Five tumor-associated autoantibodies expression levels in serum predict lung cancer and associate with poor outcome

血清中五种肿瘤相关自身抗体的表达水平可预测肺癌并与不良预后相关

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作者:Shaolei Li #, Yuanyuan Ma #, Ying Xiong #, Panpan Zhang, Xiao Wang, Yong Wang, Yue Yang

Background

This study aims to evaluate diagnostic feasibility of the tumor-associated autoantibodies and their clinical significance in lung cancer.

Conclusions

Summarily, autoantibodies levels of GAGE7, MAGEA1, PGP9.5, CAGE and p53 in serum could be used for the diagnosis of lung cancer and PGP9.5 may predict poor prognosis for the patients with lung cancer.

Methods

Blood samples were collected from 352 lung cancer patients and 226 healthy individuals. Immunohistochemical staining was used to evaluate the expression of autoantibodies in 69 cases of lung cancer tissues. Enzyme-linked immunosorbent assay (ELISA) was performed to measure the five autoantibodies levels in serum from lung cancer patients and healthy controls.

Results

Higher expression of GAGE7, MAGEA1, PGP9.5, CAGE and p53 were found in lung cancer tissues than normal tissues from the cancer genome atlas (TCGA) database. The expression levels of the five tumor-associated autoantibodies in lung cancer tissues were positively associated with those statuses in serum. There were significantly higher levels of each autoantibody in lung cancer patients than healthy individuals. The area under curve (AUC) for GAGE7, MAGEA1, PGP9.5, CAGE and p53 in diagnosis of lung cancer were 0.787, 0.641, 0.873, 0.825 and 0.749, respectively. With combination of these five autoantibodies by the logistic regression model, 0.891 of AUC was shown. In addition, the level of each autoantibody was increased in the advanced stage. Particularly, the level of PGP9.5 was significantly higher in the advanced T stage, N stage and TNM stage and CAGE was significantly elevated in the advanced N stage. Conclusions: Summarily, autoantibodies levels of GAGE7, MAGEA1, PGP9.5, CAGE and p53 in serum could be used for the diagnosis of lung cancer and PGP9.5 may predict poor prognosis for the patients with lung cancer.

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