Objective To study the expressions and clinical significance of matrix metalloproteinases-2(MMP-2) and vascular endothelial growth factor-C(VEGF-C) in patients with papillary thyroid carcinoma(PTC).Methods SP immunohistochemical technique was used to detect the expressions of MMP-2 and VEGF-C in 78 cases of PTC and 18 cases of thyroid benign tumors.Results The positive expression rates of MMP-2 and VEGF-C in PTC(80.77%,75.64%) were significantly higher than those of the thyroid benign tumor(11.11%,22.22%),P

AIM: To predict MHC class Ⅰ binding peptides by using neural network ensembles. METHODS: As a combination of neural networks, neural network ensemble (NNE) was here used to improve the predictive performance. Based on a database of 628 nonamers and their classified binding capacities, the generalized NNEs were used to classify peptides respectively with non, low, moderate and high binding capacities to MHC class I molecule encoded by gene HLA-A*0201. The predictive power of NNE was further evaluated by running generalized NNE on a set of actual T-cell epitopes. RESULTS: The generalized NNEs achieved an average predictive hit rate of 0.8 for the above classifications. In addition, NNE was also efficient in the prediction of the potential T-cell epitopes, and about 84% of the actual T-cell epitopes were among the potentially antigenic peptides with high and moderate affinities. CONCLUSION: The NNEs can be applied in the prediction of MHC class Ⅰ binding peptides, and moreover, after proper modifications, they can be conveniently extended to cover peptides with any length and thus suitable for the prediction of peptides binding to other MHC class Ⅰ or even class Ⅱ molecules.

OBJECTIVE: To evaluate the expression and prognostic value of superoxide dismutase 2 (SOD2) in breast cancer and explore its possible role in the occurrence and progression of breast cancer. METHODS: We performed bioinformatics analysis of the TCGA data for the expression and clinical relevance of SOD2 in patients with breast cancer. Gene enrichment analysis (GSEA) was performed using the KEGG gene set, the protein interaction network was constructed using the STRING database, and the key genes were screened using Cytoscape software. We also collected 60 pairs of primary breast cancer tissue samples and adjacent samples for detecting SOD2 expressions using immunohistochemistry and RT-qPCR and analyzed the correlation of SOD2 expression with the clinicopathological parameters of the patients. RESULTS: The expression of SOD2 was significantly lower in breast cancer tissue than in adjacent tissues with significant correlation with TNM stage and axillary lymph node metastasis ( < 0.05). Kaplan-Meier survival analysis showed that the recurrence-free survival, distant metastasis-free survival (RFS) and post-progressive survival were significantly shorted in patients with high SOD2 expression than in those with low SOD2 expression ( < 0.05). GSEA enrichment analysis indicated that SOD2 played an important role in the JAK-STAT signaling pathway. IL10 and STAT4 were identified as the key genes in the PPI network, and they were both positively correlated with SOD2. In the 60 pairs of clinical samples, SOD2 was highly expressed in breast cancer tissues with close correlation with axillary lymph node metastasis and the expressions of estrogen receptor and androgen receptor ( < 0.05). CONCLUSIONS The expression of SOD2 in breast cancer is significantly correlated with TNM stage and axillary lymph node metastasis. SOD2 may affect the proliferation, invasion and metastasis of breast cancer cells possibly by regulating IL10 and/or STAT4 to affect the JAK/STAT signaling pathway.
Breast Neoplasms ; Humans ; Lymphatic Metastasis ; Prognosis ; Superoxide Dismutase

Goiter, Nodular ; diagnosis ; Humans ; Thoracic Wall ; pathology

OBJECTIVE: To study the expression of G9a in human breast cancer, its association with the clinicopathological characteristics of breast cancer, and its effect on the proliferation of breast cancer cells. METHODS: A total of 122 specimens of breast cancer tissues and 61 adjacent normal tissues resected between October, 2016 and October, 2017 were obtained from the Tissue Bank of Ningxia Medical University General Hospital. Immunohistochemistry and real-time PCR were used to detect the expression of G9a in the breast cancer tissues. The relationship of G9a with the clinicopathological features of the patients, molecular subtypes of breast cancer and the immunohistochemical markers was analyzed. A bioinformatics approach was used to analyze the expression of G9a in breast tissues and its association with the prognosis of the patients with breast cancer. UNC0631, a G9a inhibitor, was used to investigate the effect of G9a on the proliferation of breast cancer cells . RESULTS: The results of immunohistochemical study, real-time PCR and bioinformatics analysis showed that G9a was highly expressed in human breast cancer tissues. G9a was highly expressed in breast invasive ductal carcinoma, and its expression was negatively correlated with age ( < 0.05). Her-2-overexpressing breast cancer showed high expressions of G9a, which was positively correlated with the expressions of Her-2, Ki-67 and E-cadherin ( < 0.05). Bioinformatics analysis suggested that a high G9a expression was an independent risk factor for poor prognosis of breast cancer. In cultured breast cancer cells, the application of the G9a inhibitor significantly inhibited the cell proliferation. CONCLUSIONS G9a is highly expressed in breast cancer tissues to promote the development and progression of breast cancer. A high G9a expression is an independent risk factor for poor prognosis of breast cancer, and G9a may serve as a new target for early diagnosis and treatment of breast cancer.
Breast Neoplasms ; Cell Proliferation ; Disease Progression ; Female ; Humans ; Immunohistochemistry ; Prognosis