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RNA G-quadruplexes cause eIF4A-dependent oncogene translation in cancer.

Wolfe AL, Singh K, Zhong Y, Drewe P, Rajasekhar VK, Sanghvi VR, Mavrakis KJ, Jiang M, Roderick JE, Van der Meulen J, Schatz JH, Rodrigo CM, Zhao C, Rondou P, de Stanchina E, Teruya-Feldstein J, Kelliher MA, Speleman F, Porco JA, Pelletier J, Rätsch G, Wendel HG - Nature (2014)

Bottom Line: Accordingly, inhibition of eIF4A with silvestrol has powerful therapeutic effects against murine and human leukaemic cells in vitro and in vivo.Notably, among the most eIF4A-dependent and silvestrol-sensitive transcripts are a number of oncogenes, superenhancer-associated transcription factors, and epigenetic regulators.Hence, the 5' UTRs of select cancer genes harbour a targetable requirement for the eIF4A RNA helicase.

View Article: PubMed Central - PubMed

Affiliation: 1] Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA [2] Weill Cornell Graduate School of Medical Sciences, New York, New York 10065, USA [3].

ABSTRACT
The translational control of oncoprotein expression is implicated in many cancers. Here we report an eIF4A RNA helicase-dependent mechanism of translational control that contributes to oncogenesis and underlies the anticancer effects of silvestrol and related compounds. For example, eIF4A promotes T-cell acute lymphoblastic leukaemia development in vivo and is required for leukaemia maintenance. Accordingly, inhibition of eIF4A with silvestrol has powerful therapeutic effects against murine and human leukaemic cells in vitro and in vivo. We use transcriptome-scale ribosome footprinting to identify the hallmarks of eIF4A-dependent transcripts. These include 5' untranslated region (UTR) sequences such as the 12-nucleotide guanine quartet (CGG)4 motif that can form RNA G-quadruplex structures. Notably, among the most eIF4A-dependent and silvestrol-sensitive transcripts are a number of oncogenes, superenhancer-associated transcription factors, and epigenetic regulators. Hence, the 5' UTRs of select cancer genes harbour a targetable requirement for the eIF4A RNA helicase.

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Analysis of genes with differential ribosomal distribution (rDiff positive set)a) Representation of ribosome coverage for 826 transcripts with significant changes in distribution between Silvestrol (red) and vehicle (black); corresponding to the rDiff positive gene list after filtering out genes with 5′ UTR length < 20nt. Both RF coverage and transcript length are normalized for comparison; translation start and stop sites are indicated by blue lines, n = 826; b–c) Ribosomal distribution plots, as in a, showing how Silvestrol affects ribosome distribution in all TE up genes (b), n = 182 after filtering out genes with 5′ UTR length < 20nt and all TE down genes (c), n = 276 after filtering out genes with 5′ UTR length < 20nt; d) Length comparison of 5′UTRs of genes with significantly altered ribosomal distribution (rDiff positive: red) and background genes (black); *: mean value, n = 826; e) Percentage of rDiff positive genes and background genes containing the indicated sequence motifs, * indicates p < 0.05, n = 2 biological replicates; f–g) The rDiff positive genes are enriched for the indicated 12-mer (f) and 9-mer (g) consensus motifs.
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Figure 10: Analysis of genes with differential ribosomal distribution (rDiff positive set)a) Representation of ribosome coverage for 826 transcripts with significant changes in distribution between Silvestrol (red) and vehicle (black); corresponding to the rDiff positive gene list after filtering out genes with 5′ UTR length < 20nt. Both RF coverage and transcript length are normalized for comparison; translation start and stop sites are indicated by blue lines, n = 826; b–c) Ribosomal distribution plots, as in a, showing how Silvestrol affects ribosome distribution in all TE up genes (b), n = 182 after filtering out genes with 5′ UTR length < 20nt and all TE down genes (c), n = 276 after filtering out genes with 5′ UTR length < 20nt; d) Length comparison of 5′UTRs of genes with significantly altered ribosomal distribution (rDiff positive: red) and background genes (black); *: mean value, n = 826; e) Percentage of rDiff positive genes and background genes containing the indicated sequence motifs, * indicates p < 0.05, n = 2 biological replicates; f–g) The rDiff positive genes are enriched for the indicated 12-mer (f) and 9-mer (g) consensus motifs.

Mentions: We developed the DERseq algorithm (Differential Expression-normalized Ribosome-occupancy; based on DEXseq24) to identify mRNAs that were most strongly affected by Silvestrol. We used a cut-off at p < 0.03 (Z-score > 2.5) to define groups of mRNAs whose translational efficiency was the most (TE down; red) or least (TE up; blue) affected by Silvestrol compared to background (grey) (Figure 3b, Suppl. Table 3a–c). The TE down group includes 281 mRNAs (220 with annotated 5′UTRs), TE up includes 190 mRNAs, and the background list 2243 mRNAs. The footprinting methodology also provides positional information and the rDiff algorithm identifies mRNAs with significant shifts in RF distribution25. For example, Silvestrol caused an accumulation of RFs in the 5′UTR of 847 protein-coding transcripts (rDiff positive genes; 641 with annotated 5′UTRs; p < 0.001) (Suppl. Table 3d). Sixty-two transcripts showed both decreased TE and altered RF distribution, while we observed no change in distribution among TE up genes (Figure 3c, Extended Data Fig. 5a–c, Suppl. Table 3e).


RNA G-quadruplexes cause eIF4A-dependent oncogene translation in cancer.

Wolfe AL, Singh K, Zhong Y, Drewe P, Rajasekhar VK, Sanghvi VR, Mavrakis KJ, Jiang M, Roderick JE, Van der Meulen J, Schatz JH, Rodrigo CM, Zhao C, Rondou P, de Stanchina E, Teruya-Feldstein J, Kelliher MA, Speleman F, Porco JA, Pelletier J, Rätsch G, Wendel HG - Nature (2014)

Analysis of genes with differential ribosomal distribution (rDiff positive set)a) Representation of ribosome coverage for 826 transcripts with significant changes in distribution between Silvestrol (red) and vehicle (black); corresponding to the rDiff positive gene list after filtering out genes with 5′ UTR length < 20nt. Both RF coverage and transcript length are normalized for comparison; translation start and stop sites are indicated by blue lines, n = 826; b–c) Ribosomal distribution plots, as in a, showing how Silvestrol affects ribosome distribution in all TE up genes (b), n = 182 after filtering out genes with 5′ UTR length < 20nt and all TE down genes (c), n = 276 after filtering out genes with 5′ UTR length < 20nt; d) Length comparison of 5′UTRs of genes with significantly altered ribosomal distribution (rDiff positive: red) and background genes (black); *: mean value, n = 826; e) Percentage of rDiff positive genes and background genes containing the indicated sequence motifs, * indicates p < 0.05, n = 2 biological replicates; f–g) The rDiff positive genes are enriched for the indicated 12-mer (f) and 9-mer (g) consensus motifs.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4492470&req=5

Figure 10: Analysis of genes with differential ribosomal distribution (rDiff positive set)a) Representation of ribosome coverage for 826 transcripts with significant changes in distribution between Silvestrol (red) and vehicle (black); corresponding to the rDiff positive gene list after filtering out genes with 5′ UTR length < 20nt. Both RF coverage and transcript length are normalized for comparison; translation start and stop sites are indicated by blue lines, n = 826; b–c) Ribosomal distribution plots, as in a, showing how Silvestrol affects ribosome distribution in all TE up genes (b), n = 182 after filtering out genes with 5′ UTR length < 20nt and all TE down genes (c), n = 276 after filtering out genes with 5′ UTR length < 20nt; d) Length comparison of 5′UTRs of genes with significantly altered ribosomal distribution (rDiff positive: red) and background genes (black); *: mean value, n = 826; e) Percentage of rDiff positive genes and background genes containing the indicated sequence motifs, * indicates p < 0.05, n = 2 biological replicates; f–g) The rDiff positive genes are enriched for the indicated 12-mer (f) and 9-mer (g) consensus motifs.
Mentions: We developed the DERseq algorithm (Differential Expression-normalized Ribosome-occupancy; based on DEXseq24) to identify mRNAs that were most strongly affected by Silvestrol. We used a cut-off at p < 0.03 (Z-score > 2.5) to define groups of mRNAs whose translational efficiency was the most (TE down; red) or least (TE up; blue) affected by Silvestrol compared to background (grey) (Figure 3b, Suppl. Table 3a–c). The TE down group includes 281 mRNAs (220 with annotated 5′UTRs), TE up includes 190 mRNAs, and the background list 2243 mRNAs. The footprinting methodology also provides positional information and the rDiff algorithm identifies mRNAs with significant shifts in RF distribution25. For example, Silvestrol caused an accumulation of RFs in the 5′UTR of 847 protein-coding transcripts (rDiff positive genes; 641 with annotated 5′UTRs; p < 0.001) (Suppl. Table 3d). Sixty-two transcripts showed both decreased TE and altered RF distribution, while we observed no change in distribution among TE up genes (Figure 3c, Extended Data Fig. 5a–c, Suppl. Table 3e).

Bottom Line: Accordingly, inhibition of eIF4A with silvestrol has powerful therapeutic effects against murine and human leukaemic cells in vitro and in vivo.Notably, among the most eIF4A-dependent and silvestrol-sensitive transcripts are a number of oncogenes, superenhancer-associated transcription factors, and epigenetic regulators.Hence, the 5' UTRs of select cancer genes harbour a targetable requirement for the eIF4A RNA helicase.

View Article: PubMed Central - PubMed

Affiliation: 1] Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA [2] Weill Cornell Graduate School of Medical Sciences, New York, New York 10065, USA [3].

ABSTRACT
The translational control of oncoprotein expression is implicated in many cancers. Here we report an eIF4A RNA helicase-dependent mechanism of translational control that contributes to oncogenesis and underlies the anticancer effects of silvestrol and related compounds. For example, eIF4A promotes T-cell acute lymphoblastic leukaemia development in vivo and is required for leukaemia maintenance. Accordingly, inhibition of eIF4A with silvestrol has powerful therapeutic effects against murine and human leukaemic cells in vitro and in vivo. We use transcriptome-scale ribosome footprinting to identify the hallmarks of eIF4A-dependent transcripts. These include 5' untranslated region (UTR) sequences such as the 12-nucleotide guanine quartet (CGG)4 motif that can form RNA G-quadruplex structures. Notably, among the most eIF4A-dependent and silvestrol-sensitive transcripts are a number of oncogenes, superenhancer-associated transcription factors, and epigenetic regulators. Hence, the 5' UTRs of select cancer genes harbour a targetable requirement for the eIF4A RNA helicase.

Show MeSH
Related in: MedlinePlus