Identification and utilization of autologous anti-tumor antibodies for the diagnosis and prognosis of cancer
Embargo Lift Date: 2018-01-29
Güre, Ali Osmay
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Lung cancer is the leading cause of cancer related death worldwide. Current diagnostic methods have limited power and unable to extend patient life significantly. SCLC; the most aggressive subtype of lung cancer is an immunogenic cancer type and able to elicit an immune response of which autologous antibodies are a measurable component. These antibodies are elicited even when the tumor is microscobic and impossible to be diagnosed clinically by the current methods of diagnosis thus antibodies can be utilized for early diagnosis. We aimed to develop a method to identify novel autologous antibodies, identify these antibodies for SCLC, Colorectal, Gastric and Ovarian cancers and validate these antibodies for SCLC diagnosis and prognosis and investigate their utility for autoimmune disease. We have developed and optimized PA screening for novel autologous antibody discovery. We have screened PA with serum pools of cancer patients (SCLC, Colorectal, Gastric and Ovarian), BD and healthy controls since PAs have many advantages compared to other discovery methods like SEREX. We have also performed sensitivity and specificity evaluations by screening custom PAs by individual sera. Image analysis softwares developed by collaboration utilized for evaluation of the screenings. The filtered valuable clones were ordered from the PA manufacturer and HisTagged protein expression and purification was performed with these clones. Pure proteins were screened with 3 independent SCLC and 2 Healthy control cohorts by an iterative ELISA approach for validation of these antibodies as valuable biomarkers. ELISA results were also confirmed by Western blotting. Monte Carlo, SVM and PC were utilized for cut-off determination, panel formation and ROC plotting. AUC was compared for evaluation of diagnostic power. Kaplan-Meier, UCR and MCR analysis was performed for prognostic analysis of the valuable antibodies. Seperately protein expression and autologous antibody presence correlation was evaluated by comparison of IHC and ELISA. The same autologous antibody identification strategy was utilized as a collaborative support for an independent study for identification of NBD specific biomarkers.We have identified 23 distinct autologous antibody biomarkers for SCLC after evaluation of PA and custom PA screenings. For 8 of these antibodies we have completed ELISA screening for all 3 SCLC and 2 healthy control cohorts. 6 of these autologous antibodies were shown to be valuable as a panel for SCLC diagnosis both by MC and SVM. Utilization of 4 of these antibodies; SOX2, p53, POLB and C11orf20, as a panel resulted in superior AUC thus high sensitivity and specificity values (55% sensitivity, 90% specificity). PC method resulted in higher AUC even only by combination of SOX2 and p53 (82% sensitivity, 90% specificity). Although individual correlations were identified, we were unable to show a significant correlation of seropositivity with survival for any of the antibodies which is common to all cohorts. We have identified a significant correlation between SOX2 antigen expression intensity and autologous antibody presence. Mtch1 was identified as a NBD specific autologous antibody by the utilization of our autologous antibody discovery and validation methodology. We were able to identify a panel of 4 antibodies; SOX2, p53, POLB and C11orf20, which resulted in 55% sensitivity at 90% specificity for SCLC. 2 of these antibodies were identified by this study as novel biomarkers; POLB and C11orf20. The panel is capable of exceeding the diagnostic power of the only commercially available diagnostic kit; EarlyCDT-Lung. PC method is very promising since a sensitivity value of 82% was reached at 90% specificity which is a diagnostic power comparable that of low-dose CT. As a future perspective we are planning to apply PC method to all the PA data and develop a kit based on this method to be utilized for SCLC diagnosis.