Identification of messenger and long noncoding RNAs associated with gallbladder cancer via gene expression profile analysis

The present study aimed to investigate the long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) involved in the progression of gallbladder cancer and explore the potential physiopathologic mechanisms of gallbladder cancer in terms of competing endogenous RNAs (ceRNAs). The original lncRNA and mRNA expression profile data (nine gallbladder cancer tissues samples and nine normal gallbladder samples) in GSE76633 was downloaded from the Gene Expression Omnibus database. Differentially expressed mRNAs and lncRNAs between gallbladder cancer tissue and normal control were selected and the pathways in which they are involved were analyzed using bioinformatics analyses. MicroRNAs (miRNAs) were also predicted based on the differentially expressed mRNAs. Finally, the co-expression relation between lncRNA and mRNA was analyzed and the ceRNA network was constructed by combining the lncRNA-miRNA, miRNA-mRNA, and lncRNA-mRNA pairs. Overall, 373 significantly differentially expressed mRNAs and 47 lncRNAs were identified between cancer and normal tissue samples. The upregulated genes were significantly enriched in the extracellular matrix (ECM)-receptor interaction pathway, while the downregulated genes were involved in the complement and coagulation cascades. Altogether, 128 co-expression relations between lncRNA and mRNA were obtained. In addition, 196 miRNA-mRNA regulatory relations and 145 miRNA-lncRNA relation pairs were predicted. Finally, the lncRNA-miRNA-gene ceRNA network was constructed by combining the three types of relation pairs, such as XLOC_011309-miR-548c-3p-SPOCK1 and XLOC_012588-miR-765-CEACAM6. mRNAs and lncRNAs may be involved in gallbladder cancer progression via ECM-receptor interaction pathways and the complement and coagulation cascades. Moreover, ceRNAs such as XLOC_011309-miR-548c-3p-SPOCK1 and XLOC_012588-miR-765-CEACAM6 can also be implicated in the pathogenesis of gallbladder cancer.     

miR-17 family miRNAs are expressed during early mammalian development and regulate stem cell differentiation

MicroRNAs are small non-coding RNAs that regulate protein expression by binding 3′UTRs of target mRNAs, thereby inhibiting translation. Similar to siRNAs, miRNAs are cleaved by Dicer. Mouse and ES cell Dicer mutants demonstrate that microRNAs are necessary for embryonic development and cellular differentiation. However, technical obstacles and the relative infancy of this field have resulted in few data on the functional significance of individual microRNAs. We present evidence that miR-17 family members, miR-17-5p, miR-20a, miR-93, and miR-106a, are differentially expressed in developing mouse embryos and function to control differentiation of stem cells. Specifically, miR-93 localizes to differentiating primitive endoderm and trophectoderm of the blastocyst. We also observe high miR-93 and miR-17-5p expression within the mesoderm of gastrulating embryos. Using an ES cell model system, we demonstrate that modulation of these miRNAs delays or enhances differentiation into the germ layers. Additionally, we demonstrate that these miRNAs regulate STAT3 mRNA in vitro. We suggest that STAT3, a known ES cell regulator, is one target mRNA responsible for the effects of these miRNAs on cellular differentiation.     

circRNA-associated ceRNA network construction reveals the circRNAs involved in the progression and prognosis of breast cancer

Recently, increasing evidences show that circular RNAs (circRNAs) are important regulators of various diseases, especially cancer. However, the regulatory role and the potential mechanism of action of circRNAs in breast cancer remain largely unknown. In this study, weighted gene co-expression network analysis was conducted with the differentially expressed miRNAs and mRNAs in breast cancer from The Cancer Genome Atlas database to identify the key modules associated with the carcinogenesis of breast cancer. In the significant turquoise and brown modules, 22 miRNAs and 1877 mRNAs were identified, respectively. Then, We compared and predicted the target genes and performed survival analysis to identify the miRNAs and mRNAs related to the prognosis of breast cancer. A circRNA-related competitive endogenous RNA network was identified by database co-screening, and deleted in liver cancer 1 (DLC1) was identified as a key gene. Finally, to assess how genes in key modules and key genes contribute to the development of breast cancer, relevant pathway information was obtained through DAVID and Gene Set Enrichment Analysis. These data demonstrated that three circRNAs (hsa-circ-0083373, hsa-circ-0083374, and hsa-circ-0083375) that regulate DLC1 expression via hsa-mir-511 and are involved in the pathogenesis and development of breast cancer.     

PGC-Enriched miRNAs Control Germ Cell Development

Non-coding microRNAs (miRNAs) regulate the translation of target messenger RNAs (mRNAs) involved in the growth and development of a variety of cells, including primordial germ cells (PGCs) which play an essential role in germ cell development. However, the target mRNAs and the regulatory networks influenced by miRNAs in PGCs remain unclear. Here, we demonstrate a novel miRNAs control PGC development through targeting mRNAs involved in various cellular pathways. We reveal the PGC-enriched expression patterns of nine miRNAs, including miR-10b, -18a, -93, -106b, -126-3p, -127, -181a, -181b, and -301, using miRNA expression analysis along with mRNA microarray analysis in PGCs, embryonic gonads, and postnatal testes. These miRNAs are highly expressed in PGCs, as demonstrated by Northern blotting, miRNA in situ hybridization assay, and miRNA qPCR analysis. This integrative study utilizing mRNA microarray analysis and miRNA target prediction demonstrates the regulatory networks through which these miRNAs regulate their potential target genes during PGC development. The elucidated networks of miRNAs disclose a coordinated molecular mechanism by which these miRNAs regulate distinct cellular pathways in PGCs that determine germ cell development.     

Genome-Wide Analyses of Radioresistance-Associated miRNA Expression Profile in Nasopharyngeal Carcinoma Using Next Generation Deep Sequencing

Background

Rapidly growing evidence suggests that microRNAs (miRNAs) are involved in a wide range of cancer malignant behaviours including radioresistance. Therefore, the present study was designed to investigate miRNA expression patterns associated with radioresistance in NPC.

Methods

The differential expression profiles of miRNAs and mRNAs associated with NPC radioresistance were constructed. The predicted target mRNAs of miRNAs and their enriched signaling pathways were analyzed via biological informatical algorithms. Finally, partial miRNAs and pathways-correlated target mRNAs were validated in two NPC radioreisitant cell models.

Results

50 known and 9 novel miRNAs with significant difference were identified, and their target mRNAs were narrowed down to 53 nasopharyngeal-/NPC-specific mRNAs. Subsequent KEGG analyses demonstrated that the 53 mRNAs were enriched in 37 signaling pathways. Further qRT-PCR assays confirmed 3 down-regulated miRNAs (miR-324-3p, miR-93-3p and miR-4501), 3 up-regulated miRNAs (miR-371a-5p, miR-34c-5p and miR-1323) and 2 novel miRNAs. Additionally, corresponding alterations of pathways-correlated target mRNAs were observed including 5 up-regulated mRNAs (ICAM1, WNT2B, MYC, HLA-F and TGF-β1) and 3 down-regulated mRNAs (CDH1, PTENP1 and HSP90AA1).

Conclusions

Our study provides an overview of miRNA expression profile and the interactions between miRNA and their target mRNAs, which will deepen our understanding of the important roles of miRNAs in NPC radioresistance.     

mRNA and microRNA selection for breast cancer molecular subtype stratification using meta-heuristic based algorithms

Cancer subtype stratification, which may help to make a better decision in treating cancerous patients, is one of the most crucial and challenging problems in cancer studies. To this end, various computational methods such as Feature selection, which enhances the accuracy of the classification and is an NP-Hard problem, have been proposed. However, the performance of the applied methods is still low and can be increased by the state-of-the-art and efficient methods. We used 11 efficient and popular meta-heuristic algorithms including WCC, LCA, GA, PSO, ACO, ICA, LA, HTS, FOA, DSOS and CUK along with SVM classifier to stratify human breast cancer molecular subtypes using mRNA and micro-RNA expression data. The applied algorithms select 186 mRNAs and 116 miRNAs out of 9692 mRNAs and 489 miRNAs, respectively. Although some of the selected mRNAs and miRNAs are common in different algorithms results, six miRNAs including miR-190b, miR-18a, miR-301a, miR-34c-5p, miR-18b, and miR-129-5p were selected by equal or more than three different algorithms. Further, six mRNAs, including HAUS6, LAMA2, TSPAN33, PLEKHM3, GFRA3, and DCBLD2, were chosen through two different algorithms. We have reported these miRNAs and mRNAs as important diagnostic biomarkers to the stratification of breast cancer subtypes. By investigating the literature, it is also observed that most of our reported mRNAs and miRNAs have been proposed and introduced as biomarkers in cancer subtypes stratification.     

Integrated analysis of co‐expression and ceRNA network identifies five lncRNAs as prognostic markers for breast cancer

Long non‐coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co‐expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan‐Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co‐expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2‐AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.     

Reference genes for the relative quantification of microRNAs in renal cell carcinomas and their metastases

To obtain accurate results in miRNA expression changes between different sample sets using real-time quantitative polymerase chain reaction (RT-qPCR) analyses, normalization to reference genes that are stably expressed across the sample sets is generally used. A literature search of miRNA expression studies in renal cell carcinoma (RCC) proved that non-miRNAs such as small RNAs or mRNAs have most frequently been used without preceding validation of their suitability. In this study, the most stably expressed miRNAs were ascertained from microarray-based data of miRNA expression in nonmalignant and malignant samples from clear cell RCC and from corresponding distant RCC metastases using the geNorm and NormFinder algorithms. Validation experiments with RT-qPCR were performed for the four best-ranked miRNAs (miR-28, miR-103, miR-106a, miR-151) together with the small RNU6B, RNU44, and RNU48 mostly described in literature. miR-28, miR-103, miR-106a, and RNU48 were proved as the most stably expressed genes. miR-28 is recommended as normalizer if only a single reference gene can be used, while the combinations of miR-28 and miR-103 or of miR-28, miR-103, and miR-106a, respectively, are preferred. RNU6B most frequently used as normalizer in miRNA expression studies should be abandoned in order to avoid misleading results.     

Molecular characterization of lung cancer: A two-miRNA prognostic signature based on cancer stem-like cells related genes

Lung cancer is one of the deadliest cancers worldwide. To increase the survival rate of lung cancer, it is necessary to explore specific prognosis markers. More and more evidence finds that noncoding RNA is closely associated with the survival of lung cancer, and cancer stem cells (CSCs) also play a significant role in the progress of lung cancer. The objective of this study is to find CSLCs genes that affect the prognosis of lung cancer. The differential expression of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), messenger RNAs (mRNAs) in the Cancer Genome Atlas (TCGA) database and differential expression data from microarray of CD326⁺ and CD326⁻ A549 cell are intersected to identify stable and consistent expression genes (2 lncRNAs, 15 miRNAs, and 134 mRNAs). The intersection of lncRNAs and miRNAs is analyzed by univariate and multivariate Cox regression to obtained prognostic genes. Two miRNAs (miR-30b-5p and miR-29c-3p) are significantly correlated with the overall survival rate. Then using these two miRNAs to construct a risk score model as a prognosis signature of lung cancer. Subsequently, we analyzed the association between two miRNAs and clinical information of lung cancer patients, of which T stage, Neoplasm cancer and risk score (P < .05) can be used as independent prognostic indicators of lung cancer. Finally, target genes of 2 miRNAs and 134 mRNAs were annotated with Gene Ontology and analyzed with Kyoto Encyclopedia of Genes and Genomes pathway, and verified with the GEO database. In summary, this study illustrates the role of miRNAs in the promotion of lung cancer by CSCs, which is important to find molecular biomarkers of lung cancer.     

Construction and analysis of dysregulated lncRNA-associated ceRNA network in colorectal cancer

Colorectal cancer (CRC) is one of the most frequently diagnosed digestive system cancer. The aim of the present study was to investigate the interactions among messenger RNAs (mRNAs), microRNAs (miRNAs), and long noncoding RNAs (lncRNAs) in CRC to reveal the mechanisms of CRC. Differentially expressed genes (DEGs) were identified from public gene expression data sets. One thousand eighty-one common dysregulated mRNAs in two data sets were identified. Gene function analysis and protein-protein interaction network analysis indicated that these DEGs might play important roles in CRC. LINC00365 was selected through coding- noncoding network analysis and its expression was validated upregulated in 22 paired clinical samples and four CRC cell lines. A competing endogenous RNA network composed of 70 miRNAs, nine mRNAs, and LINC00365 was constructed. Eight of nine mRNAs were validated upregulated in The Cancer Genome Atlas data set. Our results suggested that LINC00365 was an oncogene in CRC and it could regulate the expression of several mRNAs through sponging miRNAs.     

Over-Expression of miR-106b Promotes Cell Migration and Metastasis in Hepatocellular Carcinoma by Activating Epithelial-Mesenchymal Transition Process

Hepatocellular carcinoma (HCC) is one the the most fatal cancers worldwide. The poor prognosis of HCC is mainly due to the developement of distance metastasis. To investigate the mechanism of metastasis in HCC, an orthotopic HCC metastasis animal model was established. Two sets of primary liver tumor cell lines and corresponding lung metastasis cell lines were generated. In vitro functional analysis demonstrated that the metastatic cell line had higher invasion and migration ability when compared with the primary liver tumor cell line. These cell lines were subjected to microRNA (miRNAs) microarray analysis to identify differentially expressed miRNAs which were associated with the developement of metastasis in vivo. Fifteen human miRNAs, including miR-106b, were differentially expressed in 2 metastatic cell lines compared with the primary tumor cell lines. The clinical significance of miR-106b in 99 HCC clinical samples was studied. The results demonstrated that miR-106b was over-expressed in HCC tumor tissue compared with adjacent non-tumor tissue (p = 0.0005), and overexpression of miR-106b was signficantly correlated with higher tumor grade (p = 0.018). Further functional studies demonstrated that miR-106b could promote cell migration and stress fiber formation by over-expressing RhoGTPases, RhoA and RhoC. In vivo functional studies also showed that over-expression of miR-106b promoted HCC metastasis. These effects were related to the activation of the epithelial-mesenchymal transition (EMT) process. Our results suggested that miR-106b expression contributed to HCC metastasis by activating the EMT process promoting cell migration in vitro and metastasis in vivo.     

Retracted: Deep integrative analysis of microRNA-mRNA regulatory networks for biomarker and target discovery in chondrosarcoma

Chondrosarcoma (CHS) is a common malignant bone sarcoma and its occurrence increases with age. microRNAs (miRNAs) are a class of noncoding RNAs that participate in various biological processes and disease pathogenesis by targeting functional messenger RNA (mRNA). However, the modulation of miRNAs in CHS remains largely unknown. In this study, we performed integrative analysis to explore the expression profiles of miRNAs and mRNAs, together with their interaction networks in human CHS tissues and cell lines by RNA-seq (miRNA and mRNA). A total of 133 and 796 differentially expressed miRNAs and mRNAs were identified (|Fold change| ≥ 2 and P-value ≤ 0.5). miRNA-mRNA regulatory interactions between 55 miRNAs and 242 mRNAs were screened by the Pearson correlation analysis and target prediction. mRNAs in the network were enriched to 145 Gene Ontology terms and 35 Kyoto Encyclopedia of Genes and Genomes pathways. Specifically, some key regulators (hub-miRNAs) in the network (miR-622, miR-4539, miR-145, miR-25, and miR-96) were suggested to play important regulatory roles in the pathogenesis of CHS. In addition, functional experiments validated that miR-622 regulated CHS cell proliferation by targeting bone morphogenetic protein 1 (BMP1).     

The regulatory effect of 6-TG on lncRNA–miRNA–mRNA ceRNA network in triple-negative breast cancer cell line

Breast cancer is one of the most prevalent and recurring cancer types that leads to deaths in women. Triple-negative breast cancer (TNBC) is difficult to treat due to the lack of therapeutic targets. Many studies have focused on identifying drugs for use as alternative treatments for breast cancer. Thioguanine (6-TG) exerts antitumor effects in cancer. Increasing evidence has demonstrated that competitive endogenous ribonucleic acids (ceRNAs) are involved in cancer processes. However, the mechanism by which 6-TG regulates lncRNA–miRNA–mRNAs has not been elucidated. We evaluated the antitumor effect of 6-TG in MDA-MB-231 cells and comprehensively analyzed the RNA-Seq data of MDA-MB-231 cells treated with 6-TG. Our results showed that most tumor pathways were blocked by 6-TG. The hub genes were FN1, FLNA, FLNB, VCL, GSN, MYH10, ACTN4, KDR and EREG, and they were all down-regulated after 6-TG treatment. The coexpression network consisted of 18 microRNAs (miRNAs), 9 long noncoding RNAs (lncRNAs) and 20 mRNAs. Hsa-mir-16-5p and Hsa-mir-335-5p targeted the greatest number of mRNAs in the network. These molecules could bind to PAX8-AS1 and eliminate the inhibition of target mRNA expression. We showed that PAX8-AS1 is the main lncRNA affected by 6-TG and that PAX8-AS1 regulates the hub genes in tumor pathways by competitively binding with miR-16-5p and miR-335-5p.     

Expression signatures of intragenic miRNAs and their corresponding host genes in myeloid leukemia cells

MicroRNAs (miRNAs) are a class of small non-coding RNAs involved in gene regulation. Approximately half of miRNAs are located within known genes and called intragenic miRNAs. 408 human intragenic miRNAs and their corresponding host genes were analyzed for genomic organization and functional characterization. Using quantitative real-time PCR, the expression levels of a subset of intragenic miRNAs and their host genes were examined in diverse myeloid leukemia cell lines, and their regulation in response to pharmacological stimuli was also evaluated. Expression of miR-22 strongly correlated with both myeloid leukemia subtypes and the expression of its host gene C17orf91 (p?<?0.05). The latter was absent in hematopoietic progenitors but abundant in erythroid and monocytic lineages. These results demonstrated that the expression signatures of miR-22 and C17orf91 are associated with developmental lineages and specific leukemia subtypes.