Proteomics Approaches to Identify Tumor Antigen Directed Autoantibodies as Cancer Biomarkers

Imafuku, Yuji; Omenn, Gilbert S.; Hanash, Samir M.

doi:10.1155/2004/829450

Cited by 45 publications

(32 citation statements)

References 20 publications

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“…Among the currently available techniques, the combination of proteomics with serology (immunoproteomics (30 -34)) is largely being used to screen for panels of biomarkers and therapeutic targets in patients with infectious diseases (including SC (27,31,35,36)), cancer, or autoimmune disorders (32,(37)(38)(39)(40)(41). This discipline permits characterization of the immunome of a (micro)organism, defined as the subset of the proteome of a (micro)organism that acts as a target for the immune system (42).…”

Section: Not Only Does Systemic Candidiasis (Sc)mentioning

confidence: 99%

Decoding Serological Response to Candida Cell Wall Immunome into Novel Diagnostic, Prognostic, and Therapeutic Candidates for Systemic Candidiasis by Proteomic and Bioinformatic Analyses

Pitarch

Jiménez

Nombela

et al. 2006

Molecular & Cellular Proteomics

133

123

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In an effort to bring novel diagnostic and prognostic biomarkers or even potential targets for vaccine design for systemic candidiasis (SC) into the open, a systematic proteomic approach coupled with bioinformatic analysis was used to decode the serological response to Candida wall immunome in SC patients. Serum levels of IgG antibodies against Candida wall-associated proteins (proteins secreted from protoplasts in active wall regeneration, separated by two-dimensional gel electrophoresis, and identified by mass spectrometry) were measured in 45 SC patients, 57 non-SC patients, and 61 healthy subjects by Western blotting. Two-way hierarchical clustering and principal component analysis of their serum anti-Candida wall antibody expression patterns discriminated SC patients from controls and highlighted the heterogeneity of their expression profiles. Multivariate logistic regression models demonstrated that high levels of antibodies against glucan 1,3-␤-glucosidase (Bgl2p) and the antiwall phosphoglycerate kinase antibody seropositivity were the only independent predictors of SC. Receiver operating characteristic curve analysis revealed no difference between their combined evaluation and measurement of anti-Bgl2p antibodies alone. In a logistic regression model adjusted for known prognostic factors for mortality, SC patients with high anti-Bgl2p antibody levels or a positive anti-wall enolase antibody status, which correlated with each other, had a reduced 2-month risk of death. After controlling for each other, only the seropositivity for anti-wall enolase antibodies was an independent predictor of a lower risk of fatality, supporting that these mediated the protective effect. No association between serum anti-cytoplasmic enolase antibody levels and outcomes was established, suggesting a specific mechanism of enolase processing during wall biogenesis. We conclude that serum anti-Bgl2p antibodies are a novel accurate diagnostic biomarker for SC and that, at high levels,

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Section: Not Only Does Systemic Candidiasis (Sc)mentioning

confidence: 99%

Decoding Serological Response to Candida Cell Wall Immunome into Novel Diagnostic, Prognostic, and Therapeutic Candidates for Systemic Candidiasis by Proteomic and Bioinformatic Analyses

Pitarch

Jiménez

Nombela

et al. 2006

Molecular & Cellular Proteomics

133

123

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“…The most widely used techniques for the discovery and simultaneous profiling of multiple protein biomarkers are mass spectrometry, [16][17][18] 2-D western blotting, 19,20 2-D gel electrophoresis, 21,22 and immunological assays such as enzyme-linked immunosorbent assay (ELISA). 2,20,23 Each of these detection platforms plays an important role in the various steps involved in establishing new biomarkers; however, none of these techniques are well-suited for the comparative analysis of large numbers of samples or the multiplexed detection of many targets within an individual sample.…”

Section: Introductionmentioning

confidence: 99%

“…2,20,23 Each of these detection platforms plays an important role in the various steps involved in establishing new biomarkers; however, none of these techniques are well-suited for the comparative analysis of large numbers of samples or the multiplexed detection of many targets within an individual sample. An excellent and efficient alternative is microarray-based technologies.…”

Section: Introductionmentioning

confidence: 99%

Microarray methods for protein biomarker detection

Lee

Wark

Corn

2008

Analyst

137

108

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The application of protein biomarkers as an aid for the detection and treatment of diseases has been subject to intensified interest in recent years. The quantitative assaying of protein biomarkers in easily obtainable biological fluids such as serum and urine offers the opportunity to improve patient care via earlier and more accurate diagnoses in a convenient, non-invasive manner as well as providing a potential route towards more individually targeted treatment. Essential to achieving progress in biomarker technology is the ability to screen large numbers of proteins simultaneously in a single experiment with high sensitivity and selectivity. In this article, we highlight recent progress in the use of microarrays for high-throughput biomarker profiling and discuss some of the challenges associated with these efforts. I IntroductionThe discovery of protein biomarkers whose change in expression level or state correlates with the progression of a disease is becoming increasingly important. Once validated, proposed biomarkers can be involved in achieving an earlier diagnosis, differentiating between disease types with greater accuracy, and assessing response to treatment. Prominent examples of biomarkers include proteins that are associated with a variety of cancers, 1-4 as well as heart, 5,6 renal, 7,8 andAlzheimer's 9,10 diseases.Most biomarker studies reported to date have focused on serum-, plasmaand urine-based samples. A number of other possibilities include saliva, tears, breath condensates, cerebrospinal fluid and tissue lysates extracted from biopsy samples. There are several excellent reviews detailing biomarker discovery and validation. [11][12][13][14][15] The potential benefits of biomarkers have greatly motivated both academic and industry researchers to apply new proteomic technologies for biomarker discovery and to develop quantitative analytical methodologies for rapid and sensitive biomarker detection. Many clinically relevant biomarkers reside in blood at picomolar concentrations and lower, which is five to seven orders of magnitude lower than the most abundant plasma proteins. Therefore, protein detection with high specificity and sensitivity is required; unfortunately, no universal ultrasensitive enzymatic amplification method (such as PCR for the case of nucleic acid detection) exists for proteins. Additionally, it is desirable to screen multiple proteins simultaneously in a single sample. Multiplexed measurements are attractive not only for economic reasons but also for identifying characteristic signal patterns associated with the relative changes in entire sets of proteins as this will provide much more insight and diagnostic accuracy than individual biomarker measurements.hyejinlee@knu.ac.kr. 14,19,[24][25][26][27][28][29][30] Although microarray methods are wellestablished for high-throughput nucleic acid studies, their application for protein detection has been limited by issues such as the surface immobilization of protein capture probes without loss in bioactivity as well a...

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“…Circulating autoantibodies in lung cancer have been reported to have potential for either diagnosis or prognosis (6). Several proteomics methods are emerging as useful means to discover autoantibody biomarkers (4,7). Our previous studies uncovered autoantibodies against annexin and protein gene product (PGP) 9.5 proteins in lung cancer patient sera collected at the time of diagnosis (8,9).…”

Section: Introductionmentioning

confidence: 99%

Identification of 14-3-3𝛉 as an Antigen that Induces a Humoral Response in Lung Cancer

et al. 2007

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We have implemented a strategy to identify tumor antigens that induce a humoral immune response in lung cancer based on the analysis of tumor cell proteins. Chromatographically fractionated protein extracts from three lung cancer cell lines were subjected to Western blotting and hybridization with individual sera to determine serum antibody binding. Two sets of sera were initially investigated. One set consisted of sera from 19 newly diagnosed subjects with lung adenocarcinoma and 19 matched controls. A second independent set consisted of sera from 26 newly diagnosed subjects with lung adenocarcinoma and 24 controls matched for age, gender, and smoking history. One protein that exhibited significant reactivity with both sets of cancer sera (P = 0.0008) was confidently identified by mass spectrometry as 14-3-3u. Remarkably, significant autoantibody reactivity against 14-3-3u was also observed in an analysis of a third set consisting of 18 prediagnostic lung cancer sera collected as part of the Beta-Carotene and Retinol Efficacy Trial cohort study, relative to 19 matched controls (P = 0.0042). A receiver operating characteristic curve constructed with a panel of three proteins consisting of 14-3-3u identified in this study, plus annexin 1 and protein gene product 9.5 proteins previously identified as associated with autoantibodies in lung cancer, gave a sensitivity of 55% at 95% specificity (area under the curve, 0.838) in discriminating lung cancer at the preclinical stage from matched controls.

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Proteomics Approaches to Identify Tumor Antigen Directed Autoantibodies as Cancer Biomarkers

Cited by 45 publications

References 20 publications

Decoding Serological Response to Candida Cell Wall Immunome into Novel Diagnostic, Prognostic, and Therapeutic Candidates for Systemic Candidiasis by Proteomic and Bioinformatic Analyses

Decoding Serological Response to Candida Cell Wall Immunome into Novel Diagnostic, Prognostic, and Therapeutic Candidates for Systemic Candidiasis by Proteomic and Bioinformatic Analyses

Microarray methods for protein biomarker detection

Identification of 14-3-3𝛉 as an Antigen that Induces a Humoral Response in Lung Cancer

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