Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy

The role of intestinal microbiota and microRNAs in the anti-inflammatory effects of cranberry: from pre-clinical to clinical studies

Cranberries have known anti-inflammatory properties, which extend their benefits in the context of several chronic diseases. These benefits highly rely on the polyphenol profile of cranberries, one of few foods rich in A-type proanthocyanidin (PAC). A-type PAC comprises flavan-3-ol subunits with an additional interflavan ether bond in the conformational structure of the molecule, separating them from the more commonly found B-type PAC. PACs with a degree of polymerization higher than three are known to reach the colon intact, where they can be catabolyzed by the gut microbiota and biotransformed into lower molecular weight organic acids that are available for host absorption. Gut microbiota-derived metabolites have garnered much attention in the past decade as mediators of the health effects of parent compounds. Though, the mechanisms underlying this phenomenon remain underexplored. In this review, we highlight emerging evidence that postulates that polyphenols, including ones derived from cranberries, and their metabolites could exert anti-inflammatory effects by modulating host microRNAs. Our review first describes the chemical structure of cranberry PACs and a pathway for how they are biotransformed by the gut microbiota. We then provide a brief overview of the benefits of microbial metabolites of cranberry in the intestinal tract, at homeostasis and in inflammatory conditions. Finally, we discuss the role of microRNAs in intestinal health and in response to cranberry PAC and how they could be used as targets for the maintenance of intestinal homeostasis. Most of this research is pre-clinical and we recognize that conducting clinical trials in this context has been hampered by the lack of reliable biomarkers. Our review discusses the use of miRNA as biomarkers in this context.

Role of Secreted Frizzled-Related Protein 1 in Early Breast Carcinogenesis and Breast Cancer Aggressiveness

A human transcriptome array on ERα-positive breast cancer continuum of risk identified Secreted Frizzled-Related Protein 1 (SFRP1) as decreased during breast cancer progression. In addition, SFRP1 was inversely associated with breast tissue age-related lobular involution, and differentially regulated in women with regard to their parity status and the presence of microcalcifications. The causal role of SFRP1 in breast carcinogenesis remains, nevertheless, not well understood. In this study, we characterized mammary epithelial cells from both nulliparous and multiparous mice in organoid culture ex vivo, in the presence of estradiol (E2) and/or hydroxyapatite microcalcifications (HA). Furthermore, we have modulated SFRP1 expression in breast cancer cell lines, including the MCF10A series, and investigated their tumoral properties. We observed that organoids obtained from multiparous mice were resistant to E2 treatment, while organoids obtained from nulliparous mice developed the luminal phenotype associated with a lower ratio between Sfrp1 and Esr1 expression. The decrease in SFRP1 expression in MCF10A and MCF10AT1 cell lines increased their tumorigenic properties in vitro. On the other hand, the overexpression of SFRP1 in MCF10DCIS, MCF10CA1a, and MCF7 reduced their aggressiveness. Our results support the hypothesis that a lack of SFRP1 could have a causal role in early breast carcinogenesis.

Breast cancer cell secretome analysis to decipher miRNA regulating the tumor microenvironment and discover potential biomarkers

MicroRNA (miRNA/miR) 526 b- and miR655-overexpressed tumor cell-free secretions regulate the breast cancer tumor microenvironment (TME) by promoting tumor-associated angiogenesis, oxidative stress, and hypoxic responses. Additionally, premature miRNA (pri-miR526b and pri-miR655) are established breast cancer blood biomarkers. However, the mechanisms of how these miRNAs regulate the TME has yet to be investigated. Mass spectrometry analysis of miRNA-overexpressed cell lines MCF7-miR526b, MCF7-miR655, and miRNA-low MCF7-Mock cell-free secretomes identified 34 differentially expressed proteins coded by eight genes. In both miRNA-high cell secretomes, four markers are upregulated: YWHAB, SFN, TXNDC12, and MYL6B, and four are downregulated: PEA15, PRDX4, PSMB6, and FN1. All upregulated marker transcripts are significantly high in both total cellular RNA pool and cell-free secretions of miRNA-high cell lines, validated with quantitative RT-PCR. Bioinformatics tools were used to investigate these markers' roles in breast cancer. These markers' top gene ontology functions are related to apoptosis, oxidative stress, membrane transport, and motility supporting oncogenic miR526b- and miR655-induced functions. Gene transcription factor analysis tools were used to show how these miRNAs regulate the expression of each secretory marker. Data extracted from the Human Protein Atlas showed that YWHAB, SFN, and TXNDC12 expression could distinguish early and late-stage breast cancer in various breast cancer subtypes and are associated with poor patient survival. Additionally, immunohistochemistry analysis showed the expression of each marker in breast tumors. A stronger correlation between miRNA clusters and upregulated secretory markers gene expression was found in the luminal A tumor subtype. YWHAB, SFN, and MYL6B are upregulated in breast cancer patient's blood, showing biomarker potential. Of these identified novel miRNA secretory markers, SFN and YWHAB successfully passed all validations and are the best candidates to further investigate their roles in miRNA associated TME regulation. Also, these markers show the potential to serve as blood-based breast cancer biomarkers, especially for luminal-A subtypes.

An epithelial-mesenchymal transition-related prognostic model for colorectal cancer based on weighted gene co-expression network analysis

OBJECTIVE

To identify susceptibility modules and genes for colorectal cancer (CRC) using weighted gene co-expression network analysis (WGCNA).

METHODS

Four microarray datasets were downloaded from the Gene Expression Omnibus database. We divided the tumor samples into three subgroups based on consensus clustering of gene expression, and analyzed the correlations between the subgroups and clinical features. The genetic features of the subgroups were investigated by gene set enrichment analysis (GSEA). A gene expression network was constructed using WGCNA, and a protein-protein interaction (PPI) network was used to identify the key genes. Gene modules were annotated by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses.

RESULTS

We divided the cancer cases into three subgroups based on consensus clustering (subgroups I, II, III). The green module identified by WGCNA was correlated with clinical characteristics. Ten key genes were identified according to their degree of connectivity in the protein-protein interaction network: FYN, SEMA3A, AP2M1, L1CAM, NRP1, TLN1, VWF, ITGB3, ILK, and ACTN1.

CONCLUSION

We identified 10 hub genes as candidate biomarkers for CRC. These key genes may provide a theoretical basis for targeted therapy against CRC.

Identification of Estrus in Sows Based on Salivary Proteomics

The estrus cycle of multiparous Large White sows was divided into three stages to solve the problems of heavy workload and low accuracy of the traditional estrus identification method in pig production. Saliva protein was extracted from the oral saliva of multiparous sows. Label-free quantitative proteomics was used to detect salivary proteome, and MaxQuant software was used for quality control. Results showed that 246 proteins were identified in the three stages, where 40 proteins were significantly different (p < 0.05). The total proteins identified were enriched by STEM software and the protein function was annotated by using the ClueGO plug-in in the Cytoscape software. The results were enriched to eight different trends. The annotated items were related to protein synthesis and processing and estrogen response. Gene ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment analysis of differential proteins involved in the pathways and entries included oocyte meiosis, response to estradiol, and oogenesis. Further interaction analysis showed that an interaction occurred between P00355, F1SHL9, P28491, F1SDR7, F2Z558, F1RYY6, and F2Z5G3 proteins. The findings served as a basis for revealing the changes in salivary protein content in the sow estrus cycle and provided a reference for the development of an estrus identification kit/test strip in the next step.

Identification of potentially functional circular RNAs hsa_circ_0070934 and hsa_circ_0004315 as prognostic factors of hepatocellular carcinoma by integrated bioinformatics analysis

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, which has a high mortality rate and poor treatment outcomes with yet unknown molecular basis. It seems that gene expression plays a pivotal role in the pathogenesis of the disease. Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in various malignancies by acting as competitive endogenous RNAs (ceRNAs). However, the potential pathogenesis roles of the ceRNA network among circRNA/miRNA/mRNA in HCC are unclear. In this study, first, the HCC circRNA expression data were obtained from three Gene Expression Omnibus microarray datasets (GSE164803, GSE94508, GSE97332), and the differentially expressed circRNAs (DECs) were identified using R limma package. Also, the liver hepatocellular carcinoma (LIHC) miRNA and mRNA sequence data were retrieved from TCGA and differentially expressed miRNAs (DEMIs) and mRNAs (DEGs) were determined using the R DESeq2 package. Second, CSCD website was used to uncover the binding sites of miRNAs on DECs. The DECs' potential target miRNAs were revealed by conducting an intersection between predicted miRNAs from CSCD and downregulated DEMIs. Third, candidate genes were uncovered by intersecting targeted genes predicted by miRWalk and targetscan online tools with upregulated DEGs. The ceRNA network was then built using the Cytoscape software. The functional enrichment and the overall survival time of these potential targeted genes were analyzed, and a PPI network was constructed in the STRING database. Network visualization was performed by Cytoscape, and ten hub genes were detected using the CytoHubba plugin tool. Four DECs (hsa_circ_0000520, hsa_circ_0008616, hsa_circ_0070934, hsa_circ_0004315) were obtained and six miRNAs (hsa-miR-542-5p, hsa-miR-326, hsa-miR-511-5p, hsa-miR-195-5p, hsa-miR-214-3p, and hsa-miR-424-5p) which are regulated by the above DECs were identified. Then 543 overlapped genes regulated by six miRNAs mentioned above were predicted. Functional enrichment analysis showed that these genes are mostly associated with regulatory pathways in cancer. Ten hub genes (TTK, AURKB, KIF20A, KIF23, CEP55, CDC6, DTL, NCAPG, CENPF, PLK4) have been screened from the PPI network of the 204 survival-related genes. KIF20A, NCAPG, TTK, PLK4, and CDC6 were selected for the highest significance p-values. At the end, a circRNA-miRNA-mRNA regulatory axis was established for five final selected hub genes. This study implies the potential pathogenesis of the obtained network and proposes that the two DECs (has_circ_0070934 and has_circ_0004315) may be important prognostic markers for HCC.

miR-875 Serves as A Candidate Biomarker for Detection and Prognosis and Is Correlated with PHH3 Index Levels in Breast Cancer Patients

BACKGROUND

miRNAs play crucial roles in cancers. This study investigated the potential value of miR-875 to be a detective or/and prognostic marker and evaluate the correlation between its expression and PHH3 index levels in breast cancer.

METHODS

miR-875 expression was determined in breast cancer serum and tissues by a quantitative real-time reverse transcription-polymerase chain reaction. The detective value of serum miR-875 expression for breast cancer was assessed by receiver operating characteristic analysis. Then the associations of miR-875 expression with clinical characteristics of patients and overall survival were evaluated by χ² test and Kaplan-Meier curve methods, respectively.

RESULTS

The expression of miR-875 was increased in both breast cancer serum and tissues compared with respective controls. The high miR-875 expression in serum and tissues was associated with positive lymph node metastasis and advanced TNM stages. Besides, miR-875 expression in tissues was positively associated with the PHH3 index. And serum miR-875 could screen breast cancer patients from healthy individuals. Moreover, breast cancer patients with both high expression of miR-875 and PHH3 index had shorter overall survival.

CONCLUSION

This study suggested that miR-875 expression may be suitable as a potential breast cancer detection and prognosis biomarker. And the miR-875 expression in tissues was positively associated with the PHH3 index, suggesting that miR-875 expression may be involved in tumor proliferation of breast cancer.

The Hippo Transducer YAP/TAZ as a Biomarker of Therapeutic Response and Prognosis in Trastuzumab-Based Neoadjuvant Therapy Treated HER2-Positive Breast Cancer Patients

Background

We explored the therapeutic and prognostic effect of YAP/TAZ intensityinHER2-positive breast cancer patients. We also investigated the relationship between YAP/TAZ expression and Trastuzumab-resistance.

Methods

We collected clinicopathological information from 397 cases. We evaluated therapeutic and prognostic effect of YAP/TAZ and other variables. We also cultivated Trastuzumab-resistance cell lines and explored relationship between YAP/TAZ and Trastuzumab-resistance.

Results

Over-expression of YAP/TAZ was remarkable in Trastuzumab-resistant cells, and so did HER3 and HER2/HER3 heterodimer. Inhibition of YAP/TAZ expression reversed Trastuzumab-resistance.YAP/TAZ deficiency contributed to favorable therapeutic response, and so did hormone receptor insufficiency and chemotherapy dosage inferiority. Deficient YAP/TAZ intensity and abundant hormone receptor intensity contributed to better survival. Over-expression of YAP/TAZ was obvious in recurrent cases in comparison with their matching primary lesions. Prognostic superiority of insufficient YAP/TAZ intensity was more outstanding in hormone receptor negative cases. Over-expression of YAP/TAZ and HER3 was generally synchronous. Absence of HER3 expression in residual lesions might correlate with better breast cancer-free survival.

Conclusions

Over-expression of YAP/TAZ as well as HER-3 and HER2/HER3 heterodimer was synchronously remarkable in Trastuzumab-resistant cell lines. Inhibition of YAP/TAZ expression reversed Trastuzumab resistance. Deficient YAP/TAZ intensity as well as insufficient hormone receptor intensity and high chemotherapy dosage contributed to favorable therapeutic response. Deficient YAP/TAZ intensity and abundant hormone receptor intensity contributed to better survival, and so did absence of HER3expression in residual lesions. Prognostic superiority of YAP/TAZ expression depended on hormone receptor status. Cases with synchronous over-expression of YAP/TAZ and HER3 suffered poor survival, which revealed the potential effect of YAP/TAZ-HER2/HER3 crosstalk in prognosis of HER2-positive patients.

The Landscape of Iron Metabolism-Related and Methylated Genes in the Prognosis Prediction of Clear Cell Renal Cell Carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is characteristics of resistance to chemotherapy and radiotherapy. The prognosis of ccRCC was dismay with immense diversity. Iron metabolism disturbance is a common phenomenon in ccRCC. The purpose of our study is to identify and validate the candidate prognostic gene signature of iron metabolism and methylation closely related to the poor prognosis of ccRCC through comprehensive bioinformatics analysis in The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases.

Methods: The prognostic iron metabolism-related genes were screened according to the overlapping differentially expressed genes (DEGs) from the TCGA database. We built a prognostic model using risk score method to predict OS, each ccRCC patient's risk score was calculated, and the resulting score can divide these patients into two categories according to the cut-point risk score. The prognostic significance of the hub genes was further evaluated with the Kaplan-Meier (KM) survival and Receiver Operating Characteristic (ROC) curve analysis. Univariate and multivariate Cox regression analysis was implemented to evaluate the impact of each variable on OS. Furthermore, the prediction power of the 25 gene signatures has been validated using an independent ccRCC cohort from the GEO database. The Gene Set Enrichment Analysis (GSEA) identified the characteristics of hub related oncogenes. Finally, we utilize Weighted Gene Co-expression Network Analysis (WGCNA) to investigate the co-expression network based on these DEGs.

Results: In this study, we identified and validated 25 iron metabolism-related and methylated genes as the prognostic signatures, which differentiated ccRCC patients into high and low risk subgroups. The KM analysis showed that the survival rate of the high-risk patients was significantly lower than that of the low-risk patients. The risk score calculated with 25 gene signatures could largely predict OS and DFS for 1, 3, and 5 years in patients with ccRCC.

Conclusions: Taken together, we identified the key iron metabolism-related and methylated genes for ccRCC through a comprehensive bioinformatics analysis. This study provides a reliable and robust gene signature for the prognostic predictor of ccRCC patients and maybe provides a promising treatment strategy for this lethal disease.

Role of miRNA-542-5p in the tumorigenesis of osteosarcoma

Osteosarcoma, one of the most common malignant bone tumors, is characterized by a high rate of metastasis, and the survival rate of patients with metastatic osteosarcoma is poor. Previous studies have reported that miRNAs often regulate the occurrence and development of various tumors. In this work, we identified miRNA‐542‐5p as a critical miRNA in osteosarcoma by overlapping three Gene Expression Omnibus datasets, and then evaluated miRNA‐542‐5p expression profiles using Gene Expression Omnibus and Sarcoma‐microRNA Expression Database. We used MISIM to investigate miRNAs correlated with miR‐542 and identified potential target genes of miRNA‐542‐5p using miRWalk. Functional and pathway enrichment analyses were performed using The Database for Annotation, Visualization and Integrated Discovery. Protein–protein interaction was performed using Search Tool for the Retrieval of Interacting Genes and Cytoscape. We report that the relative level of miRNA‐542‐5p was significantly higher in osteosarcoma than in healthy bone. Expressions of hsa‐miR‐330 and hsa‐miR‐1202 were found to be strongly correlated with that of miR‐542‐5p. Furthermore, we identified a total of 514 down‐regulated genes as possible targets of miR‐542‐5p. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that the putative target genes of miR‐542‐5p were most enriched in the cell‐cycle process. The differentially expressed genes CDCA5, PARP12 and HSPD1 were found to be hub genes in protein–protein interaction networks. Finally, transfection of the osteosarcoma cell line U2OS with miR‐542‐5p mimics or inhibitor revealed that miR‐542‐5p can promote cell proliferation. In conclusion, our results suggest that miR‐542‐5p may promote osteosarcoma proliferation; thus, this miRNA may have potential as a biomarker for diagnosis and prognosis.

Role of Secreted Frizzled-Related Protein 1 in Early Mammary Gland Tumorigenesis and Its Regulation in Breast Microenvironment

In mice, the lack of secreted frizzled-related protein 1 (SFRP1) is responsible for mammogenesis and hyperplasia, while, in bovines, its overexpression is associated with post-lactational mammary gland involution. Interestingly, there are no reports dealing with the role of SFRP1 in female involution. However, SFRP1 dysregulation is largely associated with human tumorigenesis in the literature. Indeed, the lack of SFRP1 is associated with both tumor development and patient prognosis. Considering the increased risk of breast tumor development associated with incomplete mammary gland involution, it is crucial to demystify the "grey zone" between physiological age-related involution and tumorigenesis. In this review, we explore the functions of SFRP1 involved in the breast involution processes to understand the perturbations driven by the disappearance of SFRP1 in mammary tissue. Moreover, we question the presence of recurrent microcalcifications identified by mammography. In bone metastases from prostate primary tumor, overexpression of SFRP1 results in an osteolytic response of the tumor cells. Hence, we explore the hypothesis of an osteoblastic differentiation of mammary cells induced by the lack of SFRP1 during lobular involution, resulting in a new accumulation of hydroxyapatite crystals in the breast tissue.

Novel Biomarkers Associated With Progression and Prognosis of Bladder Cancer Identified by Co-expression Analysis

Our study's goal was to screen novel biomarkers that could accurately predict the progression and prognosis of bladder cancer (BC). Firstly, we used the Gene Expression Omnibus (GEO) dataset GSE37815 to screen differentially expressed genes (DEGs). Secondly, we used the DEGs to construct a co-expression network by weighted gene co-expression network analysis (WGCNA) in GSE71576. We then screened the brown module, which was significantly correlated with the histologic grade (r = 0.85, p = 1e-12) of BC. We conducted functional annotation on all genes of the brown module and found that the genes of the brown module were mainly significantly enriched in "cell cycle" correlation pathways. Next, we screened out two real hub genes (ANLN, HMMR) by combining WGCNA, protein-protein interaction (PPI) network and survival analysis. Finally, we combined the GEO datasets (GSE13507, GSE37815, GSE31684, GSE71576). Oncomine, Human Protein Atlas (HPA), and The Cancer Genome Atlas (TCGA) dataset to confirm the predict value of the real hub genes for BC progression and prognosis. A gene-set enrichment analysis (GSEA) revealed that the real hub genes were mainly enriched in "bladder cancer" and "cell cycle" pathways. A survival analysis showed that they were of great significance in predicting the prognosis of BC. In summary, our study screened and confirmed that two biomarkers could accurately predict the progression and prognosis of BC, which is of great significance for both stratification therapy and the mechanism study of BC.

Oxidative phosphorylation inhibition induces anticancerous changes in therapy-resistant-acute myeloid leukemia patient cells

Treatment of acute myeloid leukemia (AML) is still a challenge because of common relapses or resistance to treatment. Therefore, the development of new therapeutic approaches is necessary. Various studies have shown that certain cancers, including some chemoresistant AML subsets, have upregulated oxidative phosphorylation. In this study, we aimed to assess treatment-resistant AML patients' cell modulation using oxidative phosphorylation inhibitors metformin and atovaquone alone and in various combinations with cytosine analog cytarabine and apoptosis inducer venetoclax. Metabolic activity analysis using Agilent Seahorse XF Extracellular Flux Analyzer revealed that peripheral blood mononuclear cells' metabolic state was different among treatment-resistant AML patients. We demonstrated that metformin decreased therapy-resistant-AML cell oxidative phosphorylation ex vivo, cotreatment with cytarabine and venetoclax slightly increased the effect. However, treatment with atovaquone did not have a marked effect in our experiment. Cell treatment had a slight effect on cell proliferation inhibition; combination of metformin, cytarabine, and venetoclax had the strongest effect. Moreover, a slightly higher effect on cell proliferation and cell cycle regulation was demonstrated in the cells with higher initial oxidative phosphorylation rate as demonstrated by gene expression analysis using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Proteomic analysis by liquid chromatography-mass spectrometry demonstrated that chemoresistant AML cell treatment with metformin modulated metabolic pathways, while metformin combination with cytarabine and venetoclax boosted the effect. We suggest that oxidative phosphorylation inhibition is effective but not sufficient for chemoresistant AML treatment. Indeed, it causes anticancerous changes that might have an important additive role in combinatory treatment.

Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks

Identification of disease-associated miRNAs (disease miRNAs) are critical for understanding etiology and pathogenesis. Most previous methods focus on integrating similarities and associating information contained in heterogeneous miRNA-disease networks. However, these methods establish only shallow prediction models that fail to capture complex relationships among miRNA similarities, disease similarities, and miRNA-disease associations. We propose a prediction method on the basis of network representation learning and convolutional neural networks to predict disease miRNAs, called CNNMDA. CNNMDA deeply integrates the similarity information of miRNAs and diseases, miRNA-disease associations, and representations of miRNAs and diseases in low-dimensional feature space. The new framework based on deep learning was built to learn the original and global representation of a miRNA-disease pair. First, diverse biological premises about miRNAs and diseases were combined to construct the embedding layer in the left part of the framework, from a biological perspective. Second, the various connection edges in the miRNA-disease network, such as similarity and association connections, were dependent on each other. Therefore, it was necessary to learn the low-dimensional representations of the miRNA and disease nodes based on the entire network. The right part of the framework learnt the low-dimensional representation of each miRNA and disease node based on non-negative matrix factorization, and these representations were used to establish the corresponding embedding layer. Finally, the left and right embedding layers went through convolutional modules to deeply learn the complex and non-linear relationships among the similarities and associations between miRNAs and diseases. Experimental results based on cross validation indicated that CNNMDA yields superior performance compared to several state-of-the-art methods. Furthermore, case studies on lung, breast, and pancreatic neoplasms demonstrated the powerful ability of CNNMDA to discover potential disease miRNAs.

A co-expression network for differentially expressed genes in bladder cancer and a risk score model for predicting survival

Background

Urothelial bladder cancer (BLCA) is one of the most common internal malignancies worldwide with poor prognosis. This study aims to explore effective prognostic biomarkers and construct a prognostic risk score model for patients with BLCA.

Methods

Weighted gene co-expression network analysis (WGCNA) was used for identifying the co-expression module related to the pathological stage of BLCA based on the RNA-Seq data retrieved from The Cancer Genome Atlas database. Prognostic biomarkers screened by Cox proportional hazard regression model and random forest were used to construct a risk score model that can predict the prognosis of patients with BLCA. The GSE13507 dataset was used as the independent testing dataset to test the performance of the risk score model in predicting the prognosis of patients with BLCA.

Results

WGCNA identified seven co-expression modules, in which the brown module consisted of 77 genes was most significantly correlated with the pathological stage of BLCA. Cox proportional hazard regression model and random forest identified TPST1 and P3H4 as prognostic biomarkers. Elevated TPST1 and P3H4 expressions were associated with the high pathological stage and worse survival. The risk score model based on the expression level of TPST1 and P3H4 outperformed pathological stage indicators and previously proposed prognostic models.

Conclusion

The gene co-expression network-based study could provide additional insight into the tumorigenesis and progression of BLCA, and our proposed risk score model may aid physicians in the assessment of the prognosis of patients with BLCA.

Downregulation of microRNA-374a predicts poor prognosis in human glioma

Certain microRNAs (miRNAs/miRs) may be used as prognostic biomarkers in various types of cancer. The purpose of the present study was to identify miRNAs that were abnormally expressed in glioma of different grades, and to evaluate their clinical implications in patients with glioma. The differentially expressed miRNAs were evaluated from the expression profiles of six glioma tissues (three low-grade and three high-grade gliomas) determined using a microarray platform. Reverse transcription-quantitative polymerase chain reaction analysis was used to further verify the aberrant expression of the candidate miRNA in a set of 42 patients and 5 healthy controls. The miRNA target genes were predicted and the protein-protein interaction network was generated; furthermore, functional enrichment analysis of the target genes in Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was performed. Kaplan-Meier curves and Log-rank analysis, as well as multivariate Cox regression analysis were performed to assess the association of the candidate miRNA with patient survival. A total of 15 differentially expressed miRNAs, including 13 downregulated and 2 upregulated miRNAs, were identified by comparison of low-grade and high-grade glioma tissues. The miR-374a expression of high-grade gliomas was significantly lower than that of low-grade gliomas (fold change, -4.43; P=0.027). The expression levels of miR-374a gradually decreased with the increase of the pathological grade of glioma. Pearson's Chi-square test was used to determine the association of miR-374a expression with several clinicopathological factors. Furthermore, low expression of miR-374a was determined to be an independent prognostic marker and that it was significantly associated with overall survival (P=0.0213). GO and KEGG pathway analysis revealed that the target genes of miR-374a may be involved in the regulation of the RNA polymerase II promoter and mTOR signaling pathway. The four hub genes (CCND1, SP1, CDK4, CDK6) were also identified by PPI network analysis. In conclusion, the present study indicated that miR-374a may be used as a promising prognostic biomarker for the screening of high-risk populations and for the assessment of the prognosis of patients with glioma.

Med19 is targeted by miR-101-3p/miR-422a and promotes breast cancer progression by regulating the EGFR/MEK/ERK signaling pathway

Our previous study found that mediator complex subunit 19 (Med19) is upregulated and involved in breast cancer tumorigenesis; however, the detailed effects and mechanism of Med19 in breast cancer require further study. In this study, we found that Med19 was obviously elevated in human breast cancer tissues, which was significantly associated with larger tumors, high-grade malignant features and poor prognosis. Furthermore, Med19 enhanced breast cancer cell proliferation, epithelial-mesenchymal transition, invasion and migration in vitro and in vivo. Med19 interacted with epidermal growth factor receptor (EGFR) and increased EGFR expression. Moreover, Med19 activated the EGFR/mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) pathway and exerted its oncogenic activity in an EGFR signaling-mediated manner. In addition, Med19 expression was regulated by miR-101-3p and miR-422a. Med19 expression positively correlated with EGFR expression and negatively correlated with miR-101-3p and miR-422a expression in human breast cancer tissues. Med19 mediated the crosstalk between miR-101-3p/miR-422a and the EGFR/MEK/ERK signaling pathway. This study revealed a new miR-101-3p/miR-422a-Med19-EGFR/MEK/ERK axis that plays a significant role in breast cancer progression. These results help elucidate the potential mechanisms of Med19 in human breast cancer progression.

The construction and analysis of ceRNA networks in invasive breast cancer: a study based on The Cancer Genome Atlas

Background

Studies 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.

Purpose

In 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.

Methods

Abnormal 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.

Results

Differential 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.

Conclusion

This 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.

MicroRNA-152 Acts as a Tumor Suppressor MicroRNA by Inhibiting Krüppel-Like Factor 5 in Human Cervical Cancer

Aberrant expression of microRNA-152 (miR-152) is frequently observed in human cancers including ovarian cancer, breast cancer, prostate cancer, and gastric cancer. However, its expression and functional role in cervical cancer (CC) are poorly understood. Also, the association between miR-152 and Krüppel-like factor 5 (KLF5) expression in CC remains unclear. In this study, analyzing the expression of miR-152 by quantitative real-time PCR (qRT-PCR) revealed it was sharply reduced in CC tissues and cell lines. In addition, the negative correlation of miR-152 expression and KLF5 expression was observed. The dual-luciferase reporter assay validated that KLF5 was a target of miR-152. In vitro functional assays revealed that miR-152 could inhibit cell proliferation and cell cycle progression through regulating the expression of KLF5. Taken together, our study suggested that miR-152 functions as a tumor suppressor in CC, and the miR-152/KLF5 axis may provide novel therapeutic targets for CC treatment.