LncRNA2Target v2.0: a comprehensive database for target genes of lncRNAs in human and mouse

Liang, Cheng; Wang, Pingping; Tian, Rui; Wang, Song; Guo, Qinghua; Luo, Meng; Zhou, Wenyang; Liu, Guiyou; Jiang, Huijie; Jiang, Qinghua

doi:10.1093/nar/gky1051

Cited by 284 publications

(145 citation statements)

References 37 publications

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“…Long non-coding RNAs were filtered from the whole RNA-Seq data, basing on sequence length (reads > 200 nt) and on minimum sampling normalized count (set at TPM ≥ 1). The extracted lncRNA pool was, then, enriched by comparing the tag sequences with the annotation resources UCSC non-coding [30], Ensembl non-coding RNA database v.99 [31], GENCODE v.33 [32], LNCipedia v.5.2 [33], RNAinter [34], RNALocate [35], MNDR v.2.0 [36], ncRDeathDB v.2.0 [37], Malacards and Genecards [38], HUGO Gene Nomenclature Committee (HGNC) expert database [39], lncBase [40], lncRNADisease v.2.0 [41] and lncRNA2Target v.2.0 [42]. All databases provided resources both from experimental and predicted experiments regarding lncRNAs and their targets.…”

Section: Filtering and Annotation Of Non-coding Rnasmentioning

confidence: 99%

Transcriptome Analyses of lncRNAs in A2E-Stressed Retinal Epithelial Cells Unveil Advanced Links between Metabolic Impairments Related to Oxidative Stress and Retinitis Pigmentosa

et al. 2020

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Long non-coding RNAs (lncRNAs) are untranslated transcripts which regulate many biological processes. Changes in lncRNA expression pattern are well-known related to various human disorders, such as ocular diseases. Among them, retinitis pigmentosa, one of the most heterogeneous inherited disorder, is strictly related to oxidative stress. However, little is known about regulative aspects able to link oxidative stress to etiopathogenesis of retinitis. Thus, we realized a total RNA-Seq experiment, analyzing human retinal pigment epithelium cells treated by the oxidant agent N-retinylidene-N-retinylethanolamine (A2E), considering three independent experimental groups (untreated control cells, cells treated for 3 h and cells treated for 6 h). Differentially expressed lncRNAs were filtered out, explored with specific tools and databases, and finally subjected to pathway analysis. We detected 3,3'-overlapping ncRNAs, 107 antisense, 24 sense-intronic, four sense-overlapping and 227 lincRNAs very differentially expressed throughout all considered time points. Analyzed lncRNAs could be involved in several biochemical pathways related to compromised response to oxidative stress, carbohydrate and lipid metabolism impairment, melanin biosynthetic process alteration, deficiency in cellular response to amino acid starvation, unbalanced regulation of cofactor metabolic process, all leading to retinal cell death. The explored lncRNAs could play a relevant role in retinitis pigmentosa etiopathogenesis, and seem to be the ideal candidate for novel molecular markers and therapeutic strategies.

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Section: Filtering and Annotation Of Non-coding Rnasmentioning

confidence: 99%

Transcriptome Analyses of lncRNAs in A2E-Stressed Retinal Epithelial Cells Unveil Advanced Links between Metabolic Impairments Related to Oxidative Stress and Retinitis Pigmentosa

et al. 2020

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“…Two databases have mainly experimental purposes; namely, LncRNA2Target [173] and CRISPRlnc [174]. The former collects lncRNA knockdown or overexpression experiments in human and mouse to check target genes by immunoprecipitation, RNA pull-down, immunofluorescence, microarray hybridization or RNA-seq techniques.…”

Section: Bioinformatics Resources For Lncrna Researchmentioning

confidence: 99%

The Challenges and Opportunities of LncRNAs in Ovarian Cancer Research and Clinical Use

Salamini-Montemurri

Lamas-Maceiras

Barreiro-Alonso

et al. 2020

Cancers

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Ovarian cancer is one of the most lethal gynecological malignancies worldwide because it tends to be detected late, when the disease has already spread, and prognosis is poor. In this review we aim to highlight the importance of long non-coding RNAs (lncRNAs) in diagnosis, prognosis and treatment choice, to make progress towards increasingly personalized medicine in this malignancy. We review the effects of lncRNAs associated with ovarian cancer in the context of cancer hallmarks. We also discuss the molecular mechanisms by which lncRNAs become involved in cellular physiology; the onset, development and progression of ovarian cancer; and lncRNAs' regulatory mechanisms at the transcriptional, post-transcriptional and post-translational stages of gene expression. Finally, we compile a series of online resources useful for the study of lncRNAs, especially in the context of ovarian cancer. Future work required in the field is also discussed along with some concluding remarks.

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“…To reduce the error, several databases including Cell marker [16], LncRNA2Target [17], Metascape [18], Ontogene [19], String [20], Oncomine [21], Cancer Cell Line Encyclopedia (CCLE), cBioPortal for Cancer Genomics [22], genotype-tissue Expression (GTEx) [23], Gene Expression Profiling Interactive Analysis (GEPIA) [24], LinkedOmics [25], SurvExpress [26] and The Human Protein Atlas (Proteomics. Tissue-based map of the human proteome) detected the gene and protein expression levels of key biomarkers at the tissue and cell levels.…”

Section: Multidimensional Validationmentioning

confidence: 99%

The construction and analysis of tumor-infiltrating immune cells and ceRNA networks in metastatic adrenal cortical carcinoma

et al. 2020

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Purpose: To construct and analyze tumor-infiltrating immune cell and ceRNA (competitive endogenous RNA) networks in metastatic adrenal cortical carcinoma (ACC). Methods: A ceRNA network was established to identify the ceRNAs involved in metastasis of ACC based on 92 samples from TCGA, including 18 cases of metastasis and 74 cases of non-metastatic primary tumors. And the algorithm "cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT)" was used to quantify the proportion of immune cells in ACC. In addition, predictive nomograms based on the types of important immune cells or ceRNAs were constructed to predict ACC prognosis. Moreover, we evaluated the relationships between metastatic ACC-specific immune cells and ceRNA networks to identify the potential immune gene characteristics. Results: Ten prognostic biomarkers were identified as key members of the ceRNA network and three tumor-infiltrating immune cells were identified by CIBERSORT algorithm. Some important co-expression patterns between immune cells and ceRNAs network indicate significant correlation between Macrophages M0 and hsa-miR-130b-3p (P < 0.001), Macrophages M0 and H2AFX (P = 0.003). Conclusions:The present study inferred that the metastasis-related ceRNAs of H2AFX, hsa-miR-130b-3p and Macrophages M0 might play important roles in ACC metastasis.

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LncRNA2Target v2.0: a comprehensive database for target genes of lncRNAs in human and mouse

Cited by 284 publications

References 37 publications

Transcriptome Analyses of lncRNAs in A2E-Stressed Retinal Epithelial Cells Unveil Advanced Links between Metabolic Impairments Related to Oxidative Stress and Retinitis Pigmentosa

Transcriptome Analyses of lncRNAs in A2E-Stressed Retinal Epithelial Cells Unveil Advanced Links between Metabolic Impairments Related to Oxidative Stress and Retinitis Pigmentosa

The Challenges and Opportunities of LncRNAs in Ovarian Cancer Research and Clinical Use

The construction and analysis of tumor-infiltrating immune cells and ceRNA networks in metastatic adrenal cortical carcinoma

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