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Abstract 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 seprated 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.

Abstract 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.

Monoclonal antibodies against the PD-1 receptor or its ligands result in a recovery of T cell responses against tumor antigens. Nivolumab is the first antibody that has been approved in lung cancer. This mode of action is very intersting, especially because of long term responses and the moderate toxicity., (© Georg Thieme Verlag KG Stuttgart · New York.)

Background: Afatinib, an irreversible ErbB family blocker, is approved for treatment of patients with previously untreated non-small cell lung cancer (NSCLC) harboring activating epidermal growth factor receptor (EGFR) mutations. Efficacy of afatinib in EGFR tyrosine kinase inhibitor-naïve (TKI-naïve) patients with uncommon EGFR mutations (other than exon 19 deletions or exon 21 point mutations) has been reported; however, efficacy in TKI-pretreated patients with uncommon EGFR mutations is unknown., Materials and Methods: In the afatinib compassionate use program (CUP), patients with advanced or metastatic, histologically confirmed NSCLC progressing after at least one line of chemotherapy and one line of EGFR-TKI treatment were enrolled. Demographic data, mutation type, response rates, time to treatment failure (TTF), and safety in patients harboring uncommon EGFR mutations were reported., Results: In 60 patients (63% female, median age 63 years [range: 30-84 years]), a total of 66 uncommon EGFR mutations including 30 T790M mutations were reported (18.4% and 11%, respectively, of known EGFR mutations within the CUP). Most patients (67%) received afatinib as third- or fourth-line treatment. Median TTF was 3.8 months (range: 0.2 to >24.6 months; p = .244) in patients with uncommon mutations compared with 5.1 months (range: 0.1 to >21.1 months) in patients with common mutations (n = 165). Pronounced activity was observed with E709X mutations (TTF >12 months). No new safety signals were detected., Conclusion: Afatinib is clinically active and well tolerated in many TKI-pretreated NSCLC patients harboring uncommon EGFR mutations. Compared with results reported in TKI-naïve patients, activity was also indicated in patients with T790M and exon 20 insertion mutations., (©AlphaMed Press.)