BackgroundNAD (P) H: quinone oxidoreductase 1 (NQO1) is a xenobiotic metabolizing enzyme that detoxifies chemical stressors and antioxidants, providing cytoprotection in normal tissues. However, high-level expression of NQO1 has been correlated with numerous human malignancies, suggesting a role in carcinogenesis and tumor progression. This study aimed to explore the clinicopathological significance of NQO1 and as a prognostic determinant in breast cancer.MethodsA total of 176 breast cancer patients with strict follow-up, 45 ductal carcinoma in situ (DCIS), 22 hyperplasia and 52 adjacent non-tumor breast tissues were selected for immunohistochemical staining of NQO1 protein. Immunofluorescence staining was also performed to detect the subcellular localization of NQO1 protein in MCF-7 breast cancer cells. Eight fresh breast cancers paired with adjacent non-tumor tissues were quantified using real time RT-PCR (qRT-PCR) and western blot. The correlations between NQO1 overexpression and the clinical features of breast cancer were evaluated using chi-square test and Fisher’s exact tests. The survival rate was calculated using the Kaplan–Meier method, and the relationship between prognostic factors and patient survival was also analyzed by the Cox proportional hazards models.ResultsNQO1 protein showed a mainly cytoplasmic staining pattern in breast cancer. The strongly positive rate of NQO1 protein was 61.9% (109/176) in breast cancer, and was significantly higher than in DCIS (31.1%, 14/45), hyperplasia tissues (13.6%, 3/22) and adjacent non-tumor tissues (13.5%, 7/52). High-level expression of NQO1 protein was correlated with late clinical stage, poor differentiation, lymph node metastasis, Her2 expression and disease-free and 10-year overall survival rates in breast cancer. Moreover, multivariate analysis suggested that NQO1 emerged as a significant independent prognostic factor along with clinical stage and Her2 expression status in patients with breast cancer.ConclusionsHigh-level expression of NQO1 appears to be associated with breast cancer progression, and may be a potential biomarker for poor prognostic evaluation of breast cancers.

Single-index models are natural extensions of linear models and circumvent the so-called curse of dimensionality. They are becoming increasingly popular in many scientific fields including biostatistics, medicine, economics and financial econometrics. Estimating and testing the model index coefficients $\bolds{\beta}$ is one of the most important objectives in the statistical analysis. However, the commonly used assumption on the index coefficients, $\|\bolds{\beta}\|=1$, represents a nonregular problem: the true index is on the boundary of the unit ball. In this paper we introduce the EFM approach, a method of estimating functions, to study the single-index model. The procedure is to first relax the equality constraint to one with (d-1) components of $\bolds{\beta}$ lying in an open unit ball, and then to construct the associated (d-1) estimating functions by projecting the score function to the linear space spanned by the residuals with the unknown link being estimated by kernel estimating functions. The root-n consistency and asymptotic normality for the estimator obtained from solving the resulting estimating equations are achieved, and a Wilks type theorem for testing the index is demonstrated. A noticeable result we obtain is that our estimator for $\bolds{\beta}$ has smaller or equal limiting variance than the estimator of Carroll et al. [J. Amer. Statist. Assoc. 92 (1997) 447-489]. A fixed-point iterative scheme for computing this estimator is proposed. This algorithm only involves one-dimensional nonparametric smoothers, thereby avoiding the data sparsity problem caused by high model dimensionality. Numerical studies based on simulation and on applications suggest that this new estimating system is quite powerful and easy to implement.Comment: Published in at http://dx.doi.org/10.1214/10-AOS871 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

These results suggest that altered expression of hsa_circRNA_103636 in PBMCs is a potential novel biomarker for the diagnosis and treatment of MDD.

Fibrinogen is an extracellular matrix protein composed of three polypeptide chains with fibrinogen alpha (FGA), beta (FGB) and gamma (FGG). Although fibrinogen and its related fragments are involved in tumor angiogenesis and metastasis, their functional roles are incompatible. A recent genome-scale screening reveals that loss of FGA affects the acceleration of tumor growth and metastasis of lung cancer, but the mechanism remains elusive. We used CRISPR/Cas9 genome editing to knockout (KO) FGA in human lung adenocarcinoma (LUAD) cell lines A549 and H1299. By colony formation, transwell migration and matrix invasion assays, FGA KO increased cell proliferation, migration, and invasion but decreased the expressions of epithelial-mesenchymal transition marker E-cadherin and cytokeratin 5/8 in A549 and H1299 cells. However, admin-istration of FGA inhibited cell proliferation and migration but induced apoptosis in A549 cells. Of note, FGA KO cells indirectly cocultured by transwells with FGA wild-type cells increased FGA in the culture medium, leading to decreased migration of FGA KO cells. Furthermore, our functional analysis identified a direct interaction of FGA with integrin a5 as well as FGA-integrin signaling that regulated the AKT-mTOR signaling pathway in A549 cells. In addition, we validated that FGA KO increased tumor growth and metastasis through activation of AKT signaling in an A549 xenograft model.Implications: These findings demonstrate that that loss of FGA facilities tumor growth and metastasis through the integrin-AKT signaling pathway in lung cancer.

BackgroundNAD(P)H:quinone oxidoreductase (NQO1) is a flavoprotein that catalyzes two-electron reduction and detoxification of quinones and its derivatives. NQO1 catalyzes reactions that have a protective effect against redox cycling, oxidative stress and neoplasia. High expression of NQO1 is associated with many solid tumors including those affecting the colon, breast and pancreas; however, its role in the progression of ovarian carcinoma is largely undefined. This study aimed to investigate the clinicopathological significance of high NQO1 expression in serous ovarian carcinoma.MethodsNQO1 protein expression was assessed using immunohistochemical (IHC) staining in 160 patients with serous ovarian carcinoma, 62 patients with ovarian borderline tumors and 53 patients with benign ovarian tumors. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect NQO1 mRNA expression levels. The correlation between high NQO1 expression and clinicopathological features of ovarian carcinoma was evaluated by Chi-square and Fisher’s exact test. Overall survival (OS) rates of all of ovarian carcinoma patients were calculated using the Kaplan-Meier method, and univariate and multivariate analyses were performed using the Cox proportional hazards regression model.ResultsNQO1 protein expression in ovarian carcinoma cells was predominantly cytoplasmic. Strong, positive expression of NQO1 protein was observed in 63.8% (102/160) of ovarian carcinomas, which was significantly higher than in borderline serous tumors (32.3%, 20/62) or benign serous tumors (11.3%, 6/53). Importantly, the rate of strong, positive NQO1 expression in borderline serous tumors was also higher than in benign serous tumors. High expression of NQO1 protein was closely associated with higher histological grade, advanced clinical stage and lower OS rates in ovarian carcinomas. Moreover, multivariate analysis indicated that NQO1 was a significant independent prognostic factor, in addition to clinical stage, in patients with ovarian carcinoma.ConclusionsNQO1 is frequently upregulated in ovarian carcinoma. High expressin of NQO1 protein may be an effective biomarker for poor prognostic evaluation of patients with serous ovarian carcinomas.