Growing evidence has shown that a large number of miRNAs are abnormally expressed in cervical cancer (CC) tissues and play irreplaceable roles in tumorigenesis, progression, and metastasis. This study aimed to identify new biomarkers and pivotal genes associated with CC prognosis through comprehensive bioinformatics analysis. At first, the data of gene expression microarray (GSE30656) was downloaded from GEO database and differential miRNAs were obtained. Additionally, 4 miRNAs associated with the survival time of patients with CC were screened through TCGA differential data analysis, Kaplan-Meier, and Landmark analysis. Among them, the low expression of miR-188 and high expression of miR-223 correlated with the short survival of CC patients, while the down-regulation of miR-99a and miR-125b was closely related to the 5-year survival rate of patients. Then, based on the correspondence between the differentially expressed genes (DEGs) in CC from the TCGA data and the 4 miRNAs target genes, 58 target genes were screened to perform the analysis of function enrichment and the visualization of protein-protein interaction (PPI) networks. The seven pivotal genes of the PPI network as the target genes of four miRNAs related to prognosis, they were directly or indirectly involved in the development of CC. In this study, based on high-throughput data mining, differentially expressed miRNAs and related target genes were analyzed to provide an effective bioinformatics basis for further understanding of the pathogenesis and prognosis of CC. And the results may be a promising biomarker for the early screening of high-risk populations and early diagnosis of cervical cancer.

There has been increasing attention on immune-oncology for its impressive clinical benefits in many different malignancies. However, due to molecular and genetic heterogeneity of tumors, the activities of traditional clinical and pathological criteria are far from satisfactory. Immune-based strategies have re-ignited hopes for the treatment and prevention of breast cancer. Prognostic or predictive biomarkers, associated with tumor immune microenvironment, may have great prospects in guiding patient management, identifying new immune-related molecular markers, establishing personalized risk assessment of breast cancer. Therefore, in this study, weighted gene co-expression network analysis (WGCNA), single-sample gene set enrichment analysis (ssGSEA), multivariate COX analysis, least absolute shrinkage, and selection operator (LASSO), and support vector machine-recursive feature elimination (SVM-RFE) algorithm, along with a series of analyses were performed, and four immune-related genes (APOD, CXCL14, IL33, and LIFR) were identified as biomarkers correlated with breast cancer prognosis. The findings may provide different insights into prognostic monitoring of immune-related targets for breast cancer or can be served as reference for the further research and validation of biomarkers.

BackgroundStudies have shown that long noncoding RNAs (lncRNAs) make up the major proportion of the ceRNA network and can regulate gene expression by competitively binding to miRNAs. This reveals the existence of an RNA-miRNA regulatory pathway and is of great biological significance. CeRNAs, as competitive endogenous RNAs, have revealed a new mechanism of interaction between RNAs. Until now, the role of lncRNA-mediated ceRNAs in breast cancer and their regulatory mechanisms have been elucidated to some extent.PurposeIn this study, comprehensive analysis of large-scale invasive breast cancer samples in TCGA were conducted to further explore the developmental mechanism of invasive breast cancer and the potential predictive markers for invasive breast cancer prognosis in the ceRNA network.MethodsAbnormal expression profiles of invasive breast cancer associated mRNAs, lncRNAs and miRNAs were obtained from the TCGA database. Through further alignment and prediction of target genes, an abnormal lncRNA-miRNA-mRNA ceRNA network was constructed for invasive breast cancer. Through the overall survival analysis, Identification prognostic bio-markers for invasive breast cancer patients. In addition, we used Cytoscape plug-in BinGo for the different mRNA performance functional cluster analysis.ResultsDifferential analysis revealed that 1059 lncRNAs, 86 miRNAs, and 2138 mRNAs were significantly different in invasive breast cancer samples versus normal samples. Then we construct an abnormal lncRNA-miRNA-mRNA ceRNA network for invasive breast cancer, consisting of 90 DElncRNAs, 18 DEmiRNAs and 26 DEmRNAs.Further, 4 out of 90 lncRNAs, 3 out of 26 mRNAs, and 2 out of 18 miRNAs were useful as prognostic biomarkers for invasive breast cancer patients (P value < 0.05). It is worth noting that based on the ceRNA network, we found that the LINC00466-Hsa-mir-204- NTRK2 LINC00466-hsa-mir-204-NTRK2 axis was present in 9 RNAs associated with the prognosis of invasive breast cancer.ConclusionThis study provides an effective bioinformatics basis for further understanding of the molecular mechanism of invasive breast cancerand for predicting outcomes, which can guide the use of invasive breast cancerdrugs and subsequent related research.

BackgroundAs one of the most common malignant tumors in humans, lung cancer has experienced a gradual increase in morbidity and mortality. This study examined prognosis-related methylation-driven genes specific to lung adenocarcinoma (LUAD) to provide a basis for prognosis prediction and personalized targeted therapy for LUAD patients.MethodsThe methylation and survival time data from LUAD patients in the TCGA database were downloaded. The MethylMix algorithm was used to identify the differential methylation status of LUAD and adjacent tissues based on the β-mixture model to obtain disease-related methylation-driven genes. A COX regression model was then used to screen for LUAD prognosis-related methylation-driven genes, and a linear risk model based on five methylation-driven gene expression profiles was constructed. A methylation and gene expression combined survival analysis was performed to further explore the prognostic value of 5 genes independently.ResultsThere were 118 differentially expressed methylation-driven genes in the LUAD tissues and adjacent tissues. Five of the genes, CCDC181, PLAU, S1PR1, ELF3, and KLHDC9, were used to construct a prognostic risk model. Overall, the survival time was significantly lower in the high-risk group compared with that in the low-risk group (P < 0.05). In addition, the methylation and gene expression combined survival analysis found that the combined expression levels of the genes CCDC181, PLAU, and S1PR1 as well as KLHDC9 alone can be used as independent prognostic markers or drug targets.ConclusionOur findings provide an important bioinformatic basis and relevant theoretical basis for guiding subsequent LUAD early diagnosis and prognosis assessments.Electronic supplementary materialThe online version of this article (10.1186/s12935-018-0691-z) contains supplementary material, which is available to authorized users.

BackgroundRecent studies have found additional roles for vinpocetine, a potent phosphodiesterase type I inhibitor, in anti-proliferation and anti-inflammation of vascular smooth muscle cells and cancer cells via different mechanisms. In this study, we attempted to investigate whether vinpocetine protected against atherosclerotic development in apoE-/- mice and explore the underlying anti-atherogenic mechanisms in macrophages.Methodology/Principal FindingsVinpocetine markedly decreased atherosclerotic lesion size in apoE-/- mice measured by oil red O. Masson’s trichrome staining and immunohistochemical analyses revealed that vinpocetine significantly increased the thickness of fibrous cap, reduced the size of lipid-rich necrotic core and attenuated inflammation. In vitro experiments exhibited a significant decrease in monocyte adhesion treated with vinpocetine. Further, active TNF-α, IL-6, monocyte chemoattractant protein-1and matrix metalloproteinase-9 expression induced by ox-LDL were attenuated by vinpocetine in a dose-dependent manner. Similarly, ox-LDL-induced reactive oxygen species were significantly repressed by vinpocetine. Both western blot and luciferase activity assay showed that vinpocetine inhibited the enhanced Akt, IKKα/β, IκBα phosphorylation and NF-κB activity induced by ox-LDL, and the inhibition of NF-κB activity was partly caused by Akt dephosphorylation. However, knockdown of PDE1B did not affect Akt, IKKα/β and IκBα phosphorylation.ConclusionsThese results suggest that vinpocetine exerts anti-atherogenic effects through inhibition of monocyte adhesion, oxidative stress and inflammatory response, which are mediated by Akt/NF-κB dependent pathway but independent of PDE1 blockade in macrophages.

Advances in cancer biology have allowed early diagnosis and more comprehensive treatment of breast cancer (BC). However, it remains the most common cause of cancer death in women worldwide because of its strong invasiveness and metastasis. In‐depth study of the molecular pathogenesis of BC and of relevant prognostic markers would improve the quality of life and prognosis of patients. In this study, bioinformatics analysis of SNP‐related data from BC patients provided in the TCGA database revealed that six mutant genes ( NCOR1, GATA3, CDH1, ATM, AKT1, and PTEN ) were significantly associated with the corresponding expression levels of the proteins. The proteins were involved in multiple pathways related to the development of cancer, including the PI3K‐Akt signaling pathway, pertinent microRNAs, and the MAPK signaling pathway. In addition, overall survival and recurrence‐free survival analysis revealed the close associations of the expression of GATA3 , NCOR1 , CDH1, and ATM with survival of BC patients. Therefore, detecting these gene mutations and exploring their corresponding expression could be valuable in predicting the prognosis of patients. The results of the high‐throughput data mining provide important fundamental bioinformatics information and a relevant theoretical basis for further exploring the molecular pathogenesis of BC and assessing the prognosis of patients.

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This meta-analysis suggested that more pro-inflammatory diets (higher DII scores) are associated with increased breast cancer incidence. However, the research is not about significant associations but about moderate effect sizes.