H19- and hsa-miR-338-3p-mediated NRP1 expression is an independent predictor of poor prognosis in glioblastoma

Glioblastoma multiforme (GBM) is the most common and also the most invasive brain cancer. GBM progression is rapid and its prognosis is poor. Therefore, finding molecular targets in GBM is a critical goal that could also play important roles in clinical diagnostics and treatments to improve patient prognosis. We jointly analyzed the GSE103227, GSE103229, and TCGA databases for differentially expressed RNA species, obtaining 52 long non-coding RNAs (lncRNAs), 31 microRNAs (miRNAs), and 186 mRNAs, which were used to build a competing endogenous RNA network. Kaplan–Meier and receiver operating characteristic (ROC) analyses revealed five survival-related lncRNAs: H19, LINC01574, LINC01614, RNF144A-AS1, and OSMR-AS1. With multiple optimization mRNAs, we found the H19-hsa-miR-338-3P-NRP1 regulatory pathway. Additionally, we noted high NRP1 expression in GBM patients, and Kaplan–Meier and ROC analyses showed that NRP1 expression was associated with GBM prognosis. Cox analysis indicated that NRP1 is an independent prognostic factor in GBM patients. In conclusion, H19 and hsa-miR-338-3P regulate NRP1 expression, and this pathway plays an important role in GBM.

The Potential CircRNAs in Imatinib Resistance of GIST

Background: Recent studies have found that circular RNA is an abundant RNA species, belongs to part of the competing endogenous RNA network(ceRNA), which was proved to play an important role in the development, diagnosis and progress of diseases.Methods: We determined the expression of circular RNAs in paired normal gastric tissues(N), primary GIST (gastrointestinal stromal tumor) tissues (Y or YC) and imatinib mesylate secondary resistance GIST tissues(C) with microarray and predicted 8677 dysregulated circular RNAs.Results: We identified 15 circRNAs was up-regulated and 8 circRNAs were down-regulated in C group. Gene ontology (GO)and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that these host linear transcripts that differentially express circular RNAs are involved in many key biological pathways., predicting the potential tumor-genesis and drug resistance mechanism was related with HIF-1 pathway, later we draw the cirRNA-miRNA-mRNA network involved in the HIF-1 pathway, found that several dysregulated circRNAs and the relationship between circRNA-miRNAs-mRNA, such as circRNA_06551, circRNA_14668, circRNA_04497, circRNA_08683, circRNA_09923(Green, down-regulation) and circRNA_23636, circRNA_15734(Red, up-regulation). Conclusions: Taken together, we identified a panel of dysregulated circRNAs that may be potential biomarkers even therapy relevant to the GIST, especially imatinib secondary resistance GIST.

Identification of a lncRNA-Related Competing Endogenous RNA Network in Recurrent Implantation Failure

Background Impaired endometrial receptivity is supposed to be a major element leading to recurrent implantation failure (RIF). Numerous studies have identified that the lncRNAs-miRNAs-mRNAs regulation network functions in the generation of receptive uterus. Long non-coding RNAs could act as competing endogenous RNAs in the pathogenesis of RIF. However, our understanding of the underlying mechanism is still limited. Results Based on the RNA-Seq results, 617 DEmRNAs, 69 DElncRNAs and 107 DEmiRNAs were identified in the RIF group compared with the control group. To investigate the role of lncRNAs in RIF, we constructed a lncRNA related ceRNA network. A total of 3 lncRNAs, 8 miRNAs and 69 genes were identified. Above all, our study obtained 120 lncRNAs-miRNAs-mRNAs relationships in the ceRNA network. Among three hub lncRNAs, PART1 and PWRN1 were upregulated whereas PGM5P3-AS1 was downregulated in RIF endometrium. Meanwhile, three down-regulated miRNAs (hsa-miR-1207-5p, hsa-miR-134-5p, hsa-miR-1225-5p) and five up-regulated miRNAs (hsa-miR-30c-5p, hsa-miR-30b-5p, hsa-miR-145-5p, hsa-miR-21-5p, hsa-miR-196b-5p) were shown. Conclusions We constructed a lncRNA-related ceRNA network and identified three hub lncRNAs in recurrent implantation failure. The results may provide further understanding in the pathogenesis of RIF as well as potential diagnostic and therapeutic targets.

The Potential circRNAs in Imatinib Resistance of GIST

Background: Circular RNAs are a recently (re-)discovered abundant RNA species, belongs to part of the competing endogenous RNA network(ceRNA), Which was proved to play a critical role in the development, diagnosis and progress of diseases. Methods: We analyzed the expression of circular RNAs in paired normal gastric tissues(N), primary GIST (gastrointestinal stromal tumor) tissues (Y or YC) and imatinib mesylate secondary resistance GIST tissues(C) with microarray and predicted 8677 dysregulated circular RNAs. Results: We identified 15 circRNAs was up-regulated and 8 circRNAs were down-regulated in C group. Gene ontology (GO)and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified that the host linear transcripts of these differentially expressed circRNAs were involved in many critical biological pathways and molecular functions, predicting the potential tumor-genesis and drug resistance mechanism was related with HIF-1 pathway, later we draw the cirRNA-miRNA-mRNA network involved in the HIF-1 pathway, found that several dysregulated circRNAs and the relationship between circRNA-miRNAs-mRNA, such as circRNA_06551, circRNA_14668, circRNA_04497, circRNA_08683, circRNA_09923(Green, down-regulation) and circRNA_23636, circRNA_15734(Red, up-regulation). Conclusions: Taken together, we identified a panel of dysregulated circRNAs that may be potential biomarkers even therapy relevant to the GIST, especially imatinib secondary resistance GIST.

Identification of a lncRNA-related Competing Endogenous RNA Network in Recurrent Implantation Failure

Background: Impaired endometrial receptivity is supposed to be a major element leading to recurrent implantation failure (RIF). Numerous studies have identified that the lncRNAs-miRNAs-mRNAs regulation network functions in the generation of receptive uterus. Long non-coding RNAs could act as competing endogenous RNAs in the pathogenesis of RIF. However, our understanding of the underlying mechanism is still limited. Results: Based on the RNA-Seq results, 617 DEmRNAs, 69 DElncRNAs and 107 DEmiRNAs were identified in the RIF group compared with the control group. To investigate the role of lncRNAs in RIF, we constructed a lncRNA related ceRNA network. A total of 3 lncRNAs, 8 miRNAs and 69 genes were identified. Above all, our study obtained 120 lncRNAs-miRNAs-mRNAs relationships in the ceRNA network. Among three hub lncRNAs, PART1 and PWRN1 were upregulated whereas PGM5P3-AS1 was downregulated in RIF endometrium. Meanwhile, three down-regulated miRNAs (hsa-miR-1207-5p, hsa-miR-134-5p, hsa-miR-1225-5p) and five up-regulated miRNAs (hsa-miR-30c-5p, hsa-miR-30b-5p, hsa-miR-145-5p, hsa-miR-21-5p, hsa-miR-196b-5p) were shown. Conclusions: We constructed a lncRNA-related ceRNA network and identified three hub lncRNAs in recurrent implantation failure. The results may provide further understanding in the pathogenesis of RIF as well as potential diagnostic and therapeutic targets.

Identification of N6-Methyladenosine-Related LncRNAs for Predicting Overall Survival and Clustering of a Potentially Novel Molecular Subtype of Breast Cancer

We aimed to identify a signature comprising N6-methyladenosine (m6A)-related long non-coding RNAs (lncRNAs) and molecular subtypes associated with breast cancer (BRCA). We obtained data of BRCA samples from The Cancer Genome Atlas database. The m6A-related lncRNA prognostic signature (m6A-LPS) included 10 lncRNAs previously identified as prognostic m6A-related lncRNAs and was constructed using integrated bioinformatics analysis and validated. Accordingly, a risk score based on the m6A-LPS signature was established and shown to confirm differences in survival between high-risk and low-risk groups. Three distinct genotypes were identified, whose characteristics included features of the tumor immune microenvironment in each subtype. Our results indicated that patients in Cluster 2 might have a worse prognostic outcome than those in other clusters. The three genotypes and risk subgroups were enriched in different biological processes and pathways, respectively. We then constructed a competing endogenous RNA network based on the prognostic m6A-related lncRNAs. Finally, we validated the expression levels of target lncRNAs in 72 clinical samples. In summary, the m6A-LPS and the potentially novel genotype may provide a theoretical basis for further study of the molecular mechanism of BRCA and may provide novel insights into precision medicine.