer is the identification of biomarkers that could allow detection, diagnosis and prognosis of the diseases. Recent advances in mass spectrometry and proteomic instrumentations offer unique chance to rapidly identify these markers. These advances pose considerable challenges, similar to those created by microarray-based investigation, for the discovery of pattern of markers from high-dimensional data, specific to each pathologic state (e.g. normal vs cancer). We propose a three-step strategy to select important markers from high-dimensional mass spectrometry data using surface enhanced laser desorption/ionization (SELDI) technology. The first two steps are the selection of the most discriminating biomarkers with a construction of different classifiers. Finally, we compare and validate their performance and robustness using different supervised classification methods such as Support Vector Machine, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Neural Networks, Classification Trees and Boosting Trees. We show that the proposed method is suitable for analysing high-throughput proteomics data and that the combination of logistic regression and Linear Discriminant Analysis outperform other methods tested.

Recent Technological Advances in the Mass Spectrometry-based Nanomedicine Studies: An Insight from Nanoproteomics

2019 ◽  
Vol 25 (13) ◽  
pp. 1536-1553 ◽  
Author(s):  
Jing Tang ◽  
Yunxia Wang ◽  
Yi Li ◽  
Yang Zhang ◽  
Runyuan Zhang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Information Sources ◽  
Protein Quantification ◽  
Protein Profiling ◽  
Label Free ◽  
Dynamic Information ◽  
Data Repositories ◽  
Research Directions ◽  
Technological Advances ◽  
Recent Trends

Nanoscience becomes one of the most cutting-edge research directions in recent years since it is gradually matured from basic to applied science. Nanoparticles (NPs) and nanomaterials (NMs) play important roles in various aspects of biomedicine science, and their influences on the environment have caused a whole range of uncertainties which require extensive attention. Due to the quantitative and dynamic information provided for human proteome, mass spectrometry (MS)-based quantitative proteomic technique has been a powerful tool for nanomedicine study. In this article, recent trends of progress and development in the nanomedicine of proteomics were discussed from quantification techniques and publicly available resources or tools. First, a variety of popular protein quantification techniques including labeling and label-free strategies applied to nanomedicine studies are overviewed and systematically discussed. Then, numerous protein profiling tools for data processing and postbiological statistical analysis and publicly available data repositories for providing enrichment MS raw data information sources are also discussed.

scholarly journals Protein Profiling in Brain Tumors Using Mass Spectrometry

2004 ◽  
Vol 10 (3) ◽  
pp. 981-987 ◽  
Author(s):  
Sarah A. Schwartz ◽  
Robert J. Weil ◽  
Mahlon D. Johnson ◽  
Steven A. Toms ◽  
Richard M. Caprioli
Keyword(s):  
Mass Spectrometry ◽  
Brain Tumors ◽  
Protein Profiling

Pinpointing a marker protein in papillary bladder carcinomas using SELDI mass spectrometry and microdissection

2004 ◽  
Vol 200 (4) ◽  
pp. 280
Author(s):  
R.C. Krieg ◽  
N.T. Gaisa ◽  
L.A. Liotta ◽  
E.F. Petricoin ◽  
R. Knüchel
Keyword(s):  
Mass Spectrometry ◽  
Marker Protein ◽  
Bladder Carcinomas

5179 “Competition on Clinical Mass Spectrometry Based Proteomic Diagnosis” based on serum protein profiling for the detection of breast cancer

2009 ◽  
Vol 7 (2) ◽  
pp. 313-314
Author(s):  
W.E. Mesker ◽  
B.J. Mertens ◽  
Y.E.M. van der Burgt ◽  
A.M. Deelder ◽  
R.A.E.M. Tollenaar
Keyword(s):  
Breast Cancer ◽  
Mass Spectrometry ◽  
Serum Protein ◽  
Protein Profiling

Serum Protein Profiling of Smear-Positive and Smear-Negative Pulmonary Tuberculosis Using SELDI-TOF Mass Spectrometry

Lung ◽  
2009 ◽  
Vol 188 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Qi Liu ◽  
Xuerong Chen ◽  
Chaojun Hu ◽  
Renqing Zhang ◽  
Ji Yue ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Pulmonary Tuberculosis ◽  
Serum Protein ◽  
Protein Profiling ◽  
Smear Negative

scholarly journals Advanced Techniques in Clinical Practice: Use of Lab-on-a-Chip Electrophoresis and Other Methods in Protein Profiling

2009 ◽  
Vol 28 (4) ◽  
pp. 274-278 ◽  
Author(s):  
Olgica Trenčevska ◽  
Vasko Aleksovski ◽  
Kiro Stojanoski
Keyword(s):  
Mass Spectrometry ◽  
Clinical Practice ◽  
Cystatin C ◽  
Biological Fluids ◽  
Neurological Diseases ◽  
Protein Profile ◽  
Lab On A Chip ◽  
Protein Profiling ◽  
Complete Analysis ◽  
Potential Biomarker

Advanced Techniques in Clinical Practice: Use of Lab-on-a-Chip Electrophoresis and Other Methods in Protein ProfilingProteins in clinical practice are analyzed as important parameters in the determination and treatment of different diseases. The scopes of the analyses are mainly concentrated in two levels - analyses of the complete protein profile, or determination of an isolated protein. In this work, despite of the use of conventional methods, mainly electrophoresis, new techniques have been implemented in protein analyses. Lab-on-a-chip is an electrophoretic technique that, when optimized, provides analyses of the total protein profile. When normal samples are compared to samples obtained from patients with different neurological diseases, characteristic patterns can be noted. Also, correlation and comparison can be made between the newly developed microchip electrophoresis method and the results obtained using the conventional techniques. When an analysis of a specific protein is necessary, mass spectrometry has proven to give best results, in both the se lectivity and specificity of analyses. It is believed that cystatin C is a potential biomarker in neurological diseases; therefore, the mass spectrometry method has been developed in order to obtain qualitative and quantitative analyses of biological fluids. Using the developed method of mass spectrometry immunoassay (MSIA), cystatin C was easily isolated and analyzed, obtaining complete analysis within minutes. The resulting mass spectra revealed various levels of cystatin C isoforms in serum and CSF samples.

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