Dataset Information

Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer.

ABSTRACT: Mucinous epithelial ovarian cancers are clinically and morphologically distinct from the other histopathologic subtypes of ovarian cancer. Unlike other ovarian subtypes, epidemiologic studies have indicated that tobacco exposure is a significant risk factor for developing mucinous ovarian cancer. Detection of autoantibody reactivity is useful in biomarker discovery and for explaining the role of important pathophysiologic pathways in disease. In order to study if there are specific antibody biomarkers in the plasma samples of mucinous ovarian cancer patients, we have initiated a screen by employing a 'reverse capture antibody microarray' platform that uses native host antigens derived from mucinous ovarian tissues as 'baits' for the capture of differentially labelled patient and control autoantibodies. Thirty-five autoantibodies that were significantly elevated in the cancer plasma samples compared with healthy controls, and six autoantibodies that segregated smoking and non-smoking patients were identified. Functional annotation of the antibody targets has identified nine target antigens involved in integrin and Wnt signalling pathways. Immunohistochemistry of archived ovarian specimens showed significant overexpression of eight of the nine target antigens in mucinous ovarian tumour tissues, suggesting that plasma autoantibodies from mucinous ovarian cancer patients might have heightened reactivities with epitopes presented by these overexpressed antigens. Autoantibody profiling may have an unexpected utility in uncovering key signalling pathways that are dysregulated in the system of interest.

SUBMITTER: Tang L

PROVIDER: S-EPMC2794928 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer.

Tang Liangdan L Yang Junzheng J Ng Shu-Kay SK Rodriguez Noah N Choi Pui-Wah PW Vitonis Allison A Wang Kui K McLachlan Geoffrey J GJ Caiazzo Robert J RJ Liu Brian C-S BC Welch William R WR Cramer Daniel W DW Berkowitz Ross S RS Ng Shu-Wing SW

European journal of cancer (Oxford, England : 1990) 20100101 1

Mucinous epithelial ovarian cancers are clinically and morphologically distinct from the other histopathologic subtypes of ovarian cancer. Unlike other ovarian subtypes, epidemiologic studies have indicated that tobacco exposure is a significant risk factor for developing mucinous ovarian cancer. Detection of autoantibody reactivity is useful in biomarker discovery and for explaining the role of important pathophysiologic pathways in disease. In order to study if there are specific antibody biom ...[more]

PMID: 19926475

Similar Datasets

Project description:ObjectiveMucinous borderline ovarian tumor (mucinous-BOT) and invasive well-differentiated mucinous ovarian cancer (mucinous-OC) are often histopathologically misclassified. The objective of this study was to examine differences in clinico-pathological characteristics and outcomes of these two entities.MethodsThis is a retrospective population-based study examining the Surveillance, Epidemiology, and End Results Program from 1988 to 2000. Stage I mucinous-BOTs and stage I well-differentiated mucinous-OC were compared for patient demographics, tumor characteristics, and outcomes. Propensity score matching and multivariable analysis were used to assess cause-specific survival (CSS).ResultsA total of 2130 mucinous-BOT and 581 mucinous-OC cases were examined for analysis. On multivariable analysis, women with mucinous-OC were more likely to be older, Eastern U.S. residents, and have undergone hysterectomy or lymphadenectomy compared to those with mucinous-BOT, and the number of women diagnosed with mucinous-OC decreased over time (all, P < 0.05). Mucinous-OCs were more likely to be stage T1c and have a smaller tumor size as compared to mucinous-BOT (both, adjusted-P < 0.05). After propensity score matching, women with mucinous-OC had significantly poorer CSS compared to those with mucinous-BOT on multivariable analysis (10-year rates: 92.7% versus 97.5%, adjusted-hazard ratio [HR] 2.03, P = 0.007). Similar results were observed among subgroups for reproductive age, stage T1a disease, large tumor, and unstaged cases (all, P < 0.05).ConclusionStage I mucinous-BOT and stage I invasive well-differentiated mucinous-OC have distinct differences in clinical characteristics and patient survival. The inability to conduct centralized pathology review in our study limits our conclusions given the recognized issue of misclassification of mucinous-BOT and mucinous-OC, but further highlights the importance of making the proper histopathological diagnosis for invasive cancer when the ovarian tumor is of mucinous histology.

Project description:Background: Programmed cell death protein 1 (PD1) inhibitors have revolutionized cancer therapy, yet many patients fail to respond. Thus, the identification of accurate predictive biomarkers of therapy response will improve the clinical benefit of anti-PD1 therapy. Method: We assessed the baseline serological autoantibody (AAb) profile against ~2300 proteins in 10 samples and ~4600 proteins in 35 samples with alveolar soft part sarcoma (ASPS), non-small-cell lung cancer (NSCLC) and lymphoma using Nucleic Acid Programmable Protein Arrays (NAPPA). 23 selected potential AAb biomarkers were verified using simple, affordable and rapid enzyme linked immune sorbent assay (ELISA) technology with baseline plasma samples from 12 ASPS, 16 NSCLC and 46 lymphoma patients. SIX2 and EIF4E2 AAbs were further validated in independent cohorts of 17 NSCLC and 43 lymphoma patients, respectively, using ELISA. The IgG subtypes in response to therapy were also investigated. Results: Distinct AAb profiles between ASPS, NSCLC and lymphoma were observed. In ASPS, the production of P53 and PD1 AAbs were significantly increased in non-responders (p=0.037). In NSCLC, the SIX2 AAb was predictive of response with area under the curve (AUC) of 0.87, 0.85 and 0.90 at 3 months, 4.5 months, 6 months evaluation time points, respectively. In the validation cohort, the SIX2 AAb was consistently up-regulated in non-responders (p=0.024). For lymphoma, the EIF4E2 AAb correlated with a favorable response with AUCs of 0.68, 0.70, and 0.70 at 3 months, 4.5 months, and 6 months, respectively. In the validation cohort, the AUCs were 0.74, 0.75 and 0.66 at 3 months, 4.5 months, and 6 months, respectively. The PD1 and PD-L1 IgG2 AAbs were highly produced in ~20% of lymphoma responders. Furthermore, bioinformatics analysis revealed antigen functions of these AAb biomarkers. Conclusion: This study provides the first evidence that AAb biomarkers selected using high-throughput protein microarrays can predict anti-PD1 therapeutic response and guide anti-PD1 therapy.

Dataset Information

Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer.

Publications

Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets