Prognostic and Immunological Value of GNB4 in Gastric Cancer by Analyzing TCGA Database.

Background: Gastric cancer (GC) represents a universal malignant tumor of the digestive system. Stromal and immune cells belong to two main nontumor components exerting a vital function in the tumor microenvironment. Methods: Based on TCGA database, this study downloaded clinical information and gene profiles of GC. The ESTIMATE algorithm was adopted for evaluating the score of immune-infiltrating cells. This work employed Sangerbox to explore the differentially denoted genes (DEGs) related to stromal, immunity, and prognosis. Besides, the STRING database was involved in order to detect the association among the proteins. The MCODE module of Cytoscape software was used to screen key genes. Oncomine and GEPIA databases were used, aiming to study the differences in key genes in healthy gastric mucosa and GC. At last, we adopted TISDIB and TIMER databases for analyzing the association of guanine nucleotide binding protein subunit-4 (GNB4) between gastric cancer and tumor immune cells. qRT-PCR was applied for exploring differential GNB4 expression between GC and normal gastric mucosa and investigating the relation of GNB4 with tumor-infiltrating lymphocytes (TILs). Results: Patients undergoing a great stromal score exhibited worse prognostic outcome, and cases having a low immune score had better prognosis. Overall, altogether 656 genes were upregulated with 5 genes being downregulated, which were matrix immune-related differential genes. Furthermore, 18 genes were screened as hub genes on the basis of the univariate Cox risk model of TCGA database (82 differential genes predicted poor GC survival). Oncomine and GEPIA databases revealed that GNB4 expression in gastric cancer was obviously higher in comparison with that in normal gastric mucosa. The GSEA, TISDIB, and TIMER databases revealed that GNB4 is involved in various tumor signal pathways and immune and metabolic processes. qRT-PCR demonstrated that GNB4 expression in gastric cancer was notably higher in comparison with that in normal gastric mucosa, showing significant association with matrix TILs. Conclusion: The selected key gene GNB4 is a potential biomarker to guide the immunotherapy of gastric cancer.

[Integration-based co-expression network analysis to investigate tumor-associated modules across three cancer types].

In case/control gene expression data, differential expression (DE) represents changes in gene expression levels across various biological conditions, whereas differential co-expression (DC) represents an alteration of correlation coefficients between gene pairs. Both DC and DE genes have been studied extensively in human diseases. However, effective approaches for integrating DC-DE analyses are lacking. Here, we report a novel analytical framework named DC&DEmodule for integrating DC and DE analyses and combining information from multiple case/control expression datasets to identify disease-related gene co-expression modules. This includes activated modules (gaining co-expression and up-regulated in disease) and dysfunctional modules (losing co-expression and down-regulated in disease). By applying this framework to microarray data associated with liver, gastric and colon cancer, we identified two, five and two activated modules and five, five and one dysfunctional module(s), respectively. Compared with the other methods, pathway enrichment analysis demonstrated the superior sensitivity of our method in detecting both known cancer-related pathways and those not previously reported. Moreover, we identified 17, 69, and 11 module hub genes that were activated in three cancers, which included 53 known and three novel cancer prognostic markers. Random forest classifiers trained by the hub genes showed an average of 93% accuracy in differentiating tumor and adjacent normal samples in the TCGA and GEO database. Comparison of the three cancers provided new insights into common and tissue-specific cancer mechanisms. A series of evaluations demonstrated the framework is capable of integrating the rapidly accumulated expression data and facilitating the discovery of dysregulated processes.

Correlation of microRNA-367 in the clinicopathologic features and prognosis of breast cancer patients.

ABSTRACT: Breast cancer (BC) is a malignant tumor originating from cells of the breast. Notably, microRNAs have been recognized as biomarkers of BC metastasis. The present study is designed to evaluate the association between microRNA (miR)-367 expression and BC with the variance of clinicopathologic features and prognosis.Initially, 63 BC patients were allocated in the BC group, while the other 40 healthy volunteers were recruited as the control group. miR-367 expression in the serum of patients and healthy controls was detected using real-time polymerase chain reaction. Furthermore, the relation between miR-367 in serum and clinicopathologic features and prognosis of BC patients was accessed.miR-367 expression in serum of the BC group was evidently lower than that in the control group (all P < .001). Besides, miR-367 underexpression in the BC group was closely associated with the variance in tumor nodes metastasis advanced stage, tumor diameter, and lymph node metastasis of BC (all P < .001). In addition, compared with the control group, poorly expressed miR-367 BC group had short period of disease-free survival and overall survival (all P < .001).Our study demonstrated that miR-367 expression is associated with BC clinicopathologic features and prognosis. This investigation may offer new insight for BC treatment.

The "Matrisome" reveals the characterization of skin keloid microenvironment.

Keloids are fibroproliferative dermal tumors of unknown origin that are characterized by the overabundant accumulation of extracellular matrix (ECM) components. The mechanism of keloid formation has remained unclear because of a poor understanding of its molecular basis. In this study, the dermal ECM components of keloids were identified and the pathological features of keloid formation were characterized using large-scale quantitative proteomic analyses of decellularized keloid biomatrix scaffolds. We identified a total of 267 dermal core ECM and ECM-associated proteins that were differentially expressed between patients with keloids and healthy controls. Skin mechanical properties and biological processes including protease activity, wound healing, and adhesion were disordered in keloids. The integrated network analysis of the upregulated ECM proteins revealed multiple signaling pathways involved in these processes that may lead to keloid formation. Our findings may improve the scientific basis of keloid treatment and provide new ideas for the establishment of keloid models.

Long Noncoding RNA PCED1B-AS1 Promotes the Warburg Effect and Tumorigenesis by Upregulating HIF-1α in Glioblastoma.

Accumulating evidence suggests that long noncoding RNA (lncRNA) functions as a critical regulator in cancer biology. Here, we characterized the role of lncRNA PCED1B antisense RNA 1 (PCED1B-AS1) in glioblastoma (GBM). PCED1B-AS1 was notably upregulated in GBM tissues and cell lines and closely associated with larger tumor size and higher grade. Patients with high PCED1B-AS1 had shorter survival time than those with low PCED1B-AS1. Functional experiments showed that depletion of PCED1B-AS1 significantly inhibited, while overexpression of PCED1B-AS1 promoted cell proliferation, glucose uptake, and lactate release. Mechanistically, PCED1B-AS1 was able to directly bind to the 5'-UTR of HIF-1α mRNA and potentiate HIF-1α translation, leading to increased HIF-1α protein level, thereby promoting the Warburg effect and tumorigenesis. Importantly, PCED1B-AS1 lost the carcinogenic properties in the absence of HIF-1α. In addition, we also confirmed the existence of the PCED1B-AS1/HIF-1α regulatory axis in vivo. Taken together, our findings demonstrate that PCED1B-AS1 is a novel oncogenic lncRNA in GBM and functions in a HIF-1α-dependent manner, which provides a promising prognostic biomarker and druggable target for GBM.

Functional BDNF rs7124442 Variant Regulated by miR-922 is Associated with Better Short-Term Recovery of Ischemic Stroke.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) is the most abundant neurotrophin, which contributes to the neuronal survival and synaptic plasticity. This study investigated the associations of BDNF polymorphisms at the 3'-untranslated region with risk and outcome of ischemic stroke in a Chinese Han population. METHODS: 500 patients and 520 controls were enrolled for BDNF rs7124442 genotyping. The binding of miR-922 to BDNF rs7124442 was examined by luciferase assay; BDNF expression was assessed using qRT-PCR. RESULTS: Alcohol consumption, cigarette smoking, diabetes, hypertension (all P < 0.001) and higher serum triglycerides concentration (P = 0.009) were associated with an increased risk of developing ischemic stroke. After adjusted for age and sex, logistic regression analysis showed that IS patients harbored with rs7124442 TC genotype had a milder initial stroke (Dominant model: OR = 0.45, 95% CI = 0.25-0.81, P = 0.015), and also showed a better short-term recovery (Dominant model: OR = 0.39, 95% CI =0.24-0.68, P = 0.003). Furthermore, we found that co-transfection of hsa-miR-922 mimics with BDNF 3'-UTR containing the mutated allele C changed luciferase activity when compared to co-transfection with BDNF 3'-UTR containing the wild-type allele. Besides, patients carrying BDNF rs712444 TC or CC genotype had an increased level of BDNF compared with patients with the TT genotype. CONCLUSION: Our study demonstrates that the SNP rs7124442 in BDNF 3'-UTR, through affecting the regulatory role of miR-922 in BDNF expression, might act as a protective factor for the outcome of patients with ischemic stroke.

A NOVEL AND EFFICIENT ALGORITHM FOR DE NOVO DISCOVERY OF MUTATED DRIVER PATHWAYS IN CANCER.

Next-generation sequencing studies on cancer somatic mutations have discovered that driver mutations tend to appear in most tumor samples, but they barely overlap in any single tumor sample, presumably because a single driver mutation can perturb the whole pathway. Based on the corresponding new concepts of coverage and mutual exclusivity, new methods can be designed for de novo discovery of mutated driver pathways in cancer. Since the computational problem is a combinatorial optimization with an objective function involving a discontinuous indicator function in high dimension, many existing optimization algorithms, such as a brute force enumeration, gradient descent and Newton's methods, are practically infeasible or directly inapplicable. We develop a new algorithm based on a novel formulation of the problem as non-convex programming and non-convex regularization. The method is computationally more efficient, effective and scalable than existing Monte Carlo searching and several other algorithms, which have been applied to The Cancer Genome Atlas (TCGA) project. We also extend the new method for integrative analysis of both mutation and gene expression data. We demonstrate the promising performance of the new methods with applications to three cancer datasets to discover de novo mutated driver pathways.

Transgenic overexpression of BAFF regulates the expression of immune-related genes in zebrafish, Danio rerio.

The B-cell activating factor (BAFF) is a member of tumour necrosis factor (TNF) superfamily that specifically regulates B lymphocyte proliferation and survival. Excess BAFF leads to overproduction of antibodies for secretion, anti-dsDNA antibodies and a lupus-like syndrome in mice. To investigate whether transgenic overexpression of the zebrafish BAFF leads to immunoglobulin changes and/or early maturing of the immune system, a Tol2-GFP-2A-BAFF/His recombinant plasmid was constructed by inserting a 2A peptide between the green fluorescent protein (GFP) and BAFF sequences. Functional GFP and BAFF proteins were expressed separately and confirmed in HeLa cells. The relative expression of immune-related genes (IgLC-1, IgLC-2, IgLC-3, IgD, IgM and IL-4), early lymphoid markers (Ikaros, Rag-1 and TCRAC), and the protooncogene Bcl-2 were evaluated by quantitative polymerase chain reaction (PCR) in F0 founder of transgenic zebrafish juveniles and adults. Ectopic expression of BAFF in adults was confirmed using Western blots and was shown to upregulate IgLC-1, IgLC-2, IgD, IgM, IgZ/T, Ikaros, Rag-1, TCRAC, IL-4 and Bcl-2 expression in juveniles on day 21 and IgLC-1, IgLC-2, IgD, IgM,IgZ/T, Rag-1, TCRAC and Bcl-2 expression in zebrafish three months postfertilization. The relative titers of specific IgM against Edwardsiella tarda WED were assessed using modified enzyme-linked immunosorbent assay (ELISA) with the whole body homogenate of zebrafish and demonstrated a significant increase in BAFF-transgenic group. Therefore, our findings provided novel insight into further exploration of modulating adaptive immunity and studying autoimmune diseases caused by regulating BAFF.

Integrative and regularized principal component analysis of multiple sources of data.

Integration of data of disparate types has become increasingly important to enhancing the power for new discoveries by combining complementary strengths of multiple types of data. One application is to uncover tumor subtypes in human cancer research in which multiple types of genomic data are integrated, including gene expression, DNA copy number, and DNA methylation data. In spite of their successes, existing approaches based on joint latent variable models require stringent distributional assumptions and may suffer from unbalanced scales (or units) of different types of data and non-scalability of the corresponding algorithms. In this paper, we propose an alternative based on integrative and regularized principal component analysis, which is distribution-free, computationally efficient, and robust against unbalanced scales. The new method performs dimension reduction simultaneously on multiple types of data, seeking data-adaptive sparsity and scaling. As a result, in addition to feature selection for each type of data, integrative clustering is achieved. Numerically, the proposed method compares favorably against its competitors in terms of accuracy (in identifying hidden clusters), computational efficiency, and robustness against unbalanced scales. In particular, compared with a popular method, the new method was competitive in identifying tumor subtypes associated with distinct patient survival patterns when applied to a combined analysis of DNA copy number, mRNA expression, and DNA methylation data in a glioblastoma multiforme study. Copyright © 2016 John Wiley & Sons, Ltd.

Nonlinear Joint Latent Variable Models and Integrative Tumor Subtype Discovery.

Integrative analysis has been used to identify clusters by integrating data of disparate types, such as deoxyribonucleic acid (DNA) copy number alterations and DNA methylation changes for discovering novel subtypes of tumors. Most existing integrative analysis methods are based on joint latent variable models, which are generally divided into two classes: joint factor analysis and joint mixture modeling, with continuous and discrete parameterizations of the latent variables respectively. Despite recent progresses, many issues remain. In particular, existing integration methods based on joint factor analysis may be inadequate to model multiple clusters due to the unimodality of the assumed Gaussian distribution, while those based on joint mixture modeling may not have the ability for dimension reduction and/or feature selection. In this paper, we employ a nonlinear joint latent variable model to allow for flexible modeling that can account for multiple clusters as well as conduct dimension reduction and feature selection. We propose a method, called integrative and regularized generative topographic mapping (irGTM), to perform simultaneous dimension reduction across multiple types of data while achieving feature selection separately for each data type. Simulations are performed to examine the operating characteristics of the methods, in which the proposed method compares favorably against the popular iCluster that is based on a linear joint latent variable model. Finally, a glioblastoma multiforme (GBM) dataset is examined.

Expression and mechanism of action of the SARI tumor suppressor in prostate cancer.

The objective of this study was to assess the expression of SARI (Suppressor of AP-1, Regulated by IFN) in prostate cancer (Pca) and explore the effects and possible mechanism of action of SARI in the occurrence and development of Pca. In the current study, the expression of SARI was detected using PCR in 40 patients with prostate cancer, 20 patients with prostatic hyperplasia, and prostate cancer cells (LNCaP. and DU145). In addition, the effects of the pro-inflammatory cytokine interferon (IFN)-ß on the expression of SARI in DU145 prostate cancer cells and the possible potential signaling pathways activated by SARI were detected using RT-PCR. The expression of SARI protein was downregulated from 0.6957 ± 0.0104 to 0.1597 ± 0.0032 in prostate cancer cells compared with normal prostate tissues and cells. In addition, SARI gene expression increased from 0.0794 ± 0.0133 to 0.1232 ± 0.0162 significantly in a concentration- and time-dependent manner in DU145 cells treated with IFN-ß (P<0.05). Finally, MTT assays demonstrated that DU145 cells growth slowed down, flow cytometry demonstrated that IFN-ß induced apoptosis increased from 0.0343 ± 0.0039 to 0.0612 + 0.0025 in DU145 prostate cancer cells. In conclusion, the results of the current study suggest that SARI might play an important role in the occurrence and development of prostate cancer. In addition, IFN-ß might inhibit the growth of prostate cancer and promote cellular apoptosis by inducing the expression of SARI.

Precore/Core Region Mutations in Hepatitis B Virus DNA Predict Postoperative Survival in Hepatocellular Carcinoma.

Hepatitis B virus (HBV) DNA is prone to mutations because of the proofreading deficiencies of HBV polymerase. We have identified hepatocellular carcinoma (HCC) survival-associated HBV mutations in the X protein region of HBV DNA. In the present study, we extend our research to assess HCC survival-associated HBV mutations in the HBV precore/core (PreC/C) region. The PreC/C region was amplified and sequenced and the HBV mutations were identified according to the NCBI database (http://www.ncbi.nlm.nih.gov/genome/5536). The relationships between the mutations in the PreC/C region and HCC survival were analyzed. Survival curves were generated using the Kaplan-Meier method, and comparisons between the curves were made using the log-rank test. Multivariate survival analysis was performed using a Cox proportional hazards model. After adjusting for clinical characteristics, the 1915, 2134, 2221, 2245 and 2288 mutational sites were identified as statistically significant independent predictors of HCC survival by multivariate survival analysis using a Cox proportional hazards model. In addition, the mutational site of 1896 was identified for its association with survival at a borderline significance level. A total of five mutations in the precore/core region were identified as independent predictors of postoperative survival in HCC patients. The analysis of HBV DNA mutations may help identify patient subgroups with poor prognosis and may help refine therapeutic decisions regarding HCC patients.

Tongxinluo inhibits cyclooxygenase-2, inducible nitric oxide synthase, hypoxia-inducible factor-2α/vascular endothelial growth factor to antagonize injury in hypoxia-stimulated cardiac microvascular endothelial cells.

BACKGROUND: Endothelial dysfunction is considered as the initiating process and pathological basis of cardiovascular disease. Cyclooxygenase-2 (COX-2) and prostacyclin synthase (PGIS), inducible nitric oxide synthase (iNOS) and endothelial NOS (eNOS) are key enzymes with opposing actions in inflammation and oxidative stress, which are believed to be the major driver of endothelial dysfunction. And in hypoxia (Hx), Hx-inducible factor (HIF)-1α and HIF-2α are predominantly induced to activate vascular endothelial growth factor (VEGF), resulting in abnormal proliferation. Whether and how Tongxinluo (TXL) modulates COX-2, PGIS, iNOS, eNOS, HIF-1α, HIF-2α, and VEGF in Hx-stimulated human cardiac microvascular endothelial cells (HCMECs) have not been clarified. METHODS: HCMEC were treated with CoCl 2 to mimic Hx and the mRNA expressions of COX-2, PGIS, iNOS, eNOS, HIF-1α, HIF-2α, and VEGF were first confirmed, and then their mRNA expression and protein content as well as the cell pathological alterations were evaluated for TXL treatment with different concentrations. In addition, the effector molecular of inflammation prostaglandin E 2 (PGE 2 ) and the oxidative marker nitrotyrosine (NT) was adopted to reflect HCMEC injury. RESULTS: Hx could induce time-dependent increase of COX-2, iNOS, HIF-2α, and VEGF in HCMEC. Based on the Hx-induced increase, TXL could mainly decrease COX-2, iNOS, HIF-2α, and VEGF in a concentration-dependent manner, with limited effect on the increase of PGIS and eNOS. Their protein contents verified the mRNA expression changes, which was consistent with the cell morphological alterations. Furthermore, high dose TXL could inhibit the Hx-induced increase of PGE 2 and NT contents, attenuating the inflammatory and oxidative injury. CONCLUSIONS: TXL could inhibit inflammation-related COX-2, oxidative stress-related iNOS, and HIF-2α/VEGF to antagonize Hx-induced HCMEC injury.

Clinicopathological characteristics of kidney mucinous tubular and spindle cell carcinoma.

Kidney mucinous tubular and spindle cell carcinoma (MTSpCC) is a rare renal low-grade pleomorphic epithelial neoplasm featured by tubular and spindle cells with a relatively indolent behavior. This study was designed to clinicopathologically characterize two cases of kidney MTSpCC. Similar to other tumors, the data showed the diagnosis of MTSpCC relies on histological examination. Tumor cells stained strongly for CK19, CK20, and CK7 within the epithelioid component. Whereas evaluating MTSpCC clinically showed no specific symptoms, analyzing MTSpCC microscopically showed multiple elongated tubular branches of tumor cells that are closely arranged in cord-like manner under lightly stained myxoid stroma. MTSpCC also has the spindle cell area; the single tumor cell is small and nucleus round or oval. Immunohistochemical analysis of cytokeratins, electron microscopy, or genetic tests all improves the diagnosis.