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Identification of Novel Autoantibodies for Detection of Malignant Mesothelioma
Authors:Xufei Zhang  Weike Shen  Xiaomin Dong  Jiangping Fan  Lixia Liu  Xu Gao  Kemp H. Kernstine  Li Zhong
Affiliation:1. Department of Cell Biology, Hebei University College of Life Sciences, Baoding, Hebei, P.R.China.; 2. University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America.; 3. Division of Thoracic Surgery, UT Southwestern Medical Center, Dallas, Texas, United States of America.; 4. Department of Basic Medical Sciences, Western University of Health Sciences, Pomona, California, United States of America.; King''s College London, United Kingdom,
Abstract:

Background

The malignant mesothelioma (MM) survival rate has been hampered by the lack of efficient and accurate early detection methods. The immune system may detect the early changes of tumor progression by responding with tumor-associated autoantibody production. Hence, in this study, we translated the humoral immune response to cancer proteins into a potential blood test for MM.

Methodology/Principal Findings

A T7 phage MM cDNA library was constructed using MM tumor tissues and biopanned for tumor-associated antigens (TAAs) using pooled MM patient and normal serum samples. About 1008 individual phage TAA clones from the biopanned library were subjected to protein microarray construction and tested with 53 MM and 52 control serum samples as a training group. Nine candidate autoantibody markers were selected from the training group using Tclass system and logistic regression statistical analysis, which achieved 94.3% sensitivity and 90.4% specificity with an AUC value of 0.89 in receiver operating characteristic analysis. The classifier was further evaluated with 50 patient and 50 normal serum samples as an independent blind validation, and the sensitivity of 86.0% and the specificity of 86.0% were obtained with an AUC of 0.82. Sequencing and BLASTN analysis of the classifier revealed that five of these nine candidate markers were found to have strong homology to cancer related proteins (PDIA6, MEG3, SDCCAG3, IGHG3, IGHG1).

Conclusions/Significance

Our results indicated that using a panel of 9 autoantibody markers presented a promising accuracy for MM detection. Although the results need further validation in high-risk groups, they provided the potentials in developing a serum-based assay for MM diagnosis.
Keywords:
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