Dataset Information

Combined detection of dickkopf-1 subtype classification autoantibodies as biomarkers for the diagnosis and prognosis of non-small cell lung cancer.

ABSTRACT: PURPOSE:This study aims to identify the clinical significance of serum autoantibodies against dickkopf-1 (DKK1) and evaluate their feasibility in the immunodiagnosis and prognosis of non-small cell lung cancer (NSCLC). EXPERIMENTAL DESIGN:Epitope mapping by peptide microarray-based serum screening of NSCLC patients (n=72) and healthy controls (n=16) was performed. Indirect ELISA with peptides was used to measure the serum levels of autoantibodies in 206 NSCLC patients and 99 healthy controls. A 3-year follow-up was monitored to evaluate the correlation between serological levels of autoantibodies and overall survival (OS) and progression-free survival (PFS). RESULTS:Four highly reactive epitopes were identified, which included peptides 67-84 (Pep A), 37-54 (Pep B), 145-156 (Pep C) and 247-261 (Pep D). The autoantibodies levels were considerably higher in sera of NSCLC patients compared with controls (P<0.001), and a highly significant correlation with distant metastases was observed (Pep A: P=0.09, Pep B: P<0.01, Pep C: P<0.01 and Pep D: P<0.01). High levels of antibody subtype to Pep B were remarkably associated with better OS (P=0.004) and PFS (P=0.006). Subsequent Cox regression analysis disclosed that antibody to Pep B was an independent prognostic factor for NSCLC (OS: P=0.008, HR =0.435, 95% CI 0.236-0.802; PFS: P=0.032, HR =0.533, 95% CI 0.322-0.950). CONCLUSION:Identified linear epitopes of antigens by peptide microarray are easily available, and subtype classification of DKK1 autoantibodies as novel biomarkers for the diagnosis and prognosis of NSCLC. Our results also highlight the antibody subtype to Pep B as the most valuable biomarker for favorable prognosis of NSCLC.

SUBMITTER: Shen L

PROVIDER: S-EPMC5530063 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Combined detection of dickkopf-1 subtype classification autoantibodies as biomarkers for the diagnosis and prognosis of non-small cell lung cancer.

Shen Lei L Wu Xiaoguang X Tan Jinjing J Gu Meng M Teng Yu Y Wang Zitong Z Yue Wentao W

OncoTargets and therapy 20170718

<h4>Purpose</h4>This study aims to identify the clinical significance of serum autoantibodies against dickkopf-1 (DKK1) and evaluate their feasibility in the immunodiagnosis and prognosis of non-small cell lung cancer (NSCLC).<h4>Experimental design</h4>Epitope mapping by peptide microarray-based serum screening of NSCLC patients (n=72) and healthy controls (n=16) was performed. Indirect ELISA with peptides was used to measure the serum levels of autoantibodies in 206 NSCLC patients and 99 healt ...[more]

PMID: 28790847

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Project description:Molecular biology studies show that RNA N6-methyladenosine (m6A) modifications may take part in the incidence and development of idiopathic pulmonary fibrosis (IPF). Nonetheless, the roles of m6A regulators in IPF are not fully demonstrated. In this study, 12 significant m6A regulators were filtered out between healthy controls and IPF patients using GSE33566 dataset. Random forest algorithm was used to identify 11 candidate m6A regulators to predict the incidence of IPF. The 11 candidate m6A regulators included leucine-rich PPR motif-containing protein (LRPPRC), methyltransferase-like protein 3, FTO alpha-ketoglutarate dependent dioxygenase (FTO), methyltransferase-like 14/16, zinc finger CCCH domain-containing protein 13, protein virilizer homolog, Cbl proto-oncogene like 1, fragile X messenger ribonucleoprotein 1 and YTH domain containing 1/2. A nomogram model was constructed based on 11 candidate m6A regulators and considered beneficial to IPF patients using decision curve analysis. Consensus clustering method was used to distinctly divide IPF patients into two m6A patterns (clusterA and clusterB) based on 12 significant m6A regulators. M6A scores of all IPF patients were obtained using principal component analysis to quantify the m6A patterns. Patients in clusterB had higher m6A scores than those in clusterA. Furthermore, patients in clusterB were correlated with Th17 and Treg cell infiltration, innate immunity and Th1 immunity, while those in clusterA were correlated with adaptive immunity and Th2 immunity. Patients in clusterB also had higher expressions of mesenchymal markers and regulatory factors of fibrosis but lower expressions of epithelial markers. Lastly and interestingly, two m6A regulators, LRPPRC (p = 0.011) and FTO (p = 0.042), were identified as novel prognostic genes in IPF patients for the first time using an external GSE93606 dataset. Both of them had a positive correlation with a better prognosis and may serve as therapy targets. Thus, we conducted virtual screening to discover potential drugs targeting LRPPRC and FTO in the treatment of IPF. In conclusion, m6A regulators are crucial to the onset, development and prognosis of IPF. Our study on m6A patterns may provide clues for clinical diagnosis, prognosis and targeted therapeutic drugs development for IPF.

Dataset Information

Combined detection of dickkopf-1 subtype classification autoantibodies as biomarkers for the diagnosis and prognosis of non-small cell lung cancer.

Publications

Combined detection of dickkopf-1 subtype classification autoantibodies as biomarkers for the diagnosis and prognosis of non-small cell lung cancer.

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