Identification of alpha-enolase as an autoantigen in lung cancer: Its overexpression is associated with clinical outcomes

Purpose: Although existence of humoral immunity has been previously shown in malignant pleural effusions, only a limited number of immunogenic tumor-associated antigens (TAA) have been identified and associated with lung cancer. In this study, we intended to identify more TAAs in pleural effusion-derived tumor cells. Experimental Design: Using morphologically normal lung tissues as a control lysate in Western blotting analyses, 54 tumor samples were screened with autologous effusion antibodies. Biochemical purification and mass spectrometric identification of TAAs were done using established effusion tumor cell lines as antigen sources. We identified a p48 antigen as of-enolase (ENO1). Semiquantitative immunohistochemistry was used to evaluate expression status of ENO1 in the tissue samples of 80 patients with non-small cell lung cancer (NSCLC) and then correlated with clinical variables. Results: Using ENO1-specifc antiserum, up-regulation of ENO1 expression in effusion tumor cells from 11 of 17 patients was clearly observed compared with human normal lung primary epithelial and non-cancer-associated effusion cells. Immunohistochemical studies consistently showed high level of ENO1 expression in all the tumors we have examined thus far. Log-rank and Cox's analyses of ENO1 expression status revealed that its expression level in primary tumors was a key factor contributing to overall- and progression-free survivals of patients (P < 0.05). The same result was also obtained in the early stage of NSCLC patients, showing that tumors expressing relatively higher ENO1 level were tightly correlated with poorer survival outcomes. Conclusions: Our data strongly support a prognostic role of ENO1 in determining tumor malignancy of patients with NSCLC

Designing a recurrent neural network-based controller for gyro-mirror line-of-sight stabilization system using an artificial immune algorithm

10.1007/978-3-540-72377-6_8Studies in Computational Intelligence66189-20