Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2015 May 7;161(4):790-802.
doi: 10.1016/j.cell.2015.02.053.

Endogenous tRNA-Derived Fragments Suppress Breast Cancer Progression via YBX1 Displacement

Affiliations

Endogenous tRNA-Derived Fragments Suppress Breast Cancer Progression via YBX1 Displacement

Hani Goodarzi et al. Cell. .

Abstract

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.

PubMed Disclaimer

Figures

Figure 1
Figure 1. Genome-wide profiling of tRNA-derived fragments in breast cancer MDA-231 cells under normal and hypoxic conditions
(A) The linear motif SCUBYC was enriched in RNA fragments mapping to tRNA loci that were up-regulated in MDA-parental cells, but not MDA-LM2 cells, under hypoxic conditions. Shown are the mutual information values and their associated z-scores for the discovered motif in both cell-lines (Elemento et al., 2007). The enrichment score (positive for enrichment and negative for depletion), presented as logP (hypergeometric p-value), is also shown as a heatmap with blue showing depletion and yellow showing enrichment of the SCUBYC motif among the sequences in each cluster. The red border marks statistical significance of the enrichment score. (B) The levels of tRFs derived from tRNAGlu were significantly enhanced under hypoxic conditions in MDA-parental cells but not in MDA-LM2 cells. The log fold-change was calculated from the small-RNA sequencing data. The p-value was calculated using Wilcoxon rank sum test. Two exemplary tRFs that contain the SCUBYC motif are also indicated. (C) Streptavidin beads were used to co-precipitate proteins interacting with a 3′-biotinylated synthetic tRFGlu mimetic and scrambled oligonucleotide in vivo. YBX1 was identified as a potential interacting partner based on the identity of the annotated RNA-protein complexes enriched among the tRFGlu co-precipitated RNA binding proteins. (D) 3′-biotinylated synthetic oligonucleotides were used to co-precipitate YBX1. In addition to the scrambled RNA, a tRNAAla-derived fragment, which does not carry the identified motif, was also included as control. Western blotting was performed to detect YBX1 in the eluate from each sample. (E) MDA-LM2 cells were transfected with a 21-nt synthetic tRFGlu mimetic (unlabeled), also shown are scrambled transfected mimetic and untransfected cells as controls. After crosslinking immunoprecipitation of endogenous YBX1, and radiolabeling of the RNA population, a strong interaction between the transfected tRFGlu mimetic and endogenous YBX1 was observed. Error bars in all panels indicate s.e.m. unless otherwise specified.
Figure 2
Figure 2. Endogenous YBX1 interacts with a large regulon of transcripts and small-RNAs in vivo
(A) Pie-charts depicting the annotation of YBX1 binding sites obtained from immunoprecipitation of endogenous YBX1 from RNase-treated lysate of UV-irradiated MDA-parental cells followed by high-throughput sequencing of both long- and small-RNAs. (B) Relative frequency of reads mapped to each tRNA-locus in MDA-parental small-RNA sequencing and YBX1 small-RNA CLIP-seq. The tRF species most abundantly bound by YBX1 are marked. (C) Based on the YBX1 small-RNA CLIP-seq results, four species of tRNA-derived RNA fragments (tRFs) bound by YBX1 in vivo were identified. Shown are examples of tRNA structures for each species depicting the boundaries of the identified tRFs along with the YBX1 binding region based on smRNA YBX1 CLIP-seq read density at each position (also see Figure S2A). The grey nucleotides at the 3′ end mark the presence of terminal CCA sequences. The dark grey highlights for tRNATyrGTA mark the leader and intronic sequences in the unprocessed tRNA. The longest identified form of each tRF based on our high-throughput sequencing results are also indicated (grey highlight) along with the YBX1 smRNA CLIP-seq read density at each position (overlaid as a heatmap) indicating the YBX1 binding site. (D) Gene-expression profiling of control and YBX1-knockdown cells was performed under normal and hypoxic conditions in both MDA-parental and MDA-LM2 backgrounds. The set of transcripts that was down-regulated under hypoxia in a YBX1-dependent manner was identified for each cell-line. While YBX1-bound transcripts were significantly enriched among YBX1-dependent hypoxia-induced downregulated transcripts in MDA-parental cells, this enrichment was absent in the highly metastatic MDA-LM2 cells. (E) qPCR-based validation of interactions between YBX1 and tRFAspGTC, tRFGluYTC, and tRFGlyTCC. Cells transfected with exogenous tRF mimetics were subjected to UV-crosslinking and YBX1 immunoprecipitation. The abundance of each tRF in the co-immunoprecipitated RNA population was then measured using a small-RNA qPCR-based quantitation assay (n=3–4). Statistical significance is measured using one-tailed Student’s t-test: *, p<0.05, **, p<0.01, and ***, p<0.001. Error bars in all panels indicate s.e.m. unless otherwise specified.
Figure 3
Figure 3. YBX1 interacts with long- and small-RNAs via a specific linear sequence motif
(A) The transcripts up-regulated upon antisense LNA transfections targeting each of the four identified tRFs were compared to the remainder of the transcriptome (background) to identify over-representation of specific sequence elements in their 3′ UTRs. Here, we have shown the enrichment of specific 8-mers along each YBX1-bound tRF in the 3′ UTRs of these transcripts as a heatmap, with yellow and blue showing the extent of enrichment and depletion respectively (red and blue borders mark statistical significane). Also shown are the associated mutual information values and z-scores (Elemento et al., 2007). We have provided the sequence of each tRF and highlighted the identified 8-mers. (B) These 8-mers were also required to be enriched among the YBX1 binding sites identified using CLIP-seq. We used a shuffled version of each YBX1-binding site to create a background set and tested the enrichment of each 8-mer in the YBX1 binding sites relative to shuffled controls. (C) In order to infer a consensus element for YBX1 on these tRFs, the four significant 8-mers were aligned and the possible nucleotides at each position were combined to build the CU-box element represented as a regular expression. (D) The CU-box motif showed a significant enrichment in both long- and small-RNA YBX1 CLIP-seq datasets relative to randomly shuffled sequences, indicating YBX1 binds a common linear sequence motif on both short and long endogenous RNAs. Error bars in all panels indicate s.e.m. unless otherwise specified.
Figure 4
Figure 4. Endogenous transcripts bound by YBX1 are modulated by YBX1-bound tRFs
In order to measure the post-transcriptional regulatory consequences of tRFs, gain-of-function and loss-of-fuction experiments were performed by transfecting synthetic tRF mimetics or inhibitory antisense LNAs, for each of the four YBX1-binding tRFs, in normal and YBX1 knockdown cells. Transcripts that were up- or down-regulated in a YBX1 dependent manner were identified by comparing the gene expression changes in normal cells relative to those in YBX1-knockdown cells (Figure S3). Transcripts that interact with YBX1 in vivo (determined from YBX1 CLIP-seq data) were significantly deregulated upon modulations of tRF levels: (A) they were up-regulated upon LNA-mediated inhibition of YBX1-binding tRFs; (B–C) they were down-regulated in the presence of exogenously added short and long tRF mimetics (~60 and ~20 nucleotides respectively; see Figure S2B), and (D) the observed up-regulation in the LNA-transfected cells coincided with a significant increase in their stability. Whole-genome transcript stability measurements were performed in LNA-transfected cells using α-amanitin-mediated inhibition of RNA polymerase II followed by RNA extraction and profiling at 0- and 8-hr time-points. In all datasets, the calculated mutual information values (in bits) and their associated p-values are provided. Also shown are the enrichment scores, presented as logP (positivie for enrichments and negative for depletions) where P is calculated from hypergeometric distribution (shown as a heatmap with blue and gold showing depletion and enrichment respectively). The red and blue borders mark statistical significance of the enrichment/depletions. Error bars in all panels indicate s.e.m. unless otherwise specified.
Figure 5
Figure 5. YBX1 target transcripts and their response to changes in tRF levels
(A) YBX1 interacts with the 3′UTRs of HMGA1, CD151, CD97, and TIMP3. The last exon of the indicated transcripts are shown with mapped reads from experimental replicates of YBX1 CLIP-seq. (B) Transfection of antisense LNAs against YBX1-binding tRFs resulted in the up-regulation of HMGA1, CD151, CD97, and TIMP3 transcripts, in a YBX1-dependent manner, as determined by qPCR measurements. (C) Similarly, transfecting antisense LNAs resulted in a significant stabilization of HMGA1, CD97, and TIMP3 transcripts in a YBX1-dependent manner. Whole-genome RNA stability measurements were perfomed using α-amanitin-mediated inhibition of RNA polymerase II (see Methods). (D) A GFP/mCherry dual-reporter assay was used to measure the effects of cloning HMGA1, CD97, and part of the TIMP3 3′ UTRs downstream of mCherry using qRT-PCR. The 3′ UTR of MAPK14, which is devoid of YBX1 tags, was included as a control. Consistent with our prior findings, LNA transfections resulted in a significant increase in relative mCherry expression in a YBX1-dependent manner. (E) Exogenously added tRF mimetics, while showing no effect on MAPK14 abundance, resulted in a significant depletion of HMGA1, CD97, and TIMP3 transcripts from the YBX1 co-immunoprecipitated RNA population. Statistical significance is measured using one-tailed Student’s t-test: *, p<0.05, **, p<0.01, and ***, p<0.001. Error bars in all panels indicate s.e.m. unless otherwise specified.
Figure 6
Figure 6. YBX1-binding tRFs play a significant role in modulating oncogenes
(A) Competitive displacement of YBX1 from its target transcripts by tRNA-derived fragments resulted in the down-regulation of a large set of oncogenes and metastasis promoter genes. (B–D) Kaplan-Meier curves for three translation initiation factors that were modulated by tRFs via YBX1 binding (Gyorffy et al., 2012). (E) Exogenously added tRF mimetics or antisense LNAs resulted in a significant increase and decrease in cancer cell invasion, respectively. Shown are the fold-changes in cancer cell invasion for MDA-parental cells transfected with LNAs and MDA-LM2 cells transfected with tRFs. We have also included representative fields from the invasion inserts along with the median of cells observed in each cohort (n=7–8). (F) Growth rates (estimated based on an exponential model) under serum-starved conditions for MDA-LM2 cells transfected with tRF mimetics relative to mock-transfected cells (n=6). (G) qRT-PCR assays were used to quantify the levels of tRFAsp, tRFGlu, and tRFGly in metastatic (n=18) and non-metastatic (n=9) primary breast cancers. For comparing growth under serum-starved conditions, two-way ANOVA was used to measure statistical significance. For all other cases, statistical significance was measured using one-tailed Student’s t-test: *, p<0.05, **, p<0.01, and ***, p<0.001. Error bars in all panels indicate s.e.m. unless otherwise specified.
Figure 7
Figure 7. YBX1-binding tRFs play a significant role as suppressors of tumor progression and metastasis
(A–B) Bioluminescence imaging plot of metastatic lung colonization by MDA-parental and CN-parental cells transfected with synthetic antisense LNAs against all four YBX1-binding tRFs. Representative images along with quantification of the area-under-the-curve for each mouse are also included (n=3–5 in each cohort). (C–D) Bioluminescence imaging plot of lung metastasis by MDA-LM2 and CN-LM1a cells transfected with the four YBX1-binding tRFs. Representative images and area-under-the-curve quantifications are also included (n=4–5 in each cohort). (E) Bioluminescence imaging plot of lung metastasis by HCC1806 cells transfected with the four YBX1-binding tRFs. Representative images and area-under-the-curve quantifications are also included (n=5 in each cohort). (F) Schematic of tRF-mediated modulation of invasion and metastatic lung colonization through in vivo titration of YBX1 and the subsequent destabilization of its oncogenic and pro-metastatic targets. For comparing metastasis colonization assays, two-way ANOVA was used to measure statistical significance. For all other cases, statistical significance is measured using one-tailed Student’s t-test: *, p<0.05, **, p<0.01, and ***, p<0.001. Error bars in all panels indicate s.e.m. unless otherwise specified.

Comment in

  • Non-coding RNA: Stressed to bits.
    Seton-Rogers S. Seton-Rogers S. Nat Rev Cancer. 2015 Jun;15(6):320. doi: 10.1038/nrc3966. Nat Rev Cancer. 2015. PMID: 25998710 No abstract available.

References

    1. Borek E, Baliga BS, Gehrke CW, Kuo CW, Belman S, Troll W, Waalkes TP. High turnover rate of transfer RNA in tumor tissue. Cancer research. 1977;37:3362–3366. - PubMed
    1. Bristow RG, Hill RP. Hypoxia and metabolism. Hypoxia, DNA repair and genetic instability. Nature reviews Cancer. 2008;8:180–192. - PubMed
    1. Cole C, Sobala A, Lu C, Thatcher SR, Bowman A, Brown JWS, Green PJ, Barton GJ, Hutvagner G. Filtering of deep sequencing data reveals the existence of abundant Dicer-dependent small RNAs derived from tRNAs. Rna. 2009;15:2147–2160. - PMC - PubMed
    1. Elemento O, Slonim N, Tavazoie S. A universal framework for regulatory element discovery across all Genomes and data types. Molecular cell. 2007;28:337–350. - PMC - PubMed
    1. Emara MM, Ivanov P, Hickman T, Dawra N, Tisdale S, Kedersha N, Hu GF, Anderson P. Angiogenin-induced tRNA-derived Stress-induced RNAs Promote Stress-induced Stress Granule Assembly. Journal of Biological Chemistry. 2010;285:10959–10968. - PMC - PubMed

Publication types

MeSH terms

Associated data