Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UNIPROT:P04637 (p53)
 77,613 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The screening of cDNA expression libraries derived from human tumors with autologous antibody (SEREX) has proven to be a powerful method for defining the structure of tumor antigens recognized by the humoral immune system. In the present study, 48 distinct antigens (NY-CO-1-NY-CO-48) reactive with autologous IgG were identified by SEREX analysis in 4 patients with colon cancer. Sequencing analysis showed that 17 of the cDNA clones were previously uncharacterized molecules and 31 represented known gene products. The individual cDNA clones were analyzed in the following manner: a search for mutations or other structural changes; an analysis of mRNA expression in a panel of normal tissues; and a frequency analysis of the antibody response to the expressed product in the sera of colon cancer patients and normal individuals. The initial analysis showed NY-CO-13 to be a mutated version of the p53 tumor suppressor gene. Three of the 48 antigens showed a differential pattern of mRNA expression, with NY-CO-27 (galectin-4) expressed primarily in gastrointestinal tract, and NY-CO-37 and -38 showing a pattern of tissue-specific isoforms. With regard to immunogenicity, 20 of the 48 antigens were detected by allogeneic sera; 14 of these were reactive with sera from both normal donors and cancer patients, and 6 other clones (NY-CO-8, -9, -13, -16, -20 and -38) reacted exclusively with sera from colon cancer patients (ranging from 14% to 27%). Our results on colon cancer illustrate both the complexity and the potential of the SEREX approach for analysis of the humoral immune response against human cancer.
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PMID:Characterization of human colon cancer antigens recognized by autologous antibodies. 961 Jul 21

Biomarkers for early detection of epithelial ovarian cancer (EOC) are urgently needed. Patients can generate antibodies to tumor-associated antigens (TAAs). We tested multiplex detection of antibodies to candidate ovarian TAAs and statistical modeling for discrimination of sera of EOC patients and controls. Binding of serum antibody of women with EOC or healthy controls to candidate TAA-coated microspheres was assayed in parallel. A Bayesian model/variable selection approach using Markov Chain Monte Carlo computations was applied to these data, and serum CA125 values, to determine the best predictive model. The selected model was subjected to area under the receiver-operator curve (AUC) analysis. The best model generated an AUC of 0.86 [95% confidence interval (95% CI), 0.78-0.90] for discrimination between sera of EOC patients and healthy patients using antibody specific to p53, NY-CO-8, and HOXB7. Inclusion of CA125 in the model provided an AUC of 0.89 (95% CI, 0.84-0.92) compared with an AUC of 0.83 (95% CI, 0.81-0.85) using CA125 alone. However, using TAA responses alone, the model discriminated between independent sera of women with nonmalignant gynecologic conditions and those with advanced-stage or early-stage EOC with AUCs of 0.71 (95% CI, 0.67-0.76) and 0.70 (95% CI, 0.48-0.75), respectively. Serum antibody to p53 and HOXB7 is positively associated with EOC, whereas NY-CO-8-specific antibody shows negative association. Bayesian modeling of these TAA-specific serum antibody responses exhibits similar discrimination of patients with early-stage and advanced-stage EOC from women with nonmalignant gynecologic conditions and may be complementary to CA125.
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PMID:Application of Bayesian modeling of autologous antibody responses against ovarian tumor-associated antigens to cancer detection. 1645 40