Identification of lung cancer with high sensitivity and specificity by blood testing.

BACKGROUND: Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer. METHODS: We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation. RESULTS: The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%. CONCLUSION: We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be separated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.

Improving seroreactivity-based detection of glioma.

Seroreactivity profiling emerges as valuable technique for minimal invasive cancer detection. Recently, we provided first evidence for the applicability of serum profiling of glioma using a limited number of immunogenic antigens. Here, we screened 57 glioma and 60 healthy sera for autoantibodies against 1827 Escherichia coli expressed clones, including 509 in-frame peptide sequences. By a linear support vector machine approach, we calculated mean specificity, sensitivity, and accuracy of 100 repetitive classifications. We were able to differentiate glioma sera from sera of the healthy controls with a specificity of 90.28%, a sensitivity of 87.31% and an accuracy of 88.84%. We were also able to differentiate World Health Organization grade IV glioma sera from healthy sera with a specificity of 98.45%, a sensitivity of 80.93%, and an accuracy of 92.88%. To rank the antigens according to their information content, we computed the area under the receiver operator characteristic curve value for each clone. Altogether, we found 46 immunogenic clones including 16 in-frame clones that were informative for the classification of glioma sera versus healthy sera. For the separation of glioblastoma versus healthy sera, we found 91 informative clones including 26 in-frame clones. The best-suited in-frame clone for the classification glioma sera versus healthy sera corresponded to the vimentin gene (VIM) that was previously associated with glioma. In the future, autoantibody signatures in glioma not only may prove useful for diagnosis but also offer the prospect for a personalized immune-based therapy.

Novel autoantigens immunogenic in COPD patients.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a respiratory inflammatory condition with autoimmune features including IgG autoantibodies. In this study we analyze the complexity of the autoantibody response and reveal the nature of the antigens that are recognized by autoantibodies in COPD patients. METHODS: An array of 1827 gridded immunogenic peptide clones was established and screened with 17 sera of COPD patients and 60 healthy controls. Protein arrays were evaluated both by visual inspection and a recently developed computer aided image analysis technique. By this computer aided image analysis technique we computed the intensity values for each peptide clone and each serum and calculated the area under the receiver operator characteristics curve (AUC) for each clone and the separation COPD sera versus control sera. RESULTS: By visual evaluation we detected 381 peptide clones that reacted with autoantibodies of COPD patients including 17 clones that reacted with more than 60% of the COPD sera and seven clones that reacted with more than 90% of the COPD sera. The comparison of COPD sera and controls by the automated image analysis system identified 212 peptide clones with informative AUC values. By in silico sequence analysis we found an enrichment of sequence motives previously associated with immunogenicity. CONCLUSION: The identification of a rather complex humoral immune response in COPD patients supports the idea of COPD as a disease with strong autoimmune features. The identification of novel immunogenic antigens is a first step towards a better understanding of the autoimmune component of COPD.

Increased seroreactivity to glioma-expressed antigen 2 in brain tumor patients under radiation.

BACKGROUND: Surgery and radiation are the mainstays of therapy for human gliomas that are the most common primary brain tumors. Most recently, cell culture and animal studies provided the first convincing evidence that radiation not only eliminates tumor cells, but also modulates the immune response and likely improves anti-tumor immunotherapy. METHODOLOGY/PRINCIPAL FINDINGS: We present an in vivo study that analyzes the effects of radiation on the immune response in tumor patients. As readout system, we utilized the reactivity of glioma patients' sera against antigen GLEA2 as the most frequent antigen immunogenic in glioblastoma patients. We established an ELISA assay to analyze reactivity of 24 glioblastoma patients over a period of several months. As control we used 30 sera from healthy donors as well as 30 sera from lung cancer patients. We compared the course of GLEA2 seroreactivity at different times prior, during and after radiation. The GLEA2 seroreactivity was increased by the time of surgery, decreased after surgery, increased again under radiation, and slightly decreased after radiation. CONCLUSIONS/SIGNIFICANCE: Our results provide in vivo evidence for an increased antibody response against tumor antigens under radiation. Antigens that become immunogenic with an increased antibody response as result of radiation can serve as ideal targets for immunotherapy of human tumors.