Oral exposure to an acceptable daily intake dose of aspartame induced a delayed proinflammatory cytokine response in the cerebrospinal fluid of rats.

This study aimed to investigate the effect of exposure to aspartame (ASP) at safe levels on proinflammatory cytokines in the cerebrospinal fluid (CSF) of rats. Sprague Dawley rats were sacrificed after 1, 2, 4 or 8 week(s) of continuous exposure to ASP (40 mg/kg body weight). Serum, CSF and brain tissue samples were prepared, and the levels of the IL-1ß, IL-6 and TNF-α were analyzed by ELISA. In serum, the levels of all three cytokines showed a two-phase alteration, a decrease followed by an increase in the ASP group. In the brain, their levels increased from the second or fourth week compared with the control group. In CSF, the levels of these cytokines showed a similar change to that in brain tissue, but the increase appeared at a later time point. For each cytokine, there was a significant positive correlation between its levels in serum, brain tissue and CSF. This is the first discovery that ASP exposure increased the levels of proinflammatory cytokines in CSF in rats, which emerged later than in blood and brain tissue. This study suggests the necessity of conducting related clinical studies to evaluate potential neuroinflammatory effects induced by chronic ASP exposure through CSF analysis.

Identification and validation of a novel prognostic signature based on transcription factors in breast cancer by bioinformatics analysis.

Background: Breast cancer (BRCA) is the leading cause of cancer mortality among women, and it is associated with many tumor suppressors and oncogenes. There is increasing evidence that transcription factors (TFs) play vital roles in human malignancies, but TFs-based biomarkers for BRCA prognosis were still rare and necessary. This study sought to develop and validate a prognostic model based on TFs for BRCA patients. Methods: Differentially expressed TFs were screened from 1,109 BRCA and 113 non-tumor samples downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis was used to identify TFs associated with overall survival (OS) of BRCA, and multivariate Cox regression analysis was performed to establish the optimal risk model. The predictive value of the TF model was established using TCGA database and validated using a Gene Expression Omnibus (GEO) data set (GSE20685). A gene set enrichment analysis was conducted to identify the enriched signaling pathways in high-risk and low-risk BRCA patients. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the TF target genes were also conducted separately. Results: A total of 394 differentially expressed TFs were screened. A 9-TF prognostic model, comprising PAX7, POU3F2, ZIC2, WT1, ALX4, FOXJ1, SPIB, LEF1 and NFE2, was constructed and validated. Compared to those in the low-risk group, patients in the high-risk group had worse clinical outcomes (P<0.001). The areas under the curve of the prognostic model for 5-year OS were 0.722 in the training cohort and 0.651 in the testing cohort. Additionally, the risk score was an independent prediction indicator for BRCA patients both in the training cohort (HR =1.757, P<0.001) and testing cohort (HR =1.401, P=0.001). It was associated with various cancer signaling pathways. Ultimately, 9 overlapping target genes were predicted by 3 prediction nomograms. The GO and KEGG enrichment analyses of these target genes suggested that the TFs in the model may regulate the activation of some classical tumor signaling pathways to control the progression of BRCA through these target genes. Conclusions: Our study developed and validated a novel prognostic TF model that can effectively predict 5-year OS for BRCA patients.

Tumor size rather than the thyroid invasion affects the prognosis of parathyroid carcinoma without lymph node or distant metastasis.

PURPOSE: This study aimed to explore the prognostic value of thyroid invasion of parathyroid carcinoma without lymph node or distant metastasis. METHODS: Two hundred and nine cases of parathyroid carcinoma from the SEER (1989-2014) were eligible for this study. A Chi-squared test, t test, X-tile, Kaplan-Meier curves, and multivariate Cox proportional hazard regression were used for analysis. RESULTS: Thyroid invasion, sex, race, age, radiation, and surgery were not significantly associated with cancer-specific survival by multivariate analysis. However, tumor size ≥ 4 cm was significantly associated with worse cancer-specific survival (P < 0.001). CONCLUSION: Thyroid invasion, which was the criterion for T1 and T2 staging criteria of parathyroid carcinoma according to the AJCC, did not affect the prognosis of patients with parathyroid carcinoma without local lymph node or distant metastasis. Our study indicates that a tumor size ≥ 4 cm may be an appropriate indicator of T1 and T2 cancer staging.

MicroRNA-1246 suppresses the metastasis of breast cancer cells by targeting the DYRK1A/PGRN axis to prevent the epithelial-mesenchymal transition.

OBJECTIVE: Breast cancer is one of the most common malignant and highly heterogeneous tumors in women. MicroRNAs (miRNAs), such as miR-1246, play important roles in various types of malignant cancers, including triple-negative breast cancer (TNBC). However, the biological role of miR-1246 in TNBC has not yet been fully elucidated. In this study, we studied the role of miR-1246 in the occurrence and development of TNBC and its mechanism of action. METHODS: Cell Counting Kit-8 (CCK-8), wound healing, and Transwell assays were performed to observe the effects of miR-1246 on TNBC cell proliferation, migration, and invasion, respectively. The expression of epithelial-mesenchymal transition (EMT) markers was detected by western blotting. Dual luciferase reporter assays were performed to determine whether DYRK1A is a novel target of miR-1246. In addition, an immunoprecipitation experiment was performed to verify the binding of DYRK1A to PGRN. Rescue experiments were performed to determine whether DYRK1A is a novel target of miR-1246 and whether miR-1246 suppresses the metastasis of breast cancer cells by targeting the DYRK1A/PGRN axis to prevent the epithelial-mesenchymal transition. RESULTS: Our results show that miR­1246 suppresses the proliferation, migration, and invasion of TNBC cells, DYRK1A is a novel target of miR-1246 and Importin-8 mediated miR-1246 nuclear translocation. MiR­1246 plays a suppressive role in the regulation of the EMT of TNBC cells by targeting DYRK1A. DYRK1A mediates the metastasis of triple-negative breast cancer via activation of the EMT. We identified PGRN as a novel DYRK1A-interacting protein. Overexpression of PGRN and DYRK1A promoted cell proliferation and migration of TNBC, but this effect was reversed by co-expression of miR-1246 mimics.DYRK1A and PGRN act together to regulate the occurrence and development of breast cancer through miR-1246. CONCLUSION: MiR-1246 suppresses the metastasis of breast cancer cells by targeting the DYRK1A/PGRN axis and preventing the epithelial-mesenchymal transition. The MiR-1246/DYRK1A/PGRN axis regulates TNBC progression, suggesting that MiR-1246 could be promising therapeutic targets for the treatment of TNBC.

Role of primary tumor resection in patients with metastatic medullary thyroid cancer who have unresectable distant metastases.

BACKGROUND: Whether patients with medullary thyroid carcinoma (MTC) who have unresectable synchronous distant metastases should undergo primary surgical resection (PTR) remains controversial. This study aimed to identify predictive factors associated with the survival of such patients. METHODS: We conducted a retrospective study of patients with MTC who were registered in the Surveillance, Epidemiology, and End Results registry. The overall and cancer-specific mortality rates were assessed using risk-adjusted Cox proportional hazards regression modeling and stratified propensity score matching. RESULTS: One hundred and eight matched patients were assessed. Patients in the PTR group had lower overall mortality than did those in the non-PTR group. The 1-, 3-, and 5-year overall and cancer-specific survival rates in the PTR group were significantly higher. CONCLUSIONS: PTR appears to be the most appropriate intervention for patients with good performance status. Such patients are likely to benefit from surgery and to experience long-term stable disease.

Integrated Profiling Identifies CCNA2 as a Potential Biomarker of Immunotherapy in Breast Cancer.

INTRODUCTION: Breast cancer is the main reason for cancer-related deaths in women and the most common malignant cancer among women. In recent years, immunosuppressive factors have become a new type of treatment for cancer. However, there are no effective biomarkers for breast cancer immunotherapy. Therefore, exploring immune-related biomarkers is presently an important topic in breast cancer. METHODS: Gene expression profile data of breast cancer from The Cancer Genome Atlas (TCGA) was downloaded. Scale-free gene co-expression networks were built with weighted gene co-expression network analysis. The correlation of genes was performed with Pearson's correlation values. The potential associations between clinical features and gene sets were studied, and the hub genes were screened out. Gene Ontology and gene set enrichment analysis were used to reveal the function of hub gene in breast cancer. The gene expression profiles of GSE15852, downloaded from the Gene Expression Omnibus database, were used for hub gene verification. In addition, candidate biomarkers expression in breast cancer was studied. Survival analysis was performed using Log rank test and Kaplan-Meier. Immunohistochemistry was used to analyze the expression of CCNA2. RESULTS: A total of 6 modules related to immune cell infiltration were identified via the average linkage hierarchical clustering. According to the threshold criteria (module membership >0.9 and gene significance >0.35), a significant module consisting of 13 genes associated with immune cells infiltration were identified as candidate hub genes after performed with the human protein interaction network. And 3 genes with high correlation to clinical traits were identified as hub genes, which were negatively associated with the overall survival. Among them, the expression of CCNA2 was increased in metastatic breast cancer compare with non-metastatic breast cancer, who underwent immunotherapy. Immunohistochemistry results showed that CCNA2 expression in carcinoma tissues was elevated compared with normal control. DISCUSSION: CCNA2 identified as a potential immune therapy marker in breast cancer, which were first reported here and deserved further research.

MicroRNA-200c Inhibits the Metastasis of Triple-Negative Breast Cancer by Targeting ZEB2, an Epithelial-Mesenchymal Transition Regulator.

OBJECTIVE: Triple-negative breast cancer (TNBC) is one of the most common malignant, highly heterogeneous tumors in women. MicroRNAs (miRNAs), such as miR-200c, play an important role in various types of malignant cancer, including TNBC. However, the biological role of miRNA-200c in TNBC is not well understood. In this study, we investigated the mechanism of miR-200c in the growth of TNBC. METHODS: Reverse transcription quantitative polymerase chain reaction was used to detect the expression of miR-200c in TNBC tissues and TNBC cells. Cell Counting Kit-8 (CCK-8) assays, wound healing, and transwell assays were used to observe the effects of miR-200c on TNBC cell proliferation, migration, and invasion, respectively. The expression of epithelial-mesenchymal transition (EMT) markers were detected by Western blotting. Dual luciferase reporter assays were used to test whether ZEB2 is a novel target of miR-200c. RESULT: Our results show that ZEB2 is a novel target of miR-200c and that ZEB2 mediates the metastasis of triple-negative breast cancer via EMT. CONCLUSION: miR-200c attenuates TNBC cell invasion and EMT by targeting ZEB2. Our data therefore suggest that miR-200c may be used to develop novel early-stage diagnostic and therapeutic strategies for TNBC.

lncRNA TCL6 correlates with immune cell infiltration and indicates worse survival in breast cancer.

BACKGROUND: Long non-coding RNA (lncRNA) T-cell leukemia/lymphoma 6 (TCL6) has been reported as a potential tumor suppressor. However, its expression and function in breast cancer remain unknown. This study was performed to investigate the expression of lncRNA TCL6 in breast cancer and its clinical significance. METHODS: The survival and clinical molecular roles of TCL6 in breast cancer were analyzed. The underlying mechanism modulated by TCL6 and its correlation with immune-infiltrating cells were investigated. Gene Expression Omnibus (GEO) datasets were further used to confirm the prognostic role of TCL6. RESULTS: TCL6 low expression was not correlated with age, clinical stage, T stage, lymph node metastasis, distant metastasis, human epidermal growth factor 2 status, but was associated with estrogen receptor and progesterone receptor (PR) status and was an independent factor for worse survival (HR 1.876, P = 0.016). Specifically, low TCL6 expression correlated with worse prognosis in PR-negative patients. TCL6 could predict worse survival in luminal B breast cancer based on intrinsic subtypes. Immune-related pathways such as Janus kinase-signal transducer of activators of transcription were regulated by TCL6. Further finding revealed that TCL6 correlated with immune infiltrating cells such as B cells (r = 0.25, P < 0.001), CD8+ T cells (r = 0.23, P < 0.001), CD4+ T cells (r = 0.25, P < 0.001), neutrophils (r = 0.21, P < 0.001), and dendritic cells (r = 0.27, P < 0.001). TCL6 was also positively correlated with tumor-infiltrating lymphocytes infiltration and PD-1, PD-L1, PD-L2, and CTLA-4 immune checkpoint molecules (P < 0.001). CONCLUSION: Our findings suggest that lncRNA TCL6 correlates with immune infiltration and may act as a useful prognostic molecular marker in breast cancer.

Identification of a New Eight-Long Noncoding RNA Molecular Signature for Breast Cancer Survival Prediction.

Because of the phenotypic and molecular diversity, it is still difficult to predict breast cancer prognosis. This study aimed to develop and validate a multi-lncRNA (long noncoding RNA) signature to improve the survival prediction for breast cancer. Three hundred twenty-seven breast cancer patients from GSE20685 were used as a training set. GSE88770 including 117 patients and The Cancer Genome Atlas datasets including 1077 patients were used as 2 validation sets. Kaplan-Meier curve, the LASSO (least absolute shrinkage and selection operator) method, univariate and multivariate Cox analyses were applied to build a molecular model for predicting survival. Function analysis of this lncRNA signature was investigated. A novel eight-lncRNA molecular signature was first identified from multiple datasets. This signature classified patients into the high-risk and low-risk groups. Breast cancer in the high-risk group showed significantly worse survival than that in the low-risk group. Further multivariate Cox analysis revealed that this molecular signature was an independent prognostic factor for breast cancer in the training and validation sets. Furthermore, stratification analyses showed that this molecular signature was also used to classify patients into the low- and high-risk groups in patients with low or high T-stage, patients with or without lymph node metastasis, older or younger, estrogen receptor-positive or -negative, and progesterone receptor-positive or -negative patients. Our eight-lncRNA signature was a powerful tool in predicting prognosis in Luminal B breast cancer based on molecular subtype. This lncRNA signature involved in cell adhesion, apoptosis, cell differentiation, and immune regulation. Our study provided a reliable eight-lncRNA molecular signature for survival prediction of breast cancer, and this signature can stratify patients into the high- and low-risk groups. This molecular signature may help the selection of the suitable treatment strategies.

Molecular mechanism of HEIH and HULC in the proliferation and invasion of hepatoma cells.

OBJECTIVE: To study the expression and molecular mechanism of long noncoding RNAs (lncRNA) including HEIH and HULC in proliferation and invasion of hepatoma cells. METHODS: We detected the expression of HEIH and HULC in hepatocellular carcinoma cell line (MHCC97L and HepG2), as well as in human normal hepatocyte line (cHL-7702) by real-time PCR. Using MTT and transwell, we investigated the effect of HEIH and HULC on proliferation and invasion of hepatoma cells with siRNA and expression plasmid. To explore the molecular mechanism, we use western blot to reveal the role of HEIH and HULC in tumor invasion related gene expression. RESULTS: The expression of HEIH and HULC in hepatocellular carcinoma cell line was significantly increased compared with human normal hepatocyte line (P<0.05). The expression of HULC in HepG2 was higher than that in MHCC97L. The over-expression of HULC could enhance proliferation of MHCC97L and HepG2, however, the over-expression of HEIH could not. The over-expression of HULC and HEIH could promote invasion of MHCC97L and HepG2. Invasion of MHCC97L and HepG2 did not have significant change after down-regulating of HEIH and HULC by siRNA. Over-expression of HULC up-regulated the expression of Snail in HepG2. CONCLUSIONS: The expression of HEIH and HULC increased significantly in hepatocellular carcinoma cell line compared with that in human normal hepatocyte line. HULC could promote proliferation of hepatoma cells. HEIH and HULC play an important role in the invasion of hepatocellular carcinoma cell.