Proteomics: applications in basic and applied biology

Anderson, N. Leigh; Matheson, Alastair; Steiner, Sandra

doi:10.1016/s0958-1669(00)00118-x

Cited by 144 publications

(75 citation statements)

References 38 publications

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“…Another decision tree analysis of serum proteomic patterns was performed by Anderson et al (28). They showed that 8 of 9 stage I gastric cancers (88.9% sensitivity for stage I) were correctly classified.…”

Section: Discussionmentioning

confidence: 99%

Serum biomarker screening for the diagnosis of early gastric cancer using SELDI-TOF-MS

Zhang

Guo

2012

Mol Med Report

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Abstract. In this study, we performed a proteomic analysis of sera from stage I gastric cancer patients using surfaceenhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and established a diagnostic model for the early diagnosis of stage I gastric cancer. Serum samples from 169 gastric cancer patients and 83 age-and gender-matched healthy individuals were analyzed by SELDI-TOF-MS ProteinChip array technology. The SELDI-TOF-MS spectral data were analyzed using the Biomarker Wizard™ and Biomarker Patterns™ software to find differential proteins and develop a classification tree for gastric cancer. A total of 34 mass peaks were identified. Six peaks at a mass-to-charge ratio (m/z) of 2873, 3163, 4526, 5762, 6121 and 7778 were used to construct the diagnostic model. The model effectively distinguished gastric cancer samples from control samples, achieving a sensitivity and specificity of 93.49 and 91.57%, respectively. In addition, we identified 3 of the 6 protein peaks at 2873, 6121 and 7778 m/z, which distinguished between stage I and stage II/III/IV gastric cancer. The model had an accuracy of 88.89% for the identification of stage I gastric cancer. In conclusion, the diagnostic model for the detection of serum proteins by SELDI-TOF-MS ProteinChip array technology correctly distinguishes gastric cancer from healthy samples, and has the ability to screen and distinguish between early gastric cancer from advanced gastric cancer.

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Section: Discussionmentioning

confidence: 99%

Serum biomarker screening for the diagnosis of early gastric cancer using SELDI-TOF-MS

Zhang

Guo

2012

Mol Med Report

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“…Proteomics is the systematic analysis of expressed proteins in tissues, by isolation, separation, identification and functional characterization of proteins in a cell, tissue, or organism (Lueking, et al, 1999;Page, et al, 1999;Anderson, et al, 2000;Rubin and Merchant, 2000). Proteomics, under the umbrella of toxicogenomics, involves the comprehensive functional annotation and validation of proteins in response to toxicant exposure.…”

Section: Protein Expressionmentioning

confidence: 99%

An Overview of Toxicogenomics

Hamadeh

Amin²,

Paules³

et al. 2002

Current Issues in Molecular Biology

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Toxicogenomics is a rapidly developing discipline that promises to aid scientists in understanding the molecular and cellular effects of chemicals in biological systems. This field encompasses global assessment of biological effects using technologies such as DNA microarrays or high throughput NMR and protein expression analysis. This review provides an overview of advancing multiple approaches (genomic, proteomic, metabonomic) that may extend our understanding of toxicology and highlights the importance of coupling such approaches with classical toxicity studies. Background and Definition of Toxicogenomics

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“…Proteome profiling is an important research goal, and is being used to identify biomarkers for diagnosis and prognosis of disease, [139][140][141] to compare protein expression levels for clinical monitoring of drug efficacy 142,143 or toxicity 142,144,145 and may someday be useful for personalized medicine. 146 Unfortunately, large-scale protein identification is hampered by the complex, multi-step sample processing regimens that are required prior to analysis.…”

Section: Introductionmentioning

confidence: 99%

A Digital Microfluidic Approach to Proteomic Sample Processing

2009

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Proteome profiling is the identification and quantitation of all proteins in biological samples. An important application of proteome profiling that has received much attention is clinical proteomics, a field that promises the discovery of biomarkers that will be useful for early diagnosis and prognosis of diseases. While clinical proteomic methods vary widely, a common characteristic is the need for (i) extraction of proteins from complex biological fluids and (ii) extensive biochemical processing (reduction, alkylation and enzymatic digestion) prior to analysis. However, the lack of standardized sample handling and processing in proteomics is a major limitation for the field. The conventional macroscale manual sample handling requires multiple containers and transfers, which often leads to sample loss and contamination. For clinical proteomics to be adopted as a gold standard for clinical measures, the issue of irreproducibility needs to be addressed. A potential solution to this problem is to form integrated systems for sample handling and processing, and in this dissertation, I describe my work towards realizing this goal using digital microfluidics (DMF). DMF is a technique characterized by the manipulation of discrete droplets (100 nL -10 L) on an array of electrodes by the application of electrical fields. It is well-suited for carrying out rapid, sequential, miniaturized automated biochemical assays. This thesis demonstrates how DMF can be a powerful tool capable of automating several protein handling and processing steps used in proteomics.iii Methods for implementing proteomic multi-step solution-phase processes (reduction, alkylation, and digestion) on DMF were developed. This was accompanied by the development of heterogenous enzymatic microreactors for efficient protein digestion. Strategies for reducing non-specific adsorption were developed. Finally, in proof-of-concept work, a combination of protein extraction and protein processing was demonstrated on DMF devices.iv ACKNOWLEDGEMENTS

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Proteomics: applications in basic and applied biology

Cited by 144 publications

References 38 publications

Serum biomarker screening for the diagnosis of early gastric cancer using SELDI-TOF-MS

Serum biomarker screening for the diagnosis of early gastric cancer using SELDI-TOF-MS

An Overview of Toxicogenomics

A Digital Microfluidic Approach to Proteomic Sample Processing

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