Endogenous tRNA-derived fragments suppress breast cancer progression via YBX1 displacement
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE63605 | GEO | 2015/05/07
SECONDARY ACCESSION(S): PRJNA268389
REPOSITORIES: GEO
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Project description:Upon exposure to stress, tRNAs are enzymatically cleaved, yielding distinct classes of tRNA-derived fragments (tRFs), yielding distinct classes of tRFs. We identify a novel class of tRFs derived from tRNA(Glu), tRNA(Asp), tRNA(Gly), and tRNA(Tyr) that, upon induction, suppress the stability of multiple oncogenic transcripts in breast cancer cells by displacing their 3' untranslated regions (UTRs) from the RNA-binding protein YBX1. This mode of post-transcriptional silencing is sequence specific, as these fragments all share a common motif that matches the YBX1 recognition sequence. Loss-of-function and gain-of-function studies, using anti-sense locked-nucleic acids (LNAs) and synthetic RNA mimetics, respectively, revealed that these fragments suppress growth under serum-starvation, cancer cell invasion, and metastasis by breast cancer cells. Highly metastatic cells evade this tumor-suppressive pathway by attenuating the induction of these tRFs. Our findings reveal a tumor-suppressive role for specific tRNA-derived fragments and describe a molecular mechanism for their action. This transcript displacement-based mechanism may generalize to other tRNA, ribosomal-RNA, and sno-RNA fragments.
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Project description:Endogenous tRNA-derived fragments suppress breast cancer progression via YBX1 displacement
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Project description:Effector CD8+ T cell activation and its cytotoxic function are positively correlated with improved survival in breast cancer. tRNA-derived fragments (tRFs) have recently been found to be involved in gene regulation in cancer progression. However, it is unclear how interactions between expression of tRFs and T cell activation affect breast cancer patient survival. We used Kaplan-Meier survival and multivariate Cox regression models to evaluate the effect of interactions between expression of tRFs and T cell activation on survival in 1081 breast cancer patients. Spearman correlation analysis and weighted gene co-expression network analysis were conducted to identify genes and pathways that were associated with tRFs. tRFdb-5024a, 5P_tRNA-Leu-CAA-4-1, and ts-49 were positively associated with overall survival, while ts-34 and ts-58 were negatively associated with overall survival. Significant interactions were detected between T cell activation and ts-34 and ts-49. In the T cell exhaustion group, patients with a low level of ts-34 or a high level of ts-49 showed improved survival. In contrast, there was no significant difference in the activation group. Breast cancer related pathways were identified for the five tRFs. In conclusion, the identified five tRFs associated with overall survival may serve as therapeutic targets and improve immunotherapy in breast cancer.
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Project description:BackgroundtRNA-derived fragments (tRFs) are 14-40-nucleotide-long, small non-coding RNAs derived from specific tRNA cleavage events with key regulatory functions in many biological processes. Many studies have shown that tRFs are associated with Argonaute (AGO) complexes and inhibit gene expression in the same manner as miRNAs. However, there are currently no tools for accurately predicting tRF target genes.MethodsWe used tRF-mRNA pairs identified by crosslinking, ligation, and sequencing of hybrids (CLASH) and covalent ligation of endogenous AGO-bound RNAs (CLEAR)-CLIP to assess features that may participate in tRF targeting, including the sequence context of each site and tRF-mRNA interactions. We applied genetic algorithm (GA) to select key features and support vector machine (SVM) to construct tRF prediction models.ResultsWe first identified features that globally influenced tRF targeting. Among these features, the most significant were the minimum free folding energy (MFE), position 8 match, number of bases paired in the tRF-mRNA duplex, and length of the tRF, which were consistent with previous findings. Our constructed model yielded an area under the receiver operating characteristic (ROC) curve (AUC) = 0.980 (0.977-0.983) in the training process and an AUC = 0.847 (0.83-0.861) in the test process. The model was applied to all the sites with perfect Watson-Crick complementarity to the seed in the 3' untranslated region (3'-UTR) of the human genome. Seven of nine target/nontarget genes of tRFs confirmed by reporter assay were predicted. We also validated the predictions via quantitative real-time PCR (qRT-PCR). Thirteen potential target genes from the top of the predictions were significantly down-regulated at the mRNA levels by overexpression of the tRFs (tRF-3001a, tRF-3003a or tRF-3009a).ConclusionsPredictions can be obtained online, tRFTars, freely available at http://trftars.cmuzhenninglab.org:3838/tar/ , which is the first tool to predict targets of tRFs in humans with a user-friendly interface.
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Project description:Small RNAs derived from tRNAs are attracting considerable attention; however, the effects of tRNA-derived fragments (tRFs) and tRNA halves (tiRNAs) as biomarkers have not been investigated in early-stage breast cancer (EBC). The study aimed to explore whether tRFs and tiRNAs could be detected in plasma and whether they could serve as diagnostic biomarkers. The study was conducted in four phases. Thirty tRFs and tiRNAs were selected by high-throughput sequencing in screening phase and then assessed in training, testing, and external validation phases by qRT-PCR. Six tRFs (tRF-Glu-CTC-003, tRF-Gly-CCC-007, tRF-Gly-CCC-008, tRF-Leu-CAA-003, tRF-Ser-TGA-001, and tRF-Ser-TGA-002) were found significantly downregulated in plasma samples of patients with EBC compared with normal controls, and all were derived from 5' ends of tRNAs. Patients with HER2+ EBC with low expression levels of tRF-Glu-CTC-003 were related to worse disease-free survival and overall survival. The identified tRFs were further examined in cell supernatants, exosomes isolated from plasma, and tissues. In conclusion, our study identified six tRFs from the 5' ends of tRNAs as novel diagnostic biomarkers for EBC, providing additional evidence for, and a better understanding of, circulating tRFs and EBC.
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