microCLIP super learning framework uncovers functional transcriptome-wide miRNA interactions

Paraskevopoulou, Maria D.; Karagkouni, Dimitra; Vlachos, Ioannis S.; Tastsoglou, Spyros; Hatzigeorgiou, Artemis G.

doi:10.1038/s41467-018-06046-y

Cited by 34 publications

(21 citation statements)

References 54 publications

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“…On a different approach, several publicly available repositories exist that link genomic, transcriptomic and proteomic data of coding genes and non-coding RNAs targeting these genes, thus assisting researchers in identifying the most biologically relevant lncRNAs and miRNAs in a disease-specific context. In fact, databases such as LncR-NADisease [154], lncRNASNP [155], miRTarbase [156] and StarBase [157] contain thousands of experimentally validated and continuously updated lncRNA-or miRNAtarget interactions including data generated by cutting-edge techniques such as crosslinking immunoprecipitation [158,159]. In addition, the matching of these data with those coming from prediction platform such as TargetScan [160] has the potential to further improve the accuracy of the search for relevant non-coding RNAs.…”

Section: Identification Of Deregulated Non-coding Rnasmentioning

confidence: 99%

MicroRNAs (miRNAs) and Long Non-Coding RNAs (lncRNAs) as New Tools for Cancer Therapy: First Steps from Bench to Bedside

et al. 2020

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Non-coding RNAs represent a significant proportion of the human genome. After having been considered as 'junk' for a long time, non-coding RNAs are now well established as playing important roles in maintaining cellular homeostasis and functions. Some non-coding RNAs show cell-and tissue-specific expression patterns and are specifically deregulated under pathological conditions (e.g. cancer). Therefore, non-coding RNAs have been extensively studied as potential biomarkers in the context of different diseases with a focus on microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) for several years. Since their discovery, miRNAs have attracted more attention than lncRNAs in research studies; however, both families of non-coding RNAs have been established to play an important role in gene expression control, either as transcriptional or post-transcriptional regulators. Both miRNAs and lncRNAs can regulate key genes involved in the development of cancer, thus influencing tumour growth, invasion, and metastasis by increasing the activation of oncogenic pathways and limiting the expression of tumour suppressors. Furthermore, miRNAs and lncRNAs are also emerging as important mediators in drug-sensitivity and drug-resistance mechanisms. In the light of these premises, a number of pre-clinical and early clinical studies are exploring the potential of non-coding RNAs as new therapeutics. The aim of this review is to summarise the latest knowledge of the use of miRNAs and lncRNAs as therapeutic tools for cancer treatment.

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Section: Identification Of Deregulated Non-coding Rnasmentioning

confidence: 99%

MicroRNAs (miRNAs) and Long Non-Coding RNAs (lncRNAs) as New Tools for Cancer Therapy: First Steps from Bench to Bedside

et al. 2020

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“…Subsequently, these approaches have revealed that miRNAs can modulate the expression of target mRNAs by following non-predicted and non-canonical interaction patterns, for instance by binding via nucleotides beyond the seed sequence [ 17 , 18 , 20 ]. Thus, miRNAs do not only have the potential to bind regions on the mRNA other than the 3′UTR, but they can also interact with other RNA species, such as long non-coding RNAs (lncRNA) [ 21 , 22 , 23 ] ( Figure 1 B). MiRNAs are involved in the fine-tuning of most biological processes and have consequently been assigned functional roles in the emergence and progression of cancer cells.…”

Section: Introductionmentioning

confidence: 99%

Cross-Linking Ligation and Sequencing of Hybrids (qCLASH) Reveals an Unpredicted miRNA Targetome in Melanoma Cells

Kozar

Philippidou

Margue

et al. 2021

Cancers

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MicroRNAs are key post-transcriptional gene regulators often displaying aberrant expression patterns in cancer. As microRNAs are promising disease-associated biomarkers and modulators of responsiveness to anti-cancer therapies, a solid understanding of their targetome is crucial. Despite enormous research efforts, the success rates of available tools to reliably predict microRNAs (miRNA)-target interactions remains limited. To investigate the disease-associated miRNA targetome, we have applied modified cross-linking ligation and sequencing of hybrids (qCLASH) to BRAF-mutant melanoma cells. The resulting RNA-RNA hybrid molecules provide a comprehensive and unbiased snapshot of direct miRNA-target interactions. The regulatory effects on selected miRNA target genes in predicted vs. non-predicted binding regions was validated by miRNA mimic experiments. Most miRNA–target interactions deviate from the central dogma of miRNA targeting up to 60% interactions occur via non-canonical seed pairing with a strong contribution of the 3′ miRNA sequence, and over 50% display a clear bias towards the coding sequence of mRNAs. miRNAs targeting the coding sequence can directly reduce gene expression (miR-34a/CD68), while the majority of non-canonical miRNA interactions appear to have roles beyond target gene suppression (miR-100/AXL). Additionally, non-mRNA targets of miRNAs (lncRNAs) whose interactions mainly occur via non-canonical binding were identified in melanoma. This first application of CLASH sequencing to cancer cells identified over 8 K distinct miRNA–target interactions in melanoma cells. Our data highlight the importance non-canonical interactions, revealing further layers of complexity of post-transcriptional gene regulation in melanoma, thus expanding the pool of miRNA–target interactions, which have so far been omitted in the cancer field.

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“…The experimentally supported interactions of the FER1L4-miRNA were checked in DIANA-LncBase v3 database [ 44 , 45 ]. Discovered miRNAs where then uploaded to DIANA-mirPath [ 46 ] to find targeted genes with the DIANA-microT-CDS algorithm [ 47 ] and KEGG pathway enrichment analysis.…”

Section: Methodsmentioning

confidence: 99%

Dysregulation of Transcription Factor Activity during Formation of Cancer-Associated Fibroblasts

Kapusta

Dulińska-Litewka

Totoń‐Żurańska

et al. 2020

IJMS

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The reciprocal interactions between cancer cells and the quiescent fibroblasts leading to the activation of cancer-associated fibroblasts (CAFs) serve an important role in cancer progression. Here, we investigated the activation of transcription factors (TFs) in prostate fibroblasts (WPMY cell line) co-cultured with normal prostate or tumorous cells (RWPE1 and RWPE2 cell lines, respectively). After indirect co-cultures, we performed mRNA-seq and predicted TF activity using mRNA expression profiles with the Systems EPigenomics Inference of Regulatory Activity (SEPIRA) package and the GTEx and mRNA-seq data of 483 cultured fibroblasts. The initial differential expression analysis between time points and experimental conditions showed that co-culture with normal epithelial cells mainly promotes an inflammatory response in fibroblasts, whereas with the cancerous epithelial, it stimulates transformation by changing the expression of the genes associated with microfilaments. TF activity analysis revealed only one positively regulated TF in the RWPE1 co-culture alone, while we observed dysregulation of 45 TFs (7 decreased activity and 38 increased activity) uniquely in co-culture with RWPE2. Pathway analysis showed that these 45 dysregulated TFs in fibroblasts co-cultured with RWPE2 cells may be associated with the RUNX1 and PTEN pathways. Moreover, we showed that observed dysregulation could be associated with FER1L4 expression. We conclude that phenotypic changes in fibroblast responses to co-culturing with cancer epithelium result from orchestrated dysregulation of signaling pathways that favor their transformation and motility rather than proinflammatory status. This dysregulation can be observed both at the TF and transcriptome levels.

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microCLIP super learning framework uncovers functional transcriptome-wide miRNA interactions

Cited by 34 publications

References 54 publications

MicroRNAs (miRNAs) and Long Non-Coding RNAs (lncRNAs) as New Tools for Cancer Therapy: First Steps from Bench to Bedside

MicroRNAs (miRNAs) and Long Non-Coding RNAs (lncRNAs) as New Tools for Cancer Therapy: First Steps from Bench to Bedside

Cross-Linking Ligation and Sequencing of Hybrids (qCLASH) Reveals an Unpredicted miRNA Targetome in Melanoma Cells

Dysregulation of Transcription Factor Activity during Formation of Cancer-Associated Fibroblasts

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