Literature DB >> 15251977

Detection of differentially expressed proteins in early-stage melanoma patients using SELDI-TOF mass spectrometry.

Lori L Wilson1, Linh Tran, Donald L Morton, Dave S B Hoon.   

Abstract

Tumor progression is a dynamic sequence of events that involves specific protein changes. We hypothesized that Surface Enhanced Laser Desorption/Ionization (SELDI) mass spectrometric analysis of sera from patients with AJCC stage I and II melanoma with negative loco-regional lymph nodes could identify potential melanoma-associated protein biomarkers of disease recurrence. Serum specimens were collected from 49 patients who developed recurrence (n = 25) or remained free of recurrence (n = 24) without evidence of disease following complete resection (AJCC stage I and II). Follow-up was longer than 5 years. Serum proteins were denatured and applied onto two protein chip chemistry surfaces (weak cationic WCX2; metal-binding, IMAC3-Cu). SELDI ProteinChip mass spectrometry was then performed. SELDI data were analyzed, protein peak clustering and classification were performed, and a supervised classification algorithm was employed to classify the dataset. Multiple protein peaks ranging from 3.3 to 30 kDa were identified between patients with recurrence and those without recurrence, and the expression pattern differences of three proteins were used to generate the discriminating classification tree. The biomarkers were expressed with a high degree of reproducibility. In this early characterization study, melanoma recurrence was predicted with a sensitivity of 72% (18/25) and a specificity of 75% (18/24). This novel pilot study revealed three proteins that accurately identified patients who developed recurrence after curative resection of primary melanoma.

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Year:  2004        PMID: 15251977     DOI: 10.1196/annals.1318.047

Source DB:  PubMed          Journal:  Ann N Y Acad Sci        ISSN: 0077-8923            Impact factor:   5.691


  12 in total

1.  Protein signatures for survival and recurrence in metastatic melanoma.

Authors:  William M Hardesty; Mark C Kelley; Deming Mi; Robert L Low; Richard M Caprioli
Journal:  J Proteomics       Date:  2011-04-23       Impact factor: 4.044

2.  In Silico Analysis Validates Proteomic Findings of Formalin-fixed Paraffin Embedded Cutaneous Squamous Cell Carcinoma Tissue.

Authors:  Ali Azimi; Kimberley L Kaufman; Marina Ali; Steven Kossard; Pablo Fernandez-Penas
Journal:  Cancer Genomics Proteomics       Date:  2016 11-12       Impact factor: 4.069

Review 3.  Human body fluid proteome analysis.

Authors:  Shen Hu; Joseph A Loo; David T Wong
Journal:  Proteomics       Date:  2006-12       Impact factor: 3.984

4.  Proteomic analysis of serum yields six candidate proteins that are differentially regulated in a subset of women with endometriosis.

Authors:  Beata Seeber; Mary D Sammel; Xuejun Fan; George L Gerton; Alka Shaunik; Jesse Chittams; Kurt T Barnhart
Journal:  Fertil Steril       Date:  2009-02-20       Impact factor: 7.329

5.  Discovering differential protein expression caused by CagA-induced ERK pathway activation in AGS cells using the SELDI-ProteinChip platform.

Authors:  Zhen Ge; Yong-Liang Zhu; Xian Zhong; Jie-Kai Yu; Shu Zheng
Journal:  World J Gastroenterol       Date:  2008-01-28       Impact factor: 5.742

6.  Highly sensitive detection of melanoma based on serum proteomic profiling.

Authors:  Julie Caron; Alain Mangé; Bernard Guillot; Jérôme Solassol
Journal:  J Cancer Res Clin Oncol       Date:  2009-03-14       Impact factor: 4.553

7.  Identification of Autoantibodies for α and γ-Enolase in Serum from a Patient with Melanoma.

Authors:  Yui Hiura; Toyofumi Nakanishi; Miki Tanioka; Takayuki Takubo; Shinichi Moriwaki
Journal:  Jpn Clin Med       Date:  2011-07-17

8.  The value of serum biomarkers (Bc1, Bc2, Bc3) in the diagnosis of early breast cancer.

Authors:  Kemal Atahan; Hakan Küpeli; Serhat Gür; Türkan Yiğitbaşı; Yasemin Baskın; Seyran Yiğit; Mehmet Deniz; Atilla Cökmez; Ercüment Tarcan
Journal:  Int J Med Sci       Date:  2011-02-12       Impact factor: 3.738

9.  Proteomics in melanoma biomarker discovery: great potential, many obstacles.

Authors:  Michael S Sabel; Yashu Liu; David M Lubman
Journal:  Int J Proteomics       Date:  2011-10-11

Review 10.  Advances in Proteomic Technologies and Its Contribution to the Field of Cancer.

Authors:  Mehdi Mesri
Journal:  Adv Med       Date:  2014-09-07
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