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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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Ribosome footprinting defines Silvestrol’s effects on translationa) Schematic of the ribosome footprinting study; b) Frequency distribution of the ratio of translational efficiency (TE) in control and Silvestrol treated samples (TESilvestrol/TEcontrol). More or less affected mRNAs identified as TE down (red) and TE up (blue); n = 2 replicates; c) Ribosome distribution for 62 TE down and rDiff positive transcripts upon Silvestrol (red) or vehicle (black). RF coverage and transcript length are normalized, blue indicates translation start and stop sites; d) Comparison of 5′UTR lengths for TE down versus background genes. Mathematical density is scaled such that all values on the x-axis sum to 1; red: TE down, black: background genes, *: mean value, n = 2 replicates; e) Prevalence of the indicated 5′UTR motifs among the TE down and background genes (n.s.: not significant p > 0.05); f) 12-mer motif enriched in TE down genes (p = 2 × 10−16); g) Three most common 9-mer motifs in TE down genes; h) Enrichment of 12-mer and 9-mer motifs in the rDiff gene set.
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Figure 3: Ribosome footprinting defines Silvestrol’s effects on translationa) Schematic of the ribosome footprinting study; b) Frequency distribution of the ratio of translational efficiency (TE) in control and Silvestrol treated samples (TESilvestrol/TEcontrol). More or less affected mRNAs identified as TE down (red) and TE up (blue); n = 2 replicates; c) Ribosome distribution for 62 TE down and rDiff positive transcripts upon Silvestrol (red) or vehicle (black). RF coverage and transcript length are normalized, blue indicates translation start and stop sites; d) Comparison of 5′UTR lengths for TE down versus background genes. Mathematical density is scaled such that all values on the x-axis sum to 1; red: TE down, black: background genes, *: mean value, n = 2 replicates; e) Prevalence of the indicated 5′UTR motifs among the TE down and background genes (n.s.: not significant p > 0.05); f) 12-mer motif enriched in TE down genes (p = 2 × 10−16); g) Three most common 9-mer motifs in TE down genes; h) Enrichment of 12-mer and 9-mer motifs in the rDiff gene set.

Mentions: For footprinting studies, we treated KOPT-K1 cells with 25 nM of Silvestrol or vehicle for 45 minutes, then deep-sequenced total RNA and ribosome protected RNA (ribosome footprints = RFs) (Figure 3a)14. We removed reads mapping to ribosomal RNAs, non-coding RNAs, library linkers, and incomplete alignments (Extended Data Fig. 4a/b). The majority of the remaining reads between 25–35 nucleotides in length mapped to protein coding genes (Extended Data Fig. 4c/d). The total number of RF reads that mapped to exons was 3.2 million in control and 3.4 million Silvestrol samples and this corresponded to ~11,128 protein coding genes. RF reads showed a wider variation between control and Silvestrol than total RNA sequences indicating minimal transcriptional variation (Extended Data Fig. 4e). The number of ribosomes occupying any transcript is given as gene specific RF reads per one million total reads (RPM). The RPM frequency distribution in control and Silvestrol samples was overlapping, indicating that Silvestrol equally affected mRNAs with high and low ribosome occupancy (Extended Data Fig. 4f). Polysome analysis and metabolic labelling with L-azidohomoalanine (AHA) labelling confirmed an inhibitory effect on translation (AHA: Silvestrol ~ 60%; p(Silv. vs. Veh.) = 3.6 × 10−3; Cycloheximide 80%, p(CHX vs. Veh.) = 2 × 10−4) (Extended Data Fig. 4g/h). The translational efficiency (TE) for each mRNA is calculated by normalizing the RF frequency to transcript length and total transcript abundance (RPKM: reads per kilobase per million reads). RPKM values for RF from vehicle and Silvestrol samples were correlated (R2 = 0.94) indicating an overall inhibitory effect (Extended Data Fig. 4i).


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)

Ribosome footprinting defines Silvestrol’s effects on translationa) Schematic of the ribosome footprinting study; b) Frequency distribution of the ratio of translational efficiency (TE) in control and Silvestrol treated samples (TESilvestrol/TEcontrol). More or less affected mRNAs identified as TE down (red) and TE up (blue); n = 2 replicates; c) Ribosome distribution for 62 TE down and rDiff positive transcripts upon Silvestrol (red) or vehicle (black). RF coverage and transcript length are normalized, blue indicates translation start and stop sites; d) Comparison of 5′UTR lengths for TE down versus background genes. Mathematical density is scaled such that all values on the x-axis sum to 1; red: TE down, black: background genes, *: mean value, n = 2 replicates; e) Prevalence of the indicated 5′UTR motifs among the TE down and background genes (n.s.: not significant p > 0.05); f) 12-mer motif enriched in TE down genes (p = 2 × 10−16); g) Three most common 9-mer motifs in TE down genes; h) Enrichment of 12-mer and 9-mer motifs in the rDiff gene set.
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Related In: Results  -  Collection

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

Figure 3: Ribosome footprinting defines Silvestrol’s effects on translationa) Schematic of the ribosome footprinting study; b) Frequency distribution of the ratio of translational efficiency (TE) in control and Silvestrol treated samples (TESilvestrol/TEcontrol). More or less affected mRNAs identified as TE down (red) and TE up (blue); n = 2 replicates; c) Ribosome distribution for 62 TE down and rDiff positive transcripts upon Silvestrol (red) or vehicle (black). RF coverage and transcript length are normalized, blue indicates translation start and stop sites; d) Comparison of 5′UTR lengths for TE down versus background genes. Mathematical density is scaled such that all values on the x-axis sum to 1; red: TE down, black: background genes, *: mean value, n = 2 replicates; e) Prevalence of the indicated 5′UTR motifs among the TE down and background genes (n.s.: not significant p > 0.05); f) 12-mer motif enriched in TE down genes (p = 2 × 10−16); g) Three most common 9-mer motifs in TE down genes; h) Enrichment of 12-mer and 9-mer motifs in the rDiff gene set.
Mentions: For footprinting studies, we treated KOPT-K1 cells with 25 nM of Silvestrol or vehicle for 45 minutes, then deep-sequenced total RNA and ribosome protected RNA (ribosome footprints = RFs) (Figure 3a)14. We removed reads mapping to ribosomal RNAs, non-coding RNAs, library linkers, and incomplete alignments (Extended Data Fig. 4a/b). The majority of the remaining reads between 25–35 nucleotides in length mapped to protein coding genes (Extended Data Fig. 4c/d). The total number of RF reads that mapped to exons was 3.2 million in control and 3.4 million Silvestrol samples and this corresponded to ~11,128 protein coding genes. RF reads showed a wider variation between control and Silvestrol than total RNA sequences indicating minimal transcriptional variation (Extended Data Fig. 4e). The number of ribosomes occupying any transcript is given as gene specific RF reads per one million total reads (RPM). The RPM frequency distribution in control and Silvestrol samples was overlapping, indicating that Silvestrol equally affected mRNAs with high and low ribosome occupancy (Extended Data Fig. 4f). Polysome analysis and metabolic labelling with L-azidohomoalanine (AHA) labelling confirmed an inhibitory effect on translation (AHA: Silvestrol ~ 60%; p(Silv. vs. Veh.) = 3.6 × 10−3; Cycloheximide 80%, p(CHX vs. Veh.) = 2 × 10−4) (Extended Data Fig. 4g/h). The translational efficiency (TE) for each mRNA is calculated by normalizing the RF frequency to transcript length and total transcript abundance (RPKM: reads per kilobase per million reads). RPKM values for RF from vehicle and Silvestrol samples were correlated (R2 = 0.94) indicating an overall inhibitory effect (Extended Data Fig. 4i).

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