Lnc2Cancer v2.0: updated database of experimentally supported long non-coding RNAs in human cancers

Gao, Yue; Wang, Peng; Wang, Yanxia; Ma, Xueyan; Zhi, Hui; Zhou, Dianshuang; Li, Xin; Fang, Ying; Shen, Weitao; Xu, Yingqi; Shang, Shuai; Wang, Lihua; Wang, Li; Ning, Shangwei; Li, Xia

doi:10.1093/nar/gky1096

Cited by 156 publications

(116 citation statements)

References 32 publications

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“…Prioritization of cancer-related lncRNAs. To identify cancer-related lncRNAs, we first obtained the literature-curated cancer lncRNAs from Lnc2Cancer v2.0 59 and LncRNADisease 2.0 60 . Here we focused on the lincRNAs.…”

Section: Methodsmentioning

confidence: 99%

Pan-cancer characterization of immune-related lncRNAs identifies potential oncogenic biomarkers

et al. 2020

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Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and they play fundamental roles in immune regulation. Here we introduce an integrated algorithm, ImmLnc, for identifying lncRNA regulators of immune-related pathways. We comprehensively chart the landscape of lncRNA regulation in the immunome across 33 cancer types and show that cancers with similar tissue origin are likely to share lncRNA immune regulators. Moreover, the immune-related lncRNAs are likely to show expression perturbation in cancer and are significantly correlated with immune cell infiltration. ImmLnc can help prioritize cancer-related lncRNAs and further identify three molecular subtypes (proliferative, intermediate, and immunological) of non-small cell lung cancer. These subtypes are characterized by differences in mutation burden, immune cell infiltration, expression of immunomodulatory genes, response to chemotherapy, and prognosis. In summary, the ImmLnc pipeline and the resulting data serve as a valuable resource for understanding lncRNA function and to advance identification of immunotherapy targets.

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Section: Methodsmentioning

confidence: 99%

Pan-cancer characterization of immune-related lncRNAs identifies potential oncogenic biomarkers

et al. 2020

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“…The same mechanism was subsequently uncovered for HOTAIR [58]. HOTAIR is transcribed from the antisense strand of the HOXC gene cluster and is one of the most studied oncogenic lncRNAs [13,30]. One of many mechanisms of action of HOTAIR is genome-wide transcriptional regulation, for example by recruitment of polycomb repressive complex 2 (PRC2) proteins [13].…”

Section: Human Antigen R (Hur)mentioning

confidence: 80%

“…Apart from NEAT1, Yoon et al also confirmed MALAT1 as an interaction partner of AUF1 [61]. MALAT1, as mentioned in the introduction, is yet another lncRNA that has been studied intensely in recent years due to its involvement in cancer, for example by regulating alternative splicing [20,30]. AUF1 did not, despite interacting with it, affect the stability of MALAT1 [61].…”

Section: Are/poly(u)-binding/degradation Factor 1 (Auf1)mentioning

confidence: 89%

“…Their implications in cancer are of particular interest, as many lncRNAs have been found to be deregulated in cancer [29]. According to lnc2Cancer, a database for human lncRNAs with experimentally supported cancer associations, 1614 different lncRNAs were found to be implicated in a total number of 165 cancer subtypes [30], influencing different aspects of cancer biology like proliferation [31][32][33][34][35], apoptosis [34][35][36], invasion [32,[35][36][37], metastasis [38][39][40][41], angiogenesis [41][42][43], drug resistance [35,44], and genome stability [45]. According to lnc2Cancer, the most studied cancer-associated lncRNAs are MALAT1 [46], H19 [47], HOX antisense intergenic RNA (HOTAIR) [48], maternally expressed 3 (MEG3) [49], taurine upregulated 1 (TUG1) [50], antisense non-coding RNA in the INK4 locus (ANRIL) [51] and nuclear-enriched abundant transcript 1 (NEAT1) [52].While lncRNAs are distinguished from protein-coding mRNAs in several aspects, they also share certain similarities [6,7].…”

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confidence: 99%

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RNA-Binding Proteins as Important Regulators of Long Non-Coding RNAs in Cancer

Jonas

Calin

Pichler

2020

IJMS

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The majority of the genome is transcribed into pieces of non-(protein) coding RNA, among which long non-coding RNAs (lncRNAs) constitute a large group of particularly versatile molecules that govern basic cellular processes including transcription, splicing, RNA stability, and translation. The frequent deregulation of numerous lncRNAs in cancer is known to contribute to virtually all hallmarks of cancer. An important regulatory mechanism of lncRNAs is the post-transcriptional regulation mediated by RNA-binding proteins (RBPs). So far, however, only a small number of known cancer-associated lncRNAs have been found to be regulated by the interaction with RBPs like human antigen R (HuR), ARE/poly(U)-binding/degradation factor 1 (AUF1), insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), and tristetraprolin (TTP). These RBPs regulate, by various means, two aspects in particular, namely the stability and the localization of lncRNAs. Importantly, these RBPs themselves are commonly deregulated in cancer and might thus play a major role in the deregulation of cancer-related lncRNAs. There are, however, still many open questions, for example regarding the context specificity of these regulatory mechanisms that, in part, is based on the synergistic or competitive interaction between different RBPs. There is also a lack of knowledge on how RBPs facilitate the transport of lncRNAs between different cellular compartments. Compared to protein-coding genes, lncRNAs are poorly conserved between different species and their expression levels are rather low [7,8]. Initially, this led to the belief that they were nothing but transcriptional noise [6][7][8]. Soon, however, it was discovered that lncRNAs do exhibit considerable functionality, for example as regulators of transcription [6][7][8]. Mechanisms of transcriptional regulation by lncRNAs are multifarious and can occur either in cis or in trans, meaning either closer to or further away from the lncRNA's site of transcription, respectively [6,7]. A frequent mechanism of transcriptional regulation via lncRNAs is the recruitment, or prevention of such, of components of chromatin or histone-modifying complexes, like polycomb repressive complexes or histone deacetylase complexes [11][12][13]. LncRNAs can also direct transcription factors or cofactors to promoter regions of genes and facilitate the formation of chromatin loops between distant enhancers and promoters, as observed for some eRNAs [9,[14][15][16][17]. Another way that they can impact transcription is by interfering with the RNA polymerase II transcription machinery, thereby blocking transcriptional initiation or elongation [18]. LncRNAs are important regulators not only at the level of transcription but also at the post-transcriptional level [6,7]. They regulate pre-mRNA splicing by interacting with splicing factors or with the mRNA itself [19][20][21][22]. A well-studied example for this is metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), an lncRNA that interacts with serine/arginine (SR) spl...

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“…The BRCA related mRNAs are from DisGeNET v5.0 [36] and COSMIC v86 [37], and the BRCA related lncRNAs are from LncRNADisease v2.0 [38], Lnc2Cancer v2.0 [39] and MNDR v2.0 [40]. The ground truth of lncRNA related miRNA sponge interactions is obtained by integrating the interactions from miRSponge [41], LncCeRBase [42] and LncACTdb v2.0 [43].…”

Section: Heterogeneous Data Sourcesmentioning

confidence: 99%

LMSM: a modular approach for identifying lncRNA related miRNA sponge modules in breast cancer

Zhang

Liu

et al. 2019

Preprint

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AbstractUntil now, existing methods for identifying lncRNA related miRNA sponge modules mainly rely on lncRNA related miRNA sponge interaction networks, which may not provide a full picture of miRNA sponging activities in biological conditions. Hence there is a strong need of new computational methods to identify lncRNA related miRNA sponge modules. In this work, we propose a framework, LMSM, to identify LncRNA related MiRNA Sponge Modules from heterogeneous data. To understand the miRNA sponging activities in biological conditions, LMSM uses gene expression data to evaluate the influence of the shared miRNAs on the clustered sponge lncRNAs and mRNAs. We have applied LMSM to the human breast cancer (BRCA) dataset from The Cancer Genome Atlas (TCGA). As a result, we have found that the majority of LMSM modules are significantly implicated in BRCA and most of them are BRCA subtype-specific. Most of the mediating miRNAs act as crosslinks across different LMSM modules, and all of LMSM modules are statistically significant. Multi-label classification analysis shows that the performance of LMSM modules is significantly higher than baseline’s performance, indicating the biological meanings of LMSM modules in classifying BRCA subtypes. The consistent results suggest that LMSM is robust in identifying lncRNA related miRNA sponge modules. Moreover, LMSM can be used to predict miRNA targets. Finally, LMSM outperforms a graph clustering-based strategy in identifying BRCA-related modules. Altogether, our study shows that LMSM is a promising method to investigate modular regulatory mechanism of sponge lncRNAs from heterogeneous data.Author summaryPrevious studies have revealed that long non-coding RNAs (lncRNAs), as microRNA (miRNA) sponges or competing endogenous RNAs (ceRNAs), can regulate the expression levels of messenger RNAs (mRNAs) by decreasing the amount of miRNAs interacting with mRNAs. In this work, we hypothesize that the “tug-of-war” between RNA transcripts for attracting miRNAs is across groups or modules. Based on the hypothesis, we propose a framework called LMSM, to identify LncRNA related MiRNA Sponge Modules. Based on the two miRNA sponge modular competition principles, significant sharing of miRNAs and high canonical correlation between the sponge lncRNAs and mRNAs, LMSM is also capable of predicting miRNA targets. LMSM not only extends the ceRNA hypothesis, but also provides a novel way to investigate the biological functions and modular mechanism of lncRNAs in breast cancer.

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Lnc2Cancer v2.0: updated database of experimentally supported long non-coding RNAs in human cancers

Cited by 156 publications

References 32 publications

Pan-cancer characterization of immune-related lncRNAs identifies potential oncogenic biomarkers

Pan-cancer characterization of immune-related lncRNAs identifies potential oncogenic biomarkers

RNA-Binding Proteins as Important Regulators of Long Non-Coding RNAs in Cancer

LMSM: a modular approach for identifying lncRNA related miRNA sponge modules in breast cancer

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