miRcode: a map of putative microRNA target sites in the long non-coding transcriptome

Jeggari, Ashwini; Marks, Debora S.; Larsson, Erik

doi:10.1093/bioinformatics/bts344

Cited by 658 publications

(543 citation statements)

References 27 publications

(32 reference statements)

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“…To further explore the regulatory mechanism of the lncRNA expression pattern, miRcode [32] software was used to predict the potential complementary base pairing between LNMICC and miRNAs. We transfected MS751 cells with mimics of all predicted miRNAs, and miR190 had the most significant effect on LNMICC expression (Fig.…”

Section: Lnmicc Is a Direct Target Of Mir190mentioning

confidence: 99%

LNMICC Promotes Nodal Metastasis of Cervical Cancer by Reprogramming Fatty Acid Metabolism

et al. 2018

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Running Title: LNMICC promotes lymph node metastasis in cervical cancer.Key words: lymph node metastasis; fatty acid metabolism; long non-coding RNA; cervical cancer. Conflict of Interest:The authors declare no potential conflicts of interest.Research. AbstractCancer spread to lymph nodes (LN) predicts poor survival but underlying mechanisms remain little understood. In this study, we show that overexpression of the long non-coding RNA LNMICC associates with LN metastasis of primary cervical cancer, where it serves as an independent high-risk factor in patient survival. Functional investigations demonstrated that LNMICC promoted LN metastasis by reprogramming fatty acid metabolism, by recruiting the nuclear factor NPM1 to the promoter of the fatty acid binding protein FABP5. We also found that the pro-metastatic effects of LNMICC were directly targeted and suppressed by miR-190. Our results establish a new mechanism of LN metastasis and highlight LNMICC as a candidate prognostic biomarker and therapeutic target in cervical cancer.

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Section: Lnmicc Is a Direct Target Of Mir190mentioning

confidence: 99%

LNMICC Promotes Nodal Metastasis of Cervical Cancer by Reprogramming Fatty Acid Metabolism

et al. 2018

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“…In the next step, we focused on whether these intersection miRNAs would target the above 25 GC specific lncRNAs. In the ceRNAs network, 17 miRNAs targeted 19 key lncRNAs were predicted though miRcode (http://www.mircode.org/) (25) (Table II).…”

Section: Go and Pathway Analysis Of Differentially Expressed Genesmentioning

confidence: 99%

Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric cancer

Liang

Yao

et al. 2016

International Journal of Oncology

111

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Abstract. Abnormal expression of long non-coding RNAs (lncRNAs) have been shown to play an important role in tumor biology. The Cancer Genome Atlas (TCGA) platform is a large sample sequencing database of lncRNAs, and further analysis of the associations between these data and patients' clinical related information can provide new approaches to find the functions of lncRNA. In the present study, 361 RNA sequencing profiles of gastric cancer (GC) patients were selected from TCGA. Then, we constructed the lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network of GC. There were 25 GC specific lncRNAs (fold change >2, p<0.05) identified, 19 of them were included in ceRNA network. Subsequently, we selected these 19 key lncRNAs and analyzed the correlations with clinical features and overall survival, 14 of them were discriminatively expressed with tumor size, tumor grade, TNM stage and lymphatic metastasis (p<0.05). In addition, eight lncRNAs (RPLP0P2, FOXD2-AS1, H19, TINCR, SLC26A4-AS1, SMIM10L2A, SMIM10L2B and SNORD116-4) were found to be significantly associated with overall survival (log-rank p<0.05). Finally, two key lncRNAs HOTAIR and UCA1 were selected for validation of their expression levels in 82 newly diagnosed GC patients by qRT-PCR. Results showed that the fold changes between TCGA and qRT-PCR were 100% in agreement. In addition, we also found that HOTAIR was significantly correlated with tumor size and lymphatic metastasis (p<0.05), and UCA1 was significantly correlated with tumor size, TNM stage and lymphatic metastasis (p<0.05).The clinical relevance of the two lncRNAs and the bioinformatics analysis results were almost the same. Overall, our study showed the GC specific lncRNAs expression patterns and a ceRNA network in GC. Clinical features related to GC specific lncRNAs also suggested these lncRNAs are worthwhile for further study as novel candidate biomarkers for the clinical diagnosis of GC and potential indicators for prognosis. IntroductionNoncoding RNAs (ncRNAs) are transcripts that have no ability of coding proteins, which widely exit in high eukaryotics. According to their characteristics, ncRNAs can be divided into several subtypes including transfer RNA, small nucleolar RNA (snoRNA), ribosomal RNA (rRNA), microRNA (miRNA) and long non-coding RNA (lncRNA). The amount of the ncRNAs transcripts is >98% of the whole genome transcripts and have been suggested to represent transcriptional noise (1). However, more and more evidence indicates that transcriptional output of genome is far more complex than predicted, and suggests new paradigms of ncRNA regulation (2).Recent studies suggest that the ncRNAs may play important biological roles in transcriptional regulation, cellular development, formation of chromosome and RNA modification (3). Based on the transcript size, ncRNAs are grouped into small ncRNAs (<200 bp) and long ncRNAs (>200 bp, up to 100 kb). lncRNA is the functional end-product, and the level of lncRNA expression correlates directly with the level of the active molecule. Thus, ...

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“…AnnoLnc is an online tool which provides lncRNAs annotations includ ing their interactions with miRNA and proteins [26]. The miRcode has provided a map of possible miRNA target sites across the complete GENCODE annotated transcriptome, includ ing more than 10 000 lncRNA genes so facilitates the identification of miRNA-lncRNA interactions [27]. Schema 1 shows the pipeline used for identification of VDR related lncRNAs in BC.…”

Section: In Silico Functional Analysis Of Lncrnasmentioning

confidence: 99%

A Combined Bioinformatics and Literature Based Approach for Identification of Long Non-coding RNAs That Modulate Vitamin D Receptor Signaling in Breast Cancer

Oskooei¹,

Ghafouri‐Fard²,

Mir³

2018

Klin Onkol

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Kombinovaný bio informatický a literární přístup k identifikaci dlouhých nekódujících molekul RNA, které modulují signalizaci přes receptor vitaminu D u karcinomu prsu Kholghi Oskooei V., Ghafouri-Fard S., Omrani MD Department of Medical Genetics, Shahid Beheshti University of Medical Sciences, Tehran, Iran SummaryBackground: Long non-cod ing RNAs (lncRNAs) as an important fraction of human transcriptome have been shown to exert fundamental role in regulation of signal ing pathways implicated in carcinogenesis. Among them is vitamin D receptor (VDR) signal ing whose participation in various cancers includ ing breast cancer (BC) is evident. In spite of the presence of several evidences for participation of lncRNAs as well as VDR signal ing in BC pathogenesis, no comprehensive study has evaluated the link between lncRNA dysregulation and VDR signal ing in BC. Aim: To introduce a bio informatics approach for identification of lncRNAs that modulate VDR signal ing in BC. This approach includes co-expression analysis, in silico identification of lncRNAs that target VDR and literature search. Conclusions: Tens of lncRNAs are predicted to affect VDR signaling. Among them are some lncRNAs such as MALAT1 which has prominent role in BC pathogenesis. Identification of the lncRNAs that influence VDR gene expression is possible through in silico analysis. Consider ing the prominent role of VDR in BC pathogenesis as well as availability of VDR modulat ing agents, evaluation of VDR signal ing pathway and related networks are of practical significance and bio informatics tools are expected to facilitate such action.

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miRcode: a map of putative microRNA target sites in the long non-coding transcriptome

Cited by 658 publications

References 27 publications

LNMICC Promotes Nodal Metastasis of Cervical Cancer by Reprogramming Fatty Acid Metabolism

LNMICC Promotes Nodal Metastasis of Cervical Cancer by Reprogramming Fatty Acid Metabolism

Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric cancer

A Combined Bioinformatics and Literature Based Approach for Identification of Long Non-coding RNAs That Modulate Vitamin D Receptor Signaling in Breast Cancer

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