Circular RNA (circRNA) is a large group of RNA family extensively existed in cells and tissues. High-throughput sequencing provides a way to view circRNAs across different samples, especially in various diseases. However, there is still no comprehensive database for exploring the cancer-specific circRNAs. We collected 228 total RNA or polyA(-) RNA-seq samples from both cancer and normal cell lines, and identified 272 152 cancer-specific circRNAs. A total of 950 962 circRNAs were identified in normal samples only, and 170 909 circRNAs were identified in both tumor and normal samples, which could be further used as non-tumor background. We constructed a cancer-specific circRNA database (CSCD, http://gb.whu.edu.cn/CSCD). To understand the functional effects of circRNAs, we predicted the microRNA response element sites and RNA binding protein sites for each circRNA. We further predicted potential open reading frames to highlight translatable circRNAs. To understand the association between the linear splicing and the back-splicing, we also predicted the splicing events in linear transcripts of each circRNA. As the first comprehensive cancer-specific circRNA database, we believe CSCD could significantly contribute to the research for the function and regulation of cancer-associated circRNAs.

Background: Deregulated circular RNAs (circRNAs) are associated with the development of cancer and therapy resistance. However, functional research of circRNAs mostly focus on potential miRNA or protein binding and more potential regulation of circRNA on host gene DNA in cancers are yet to be inspected. Method: We performed total RNA sequencing on clinical breast cancer samples and identified the expression patterns of circRNAs and corresponding host genes in patient blood, tumor and adjacent normal tissues. qPCR, northern blot and in situ hybridization were used to validate the dysregulation of circRNA circSMARCA5. A series of procedures including R-loop dot-blotting, DNA-RNA immunoprecipitation and mass spectrum, etc. were conducted to explore the regulation of circSMARCA5 on the transcription of exon 15 of SMARCA5. Moreover, immunofluorescence and in vivo experiments were executed to investigate the overexpression of circSMARCA5 with drug sensitivities. Results: We found that circRNAs has average higher expression over its host linear genes in peripheral blood. Compared to adjacent normal tissues, circSMARCA5 is decreased in breast cancer tissues, contrary to host gene SMARCA5. The enforced expression of circSMARCA5 induced drug sensitivity of breast cancer cell lines in vitro and in vivo. Furthermore, we demonstrated that circSMARCA5 can bind to its parent gene locus, forming an R-loop, which results in transcriptional pausing at exon 15 of SMARCA5. CircSMARCA5 expression resulted in the downregulation of SMARCA5 and the production of a truncated nonfunctional protein, and the overexpression of circSMARCA5 was sufficient to improve sensitivity to cytotoxic drugs. Conclusion: Our results revealed a new regulatory mechanism for circRNA on its host gene and provided evidence that circSMARCA5 may serve as a therapeutic target for drug-resistant breast cancer patients.

Two genes are synthetically lethal (SL) when defects in both are lethal to a cell but a single defect is non-lethal. SL partners of cancer mutations are of great interest as pharmacological targets; however, identifying them by cell line-based methods is challenging. Here we develop MiSL (Mining Synthetic Lethals), an algorithm that mines pan-cancer human primary tumour data to identify mutation-specific SL partners for specific cancers. We apply MiSL to 12 different cancers and predict 145,891 SL partners for 3,120 mutations, including known mutation-specific SL partners. Comparisons with functional screens show that MiSL predictions are enriched for SLs in multiple cancers. We extensively validate a SL interaction identified by MiSL between the IDH1 mutation and ACACA in leukaemia using gene targeting and patient-derived xenografts. Furthermore, we apply MiSL to pinpoint genetic biomarkers for drug sensitivity. These results demonstrate that MiSL can accelerate precision oncology by identifying mutation-specific targets and biomarkers.

BackgroundRobust and precise molecular prognostic predictors for luminal breast cancer are required. This study aimed to identify key methylation sites in luminal breast cancer, as well as precise molecular tools for predicting prognosis.MethodsWe compared methylation levels of normal and luminal breast cancer samples from The Cancer Genome Atlas dataset. The relationships among differentially methylated sites, corresponding mRNA expression levels and prognosis were further analysed. Differentially expressed genes in normal and cancerous samples were analysed, followed by the identification of prognostic signature genes. Samples were divided into low- and high-risk groups based on the signature genes. Prognoses of low- and high-risk groups were compared. The Gene Expression Omnibus dataset were used to validate signature genes for prognosis prediction. Prognosis of low- and high-risk groups in Luminal A and Luminal B samples from the TCGA and the Metabric cohort dataset were analyzed. We also analysed the correlation between clinical features of low- and high- risk groups as well as their differences in gene expression.ResultsFourteen methylation sites were considered to be related to luminal breast cancer prognosis because their methylation levels, mRNA expression and prognoses were closely related to each other. The methylation level of SOSTDC1 was used to divide samples into hypo- and hyper-methylation groups. We also identified an mRNA signature, comprising eight transcripts, ESCO2, PACSIN1, CDCA2, PIGR, PTN, RGMA, KLK4 and CENPA, which was used to divide samples into low- and high-risk groups. The low-risk group showed significantly better prognosis than the high-risk group. A correlation analysis revealed that the risk score was an independent prognostic factor. Low- and high- risk groups significantly correlated with the survival ratio in Luminal A samples, but not in Luminal B samples on the basis of the TCGA and the Metabric cohort dataset. Further functional annotation demonstrated that the differentially expressed genes were mainly involved in cell cycle and cancer progression.ConclusionsWe identified several key methylation sites and an mRNA signature for predicting luminal breast cancer prognosis. The signature exhibited effective and precise prediction of prognosis and may serve as a prognostic and diagnostic marker for luminal breast cancer.Electronic supplementary materialThe online version of this article (10.1186/s12885-018-4314-9) contains supplementary material, which is available to authorized users.

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The maladaptive drug memory developed between the drug-rewarding effect and environmental cues contributes to difficulty in preventing drug relapse. Established reward memories can be disrupted by pharmacologic interventions following their reactivation. Rapamycin, an inhibitor of mammalian target of rapamycin (mTOR) kinase, has been proved to be involved in various memory consolidation. However, it is less well characterized in drug memory reconsolidation. Using a conditioned place preference (CPP) procedure, we examined the effects of systemically administered rapamycin on reconsolidation of drug memory in rats. We found that systemically administered rapamycin (0.1 or 10 mg/kg, i.p.) after re-exposure to drug-paired environment, dose dependently decreased the expression of CPP 1 d later, and the effect lasted for up to 14 d and could not be reversed by a priming injection of morphine. The effect of rapamycin on morphine-associated memory was specific to drug-paired context, and rapamycin had no effect on subsequent CPP expression when rats were exposed to saline-paired context or homecage. These results indicated that systemic administration of rapamycin after memory reactivation can persistently inhibit the drug seeking behaviour via disruption of morphine memory reconsolidation in rats. Additionally, the effect of rapamycin on memory reconsolidation was reproduced in cocaine CPP and alcohol CPP. Furthermore, rapamycin did not induce conditioned place aversion and had no effect on locomotor activity and anxiety behaviour. These findings suggest that rapamycin could erase the acquired drug CPP in rats, and that mTOR activity plays an important role in drug reconsolidation and is required for drug relapse.

Circular RNA (circRNA) is a group of RNA families generated by RNA circularization, which was discovered ubiquitously across different cancers. However, the internal structure of circRNA is difficult to determine due to alternative splicing that occurs in its exons and introns. Furthermore, cancer-specific alternative splicing of circRNA is less likely to be identified. Here, we proposed a de novo algorithm, CircSplice, that could identify internal alternative splicing in circRNA and compare differential circRNA splicing events between different conditions ( http://gb.whu.edu.cn/CircSplice or https://github.com/GeneFeng/CircSplice ). By applying CircSplice in clear cell renal cell carcinoma and bladder cancer, we detected 4498 and 2977 circRNA alternative splicing (circ-AS) events in the two datasets respectively and confirmed the expression of circ-AS events by RT-PCR. We further inspected the distributions and patterns of circ-AS in cancer and adjacent normal tissues. To further understand the potential functions of cancer-specific circ-AS, we classified those events into tumor suppressors and oncogenes and performed pathway enrichment analysis. This study is the first comprehensive view of cancer-specific circRNA alternative splicing, which could contribute significantly to regulation and functional research of circRNAs in cancers. Electronic supplementary material The online version of this article (10.1186/s12943-019-0996-0) contains supplementary material, which is available to authorized users.

Increasing evidence has demonstrated that pyroptosis, a type of inflammatory programmed cell death, plays an important role in the pathogenesis and progression of gastric cancer. However, it remains unclear whether pyroptosis-related long non-coding RNAs (lncRNAs) can be used to predict the diagnosis and prognosis of gastric adenocarcinoma. This study aimed to evaluate and test the role of the lncRNA signature associated with pyroptosis as a prognostic tool for stomach adenocarcinoma (STAD) and to ascertain their immune value. Relative RNA-sequencing data were extracted from The Cancer Genome Atlas database (TCGA), and data preprocessing was performed for STAD. Pearson correlation analysis was used to determine whether lncRNAs were significantly correlated with pyroptosis based on 23 genes related to pyroptosis. Univariate Cox regression and least absolute shrinkage and selection operator(LASSO) analyses were both adopted to select features and establish the pyroptosis-related lncRNA (PRL) prognostic signature. Kaplan–Meier(KM) survival analysis of the different risk groups was conducted according to the risk scores. We further examined the functional enrichment, tumor microenvironment, and landscape of mutation status among the different risk groups, and these analyses further explained the reasons for the differences in the prediction as well as survival value of the different risk groups. Four lncRNAs, including HAND2-AS1, LINC01354, RP11-276H19.1, and PGM5-AS1, were involved in the PRL signature and used to split STAD patients into two risk groups. Overall survival time(OS) was significantly higher in the low-risk group than in the high-risk group in both the training and validation groups. Functional enrichment analysis was further employed to analyze differentially expressed genes in high- and low-risk groups to identify potential molecular functions and pathways associated with pyroptosis in the gastric cancer microenvironment. Protein-protein interaction (PPI) and Friends analysis identified hub genes that may play a key role in differentially expressed genes in high- and low-risk groups. In addition, there were remarkable discrepancies between the different risk groups in the tumor stage (P < 0.01) and histologic grade (P < 0.05). Furthermore, drug-susceptibility testing indicated potential sensitive chemotherapeutic drugs for each risk group. This study is the first to establish and validate STAD-associated PRLs that can effectively guide the prognosis and the immune microenvironment in STAD patients and provide evidence for the development of molecularly targeted therapies related to pyroptosis.