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Background To investigate the expression and diagnostic value of seven autoantibodies (P53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGE, and CACE) in lung cancer patients. Methods A total of 370 patients were admitted to the Thoracic Surgery of the First Affiliated Hospital of Suzhou University from 2017 to 2019, including 305 patients with lung cancer and 65 patients with benign lesions. The concentrations of the seven autoantibodies were determined by enzyme linked immunosorbent assay (ELISA).The expression levels of each antibody were compared between the two groups, and the levels of each antibody between lung cancer patients with different pathological types were also compared. We aimed to analyze the diagnostic efficiency of single antibody detection combined with seven antibodies, and also to explore whether there were differences among the positive rates of each antibody in sex, age, smoking history, pathological classification, and clinical stages in the lung cancer group. Results The expression levels of seven autoantibodies in the lung cancer group were higher than those in the benign lesion group. In the lung cancer group, the expression levels of the seven autoantibodies did not vary statistically among different pathological types. The area under the curve of combined detection of the seven antibodies reached 0.735, and the Y-index reached 0.35, which was higher than that of single antibody detection. P53 exhibited the highest sensitivity and lowest specificity; meanwhile, PGP9.5, SOX2, GAGE7, GBU4-5, and MAGEA1 exhibited low sensitivity and high specificity. The sensitivity and specificity of the CAGE were approximately 60%, respectively. There was no statistical difference in the positive rate of each antibody in age, smoking history, and clinical stage. The positive rate of MAGEA1 and CAGE was statistically different in sex, and the positive rate of MAGEA1 was statistically different in pathological classification. Conclusions The seven autoantibodies of lung cancer can potentially be used as an auxiliary examination method for the early diagnosis of lung cancer.

Primary mediastinal germ cell tumors (PMGCT) represent a rare but sometimes highly aggressive type of mediastinal tumors. The current prognostic models for PMGCT are insufficient. This study was undertaken to establish and validate an individualized nomogram for predicting the overall survival (OS) of patients with PMGCT.We conducted a retrospective analysis of patients with PMGCT diagnosed between 2000 and 2018 in the Surveillance, Epidemiology, and End Results (SEER) database in the United States. Clinical variables included surgery subtype, gender, treatment regimens, age, histology, tumor size, stage, chemotherapy, radiation, race, and survival-related information. The main outcome measure was survival duration. The Kaplan-Meier method along with the log-rank test were utilized to estimate the OS. Independent prognostic factors were identified by performing the univariate and multivariate Cox proportional hazards regression analyses, from which an individualized nomogram was constructed to predict 3-, 5-, and 10-year OS of patients with PMGCT. The concordance index (C-index) and calibration curve were used to verify the discrimination and accuracy of the nomogram.A total of 845 patients with PMGCT were recruited from the SEER database and further randomly assigned to a training set (n=635) and a validation set (n=210) at a ratio of 7:3. The 3-, 5-, and 10-year OS for overall PMGCT was 70.0%, 67.1%, and 63.9%, respectively. Cox regression analysis indicated that age, tumor size, stage, chemotherapy, radiation, histology, and surgery type were as independent factors for OS in patients with PMGCT (P0.05). An individualized nomogram for OS was constructed utilizing these variables, with the C-index of 0.714 [95% confidence interval (CI): 0.695 to 0.743] and 0.756 (95% CI: 0.735 to 0.787) in the training and validation groups. Moreover, good levels of agreement were observed according to the calibration curve between the predicted and actual 3-, 5-, and 10-year survival rates both in the training and validated cohorts, showing that the model could accurately predict patient prognosis.This study documented the first attempt at establishing and validating a novel nomogram for predicting the 3-, 5-, and 10-year OS probabilities of PMGCT. The prognostic nomogram was demonstrated to have good performance for predicting individualized OS of patients with PMGCT.