Crosstalk between Noncoding RNAs and the Epigenetics Machinery in Pediatric Tumors and Their Microenvironment
Abstract
:Simple Summary
Abstract
1. Introduction
2. Role of ncRNAS in the Epigenetic Regulation of Pediatric Tumors
2.1. Histone Modifications
2.1.1. miRNAs
2.1.2. LncRNAs
2.2. DNA Methylation
2.2.1. miRNAs
2.2.2. LncRNAs
3. Role of ncRNAS in the Epigenetic Regulation of the TME
3.1. miRNAs
3.2. LncRNAs
3.3. PiRNAs and snRNAs
LncRNAs | Cancer Type | Target Epigenetic Regulator | Mechanism of Action | Role as Potential Biomarker |
---|---|---|---|---|
HOX antisense intergenic RNA (HOTAIR) [178] | Cutaneous squamous cell carcinoma (CSCC) | Transcription factor Sp1 | HOTAIR interacts and upregulates Sp1, promoting Sp1-induced DNMT1-mediated promoter methylation and repression of miR-199a. Downregulation of miR-199a promotes CSCC cell stemness and tumor progression. | Upregulated in CSCC tissues compared to normal adjacent cells and associated with worse patient prognosis. |
LncRNA IRAIN [179,180] | RCC | Dnmt1, Dnmt3a, and Dnmt3b | IRAIN recruits Dnmt1, Dnmt3a, and Dnmt3b to the VEGFA promoter, inhibiting its expression. VEGFA downregulation inhibits ECs recruitment, tumor angiogenesis, and growth. | IRAIN has lower expression in RC tissues than in healthy renal tissues. |
LINC00152 [181] | Gastric cancer | EZH2 | LINC00152 recruits EZH2 to CXCL9 and CXCL10 promoters and epigenetically silences them. LINC00152 inhibition upregulates CXCL9, CXCL10, and CXCR3, which promotes intratumoral cytotoxic CD8+ T-cell infiltration. | LINC00152 is highly expressed in gastric cancer patients than normal counterparts. |
Nuclear paraspeckle assembly transcript 1 (NEAT1) [182,183] | Glioblastoma | RNA-binding protein SFPQ | NEAT1 promotes paraspeckle assembly and relocates transcriptional repressor SFPQ from the CXCL8 promoter to paraspeckles, upregulating its protein product IL8 expression. IL8 secretion from tumor cells facilitates TAM recruitment and immunosuppression. | GBM tissues have higher expression of NEAT1 than low-grade glioma and normal brain tissues. |
Colorectal neoplasia differentially expressed (CRNDE) [184,185] | HCC | p300/YY1 complex | CRNDE stabilizes the p300/YY1 complex and enhances histone H3K9 and H3K27 acetylation at the EGFR promoter, upregulating its expression. Exosomal EGFR is known to modulate the liver microenvironment to facilitate liver metastases. | CRNDE is highly expressed in human HCC compared to normal liver cells. |
MIAT [186,187,188] | Thyroid cancer | EZH2 | MIAT sponges miR-150 activity and upregulates its target EZH2, promoting tumor cell proliferation, migration, and invasion. MIAT upregulation is associated with immune suppression in cancer. | MIAT is overexpressed in thyroid cancer patients |
HOTAIR [189] | AML | EZH2 | HOTAIR recruits EZH2 to the p15 promoter, inducing its H3K27me3 and silencing gene expression. p15 downregulation is associated with the enhanced self-renewal capacity of leukemia stem cells, promoting leukemogenesis. | HOTAIR expression is significantly upregulated in AML patients. |
NcRNA Types | Cancer Type | Target Epigenetic Regulator | Mechanism of Action |
---|---|---|---|
piRNA-823 [190] | Multiple myeloma | DNMT3A and 3B | piRNA-823 overexpression upregulates DNMT3A and DNMT3B levels and increases global DNA methylation. PiRNA-823 silencing reexpress methylation-silenced tumor suppressor, p16INK4A, decreases tumor angiogenesis, and inhibits tumor growth. |
piR_011186 [191] | AML | DNMT1, Suv39H1 and/or EZH2 | piR_011186 promotes DNA and histone H3 methylation of the CDKN2B promoter, which downregulates its expression and is associated with enhanced cell proliferation. |
PIWI-like 4 (piRNA associated protein) [192] | Glioma | H3K27me3 demethylase UTX | PIWIL4 interacts with UTX, which removes transcriptionally repressive H3K27me3 marks on neuronal genes, promoting neuronal differentiation and activity. The upregulation of neuronal genes due to PIWIL4–UTX interaction can further modify the glioma microenvironment and promote glioma cell proliferation. |
piRNA-823 [193] | Multiple myeloma | DNMT3B | G-MDSCs induce piRNA-823 expression in multiple myeloma cells, which in turn activates DNMT3B expression and increases global DNA methylation. These changes are associated with enhanced stemness of multiple myeloma stem cells and tumor growth. |
piRNA-30473 [194] | DLBCL | m6A mRNA methylase WTAP | piRNA-30473 stabilizes WTAP mRNA, upregulating global m6A levels in DLBCL cells. This increases hexokinase 2 (HK2) expression, which is associated with increased cell proliferation and tumorigenicity of DLBCL cells. |
sdnRNA-3 [176] | Melanoma | Chromatin-remodeling regulator Mi-2β | sdnRNA-3 promotes the enrichment of chromodomain-helicase-DNA-binding protein 4 (CHD4), also known as Mi-2β, to the Nos2 promoter. This induces H3K27me3 modification of the Nos2 gene and represses the transcription of its gene product, inducible nitric oxide synthase (iNOS). The decrease in sdnRNA-3 expression in TAMs increases iNOS transcription and inhibits tumor growth. |
RN7SK [177] | Multiple cancers including lung, liver, colon, and gastric | m6A readers | M6A readers recognize and interact with m6A-modified RN7SK, which facilitates the formation of RN7SK secondary structures and stabilizes its expression. RN7SK prevents the mRNA degradation of m6A readers by exonucleases, increasing their expression. The upregulation of m6A readers such as EWSR1 and KHDRBS1 promotes Wnt/β-catenin signaling and tumorigenesis by suppressing ubiquitin protein Cullin1 in various tumor types. |
U1 snRNP [195] | Lung and breast cancer | Proximal polyadenylation signals (PASs) in introns and exons | U1 snRNP inhibits proximal polyadenylation signals (PASs) in introns and last exons, preventing premature transcription termination and mRNA shortening of target genes. U1 snRNP inhibition in cancer cells prompts the removal of 3ʹUTR miRNA target sites from many oncogenic mRNAs, resulting in their upregulation. The upregulated genes are involved in signaling pathways that control cell-cycle progression (CDC25A, CCNB1, and BRCA1), apoptosis (BCL6), cell growth (FGFR1, EGFR, and BRAF), cell migration (FGFR1, FYN, and TIMP2), extracellular matrix remodeling (TIMP2), DNA replication (APC), and transcription (EWSR1). |
Database Name | Used for | Link |
---|---|---|
miRBase [196] | This database contains information about miRNAs including sequences, annotations, and expression data. It also provides tools for predicting miRNA targets. | https://www.mirbase.org (accessed on 26 April 2023) |
TargetScan [197] | This provides computational predictions of miRNA targets based on the matching of miRNA seed sequence with complementary mRNA sequences. | www.targetscan.org (accessed on 26 April 2023) |
miRTarBase [198] | This database provides information about experimentally validated miRNA–target mRNA interactions. | www.mirtarbase.cuhk.edu.cn/ (accessed on 26 April 2023) |
miRWalk [199] | miRWalk provides predictions of miRNA–target interactions based on several existing miRNA–target prediction programs, including TargetScan, miRanda, miRBase, and miRDB4. It also integrates these predictions with experimentally validated interactions from other databases, such as miRTarBase. | https://mirtarbase.cuhk.edu.cn/ (accessed on 26 April 2023) |
NONCODE [200] | This comprehensive database contains information about expression and functions of lncRNA. | www.noncode.org/introduce.php (accessed on 26 April 2023) |
lncRNAdb [201] | This database includes lncRNA annotations, functions, and interactions with other molecules. | https://ngdc.cncb.ac.cn/ (accessed on 26 April 2023) |
LNCipedia [202] | It includes comprehensive information on lncRNA structure, sequence, expression, and functional annotation. | https://lncipedia.org/ (accessed on 26 April 2023) |
LncBook [203] | It is a comprehensive dataset for studying the functions and mechanisms of lncRNAs. It integrates multi-omics data from expression, methylation, genome variation, and lncRNA–miRNA interactions, providing a more complete picture of the lncRNA molecular networks. | https://ngdc.cncb.ac.cn/lncbook/ (accessed on 26 April 2023) |
LncATLAS [204] and LncLocator [205] | LncATLAS is a database of lncRNA subcellular localization, whereas LncLocator can predict the subcellular localization of the lncRNAs. | https://lncatlas.crg.eu/ (accessed on 26 April 2023) http://www.csbio.sjtu.edu.cn/bioinf/lncLocator/ (accessed on 26 April 2023) |
piRNABank [206] | It provides information on piRNA sequences, genomic locations, expression patterns, and potential targets. | http://pirnabank.ibab.ac.in/ (accessed on 26 April 2023) |
piRBase [207] | The database comprises piRNA sequences, genomic locations, expression patterns, targets, and functions. | http://bigdata.ibp.ac.cn/piRBase/ (accessed on 26 April 2023) |
Rfam [208] | This database includes a variety of RNA families, including small nuclear RNAs. It provides annotation and alignment data, secondary structure predictions, and functional information for each family. | https://rfam.org/ (accessed on 26 April 2023) |
snOPY [209] | It provides comprehensive information about small nucleolar RNA (snoRNAs), snoRNA gene loci, and target RNAs. | http://snoopy.med.miyazaki-u.ac.jp/snorna_db.cgi (accessed on 26 April 2023) |
RNAcentral [210] | It is a comprehensive database that provides a single access point to a large and diverse collection of RNA sequences and their functions. | https://rnacentral.org/ (accessed on 26 April 2023) |
starBase [211] | This database can be used to identify the RNA–RNA and protein–RNA interaction networks. | http://starbase.sysu.edu.cn/ (accessed on 26 April 2023) |
RSEM [212] | This tool can be used for quantifying gene and transcript expression levels from RNA-Seq data. | software package |
miRDeep2 [213] | This tool can be used to identify novel and known miRNAs in deep sequencing data. | software package |
ANNOVAR [214] | This tool can be used to functionally annotate genetic variants, including noncoding regions detected from diverse genomes. | https://annovar.openbioinformatics.org/ (accessed on 26 April 2023) |
4. Conclusions
Funding
Conflicts of Interest
References
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Pathania, A.S. Crosstalk between Noncoding RNAs and the Epigenetics Machinery in Pediatric Tumors and Their Microenvironment. Cancers 2023, 15, 2833. https://doi.org/10.3390/cancers15102833
Pathania AS. Crosstalk between Noncoding RNAs and the Epigenetics Machinery in Pediatric Tumors and Their Microenvironment. Cancers. 2023; 15(10):2833. https://doi.org/10.3390/cancers15102833
Chicago/Turabian StylePathania, Anup S. 2023. "Crosstalk between Noncoding RNAs and the Epigenetics Machinery in Pediatric Tumors and Their Microenvironment" Cancers 15, no. 10: 2833. https://doi.org/10.3390/cancers15102833
APA StylePathania, A. S. (2023). Crosstalk between Noncoding RNAs and the Epigenetics Machinery in Pediatric Tumors and Their Microenvironment. Cancers, 15(10), 2833. https://doi.org/10.3390/cancers15102833