PurposeThis study aimed to probe into the associations among circular RNA ZFR (circ-ZFR), miR-130a/miR-107, and PTEN, and to investigate the regulatory mechanism of circ-ZFR‒miR-130a/miR-107‒PTEN axis in gastric cancer (GC).Materials and MethodsGSE89143 microarray data used in the study were acquired from publicly available Gene Expression Omnibus database to identify differentially expressed circular RNAs inGC tissues. The expressions of circ-ZFR, miR-130a, miR-107, and PTEN were examined by real-time reverse transcription polymerase chain reaction, while PTEN protein expression was measured by western blot. The variation of GC cell proliferation and apoptosis was confirmed by cell counting kit-8 assay and flow cytometry analysis. The targeted relationships among circZFR, miR-130a/miR-107, and PTEN were predicted via bioinformatics analysis and demonstrated by dual-luciferase reporter assay and RNA immunoprecipitation assay. The impact of ZFR on gastric tumor was further verified in xenograft mice model experiment.ResultsCirc-ZFR and PTEN were low-expressed whereas miR-107 and miR-130a were highexpressed in GC tissues and cells. There existed targeted relationships and interactions between miR-130a/miR-107 and ZFR/PTEN. Circ-ZFR inhibited GC cell propagation, cell cycle and promoted apoptosis by sponging miR-107/miR-130a, while miR-107/miR-130a promoted GC cell propagation and impeded apoptosis through targeting PTEN. Circ-ZFR inhibited cell proliferation and facilitated apoptosis in GC by sponging miR-130a/miR-107 and modulating PTEN. Circ-ZFR curbed GC tumor growth and affected p53 protein expression in vivo.ConclusionCirc-ZFR restrained GC cell proliferation, induced cell cycle arrest and promoted apoptosis by sponging miR-130a/miR-107 and regulating PTEN.

The lung is the most common extra-abdominal site of metastasis in colorectal cancer (CRC), in which circular RNA (circRNA) may have a crucial role. Therefore, the present study detected circRNA expression to identify novel targets to further study lung metastasis in CRC. In the present study, total RNA was extracted from CRC tissues of patients with and without lung metastasis to perform high-throughput microarray assay in order to detect differentially expressed circRNA. Following this, gene ontology (GO) and pathway analyses of the genes producing differentially expressed circRNA were performed to predict the function of circRNA using standard enrichment computational methods. Additionally, the circRNA/microRNA (miRNA) interactions were constructed with bioinformatics methods to predict the binding of miRNA with circRNA. In the CRC tissues from patients with lung metastasis, 431 circRNA were detected to be differentially expressed, including 192 upregulated and 239 downregulated over 2-fold compared with the CRC tissues without metastasis. Furthermore, GO analysis revealed that the genes producing upregulated circRNA were involved in DNA repair, while the genes producing downregulated circRNA were enriched in signal transduction. By pathway analysis, it was identified that the genes producing downregulated circRNA were involved in the nuclear factor-κB and Wnt signaling pathway in the CRC tissues from patients with lung metastasis compared with the CRC tissues without metastasis. In addition, it was demonstrated that hsa_circRNA_105055, hsa_circRNA_086376 and hsa_circRNA_102761 could commonly bind with miR-7 regulating target genes PRKCB, EPHA3, BRCA1 and ABCC1. The findings of the present study may provide a novel perspective on circRNA and lay a foundation for future research of potential roles of circRNA in CRC with lung metastasis.

The present study aimed to construct prospective models for tumor grading of rectal carcinoma by using magnetic resonance (MR)-based radiomics features. A set of 118 patients with rectal carcinoma was analyzed. After imbalance-adjustments of the data using Synthetic Minority Oversampling Technique (SMOTE), the final data set was randomized into the training set and validation set at the ratio of 3:1. The radiomics features were captured from manually segmented lesion of magnetic resonance imaging (MRI). The most related radiomics features were selected using the random forest model by calculating the Gini importance of initial extracted characteristics. A random forest classifier model was constructed using the top important features. The classifier model performance was evaluated via receive operator characteristic curve and area under the curve (AUC). A total of 1,131 radiomics features were extracted from segmented lesion. The top 50 most important features were selected to construct a random forest classifier model. The AUC values of grade 1, 2, 3, and 4 for training set were 0.918, 0.822, 0.775, and 1.000, respectively, and the corresponding AUC values for testing set were 0.717, 0.683, 0.690, and 0.827 separately. The developed feature selection method and machine learning-based prediction models using radiomics features of MRI show a relatively acceptable performance in tumor grading of rectal carcinoma and could distinguish the tumor subjects from the healthy ones, which is important for the prognosis of cancer patients.

Increasing data demonstrate that circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) play important roles in tumorigenesis. However, the mechanisms in colorectal cancer (CRC) remain unclear. Here, hundreds of significantly expressed circRNAs, and thousands of lncRNAs as well as mRNAs were identified. By qRT-PCR, one abnormal circRNA, lncRNA, and three mRNAs were verified in 24 pairs of tissues and blood samples, respectively. Then, by GO analysis, we found that the gene expression profile of linear counterparts of upregulated circRNAs in human CRC tissues preferred positive regulation of GTPase activity, cellular protein metabolic process, and protein binding, while that of downregulated circRNAs of CRC preferred positive regulation of cellular metabolic process, acetyl-CoA metabolic process, and protein kinase C activity. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that p53 signaling pathway was an important pathway in upregulated protein-coding genes, whereas cyclic guanosine monophosphate-protein kinase G (cGMP–PKG) signaling pathway was the top enriched KEGG pathway for downregulated transcripts. Furthermore, lncRNA–mRNA co-expression analysis demonstrated that downregulated lncRNA uc001tma.3 was negatively with CDC45 and positively with ELOVL4, BVES, FLNA, and HSPB8, while upregulated lncRNA NR_110882 was positively with FZD2. In addition, lncRNA–transcription factor (TF) co-expression analysis showed that the most relevant TFs were forkhead box protein A1 (FOXA1), transcription initiation factor TFIID submint 7 (TAF7), and adenovirus early region 1A(E1A)-associated protein p300 (EP300). Our findings offer a fresh view on circRNAs and lncRNAs and provide the foundation for further study on the potential roles of circRNAs and lncRNAs in colorectal cancer. Electronic supplementary material The online version of this article (10.1007/s10142-018-0641-9) contains supplementary material, which is available to authorized users.