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eIF4E and eIF4GI have distinct and differential imprints on multiple myeloma's proteome and signaling.

Attar-Schneider O, Pasmanik-Chor M, Tartakover-Matalon S, Drucker L, Lishner M - Oncotarget (2015)

Bottom Line: Previously, we have shown that eIF4E/eIF4GI attenuation (siRNA/Avastin) deleteriously affected MM cells' fate and reduced levels of eIF4E/eIF4GI established targets.We showed different imprints for eIF4E and eIF4GI in all assayed aspects.These results promote our understanding of the relative contribution and importance of eIF4E and eIF4GI to the malignant phenotype and shed light on their function in eIF4F translation initiation complex.

View Article: PubMed Central - PubMed

Affiliation: Oncogenetic Laboratory, Meir Medical Center, Kfar Saba, Israel.

ABSTRACT
Accumulating data indicate translation plays a role in cancer biology, particularly its rate limiting stage of initiation. Despite this evolving recognition, the function and importance of specific translation initiation factors is unresolved. The eukaryotic translation initiation complex eIF4F consists of eIF4E and eIF4G at a 1:1 ratio. Although it is expected that they display interdependent functions, several publications suggest independent mechanisms. This study is the first to directly assess the relative contribution of eIF4F components to the expressed cellular proteome, transcription factors, microRNAs, and phenotype in a malignancy known for extensive protein synthesis-multiple myeloma (MM). Previously, we have shown that eIF4E/eIF4GI attenuation (siRNA/Avastin) deleteriously affected MM cells' fate and reduced levels of eIF4E/eIF4GI established targets. Here, we demonstrated that eIF4E/eIF4GI indeed have individual influences on cell proteome. We used an objective, high throughput assay of mRNA microarrays to examine the significance of eIF4E/eIF4GI silencing to several cellular facets such as transcription factors, microRNAs and phenotype. We showed different imprints for eIF4E and eIF4GI in all assayed aspects. These results promote our understanding of the relative contribution and importance of eIF4E and eIF4GI to the malignant phenotype and shed light on their function in eIF4F translation initiation complex.

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RPMI 8226 eIF4E/eIF4GI KDs demonstrated distinct dissimilarities in transcribed genes' repertoires and TFsRPMI 8226 cells were transfected with negative or anti eIF4E siRNA or anti eIF4GI siRNA. Total RNA was extracted 120 h post transfection and applied to whole genome Affymetrix microarray chips. Significantly altered gene lists were generated in comparison to negative control (p < 0.05 and 1.25 fold expression difference). Genelists were compared using Venny and newly produced lists of common and exclusive components of eIF4E/eIF4GI KDs (Venn diagram) were analyzed: (A) whole genome (B) panels of altered TFs deduced from whole genome data using bioinformatics tools (Webgestalt, ToppGene).
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Figure 1: RPMI 8226 eIF4E/eIF4GI KDs demonstrated distinct dissimilarities in transcribed genes' repertoires and TFsRPMI 8226 cells were transfected with negative or anti eIF4E siRNA or anti eIF4GI siRNA. Total RNA was extracted 120 h post transfection and applied to whole genome Affymetrix microarray chips. Significantly altered gene lists were generated in comparison to negative control (p < 0.05 and 1.25 fold expression difference). Genelists were compared using Venny and newly produced lists of common and exclusive components of eIF4E/eIF4GI KDs (Venn diagram) were analyzed: (A) whole genome (B) panels of altered TFs deduced from whole genome data using bioinformatics tools (Webgestalt, ToppGene).

Mentions: In our preceding studies we showed dependence of specific known targets on eIF4E/eIF4GI [12–14]. In those studies we used a KD model of eIF4E or eIF4GI in MM cell lines and demonstrated reduced targets' expression 96 hours post-transfection without reciprocal effect [13, 14]. Here, we obtained lists of genes with the Affymetrix microarrays depicting changes in expression upon eIF4E/eIF4GI KD 120 hours post-transfection. Using the nonparametric Kolmogorov-Smirnov we concluded that the data distribution is not normal. Hence, we applied the Wilcoxon signed ranks test and determined significant differences between the KDs' gene lists output (pv = 0.00048). These results suggested that there is a distinct dissimilarity in the effects of eIF4E and eIF4GI KDs on the transcribed genes' repertoire (Figure 1A), as most of the genes were unique to each treatment and only a small fraction was common. Differences between eIF4E and eIF4GI KDs were further characterized employing various bioinformatics tools (material and methods).


eIF4E and eIF4GI have distinct and differential imprints on multiple myeloma's proteome and signaling.

Attar-Schneider O, Pasmanik-Chor M, Tartakover-Matalon S, Drucker L, Lishner M - Oncotarget (2015)

RPMI 8226 eIF4E/eIF4GI KDs demonstrated distinct dissimilarities in transcribed genes' repertoires and TFsRPMI 8226 cells were transfected with negative or anti eIF4E siRNA or anti eIF4GI siRNA. Total RNA was extracted 120 h post transfection and applied to whole genome Affymetrix microarray chips. Significantly altered gene lists were generated in comparison to negative control (p < 0.05 and 1.25 fold expression difference). Genelists were compared using Venny and newly produced lists of common and exclusive components of eIF4E/eIF4GI KDs (Venn diagram) were analyzed: (A) whole genome (B) panels of altered TFs deduced from whole genome data using bioinformatics tools (Webgestalt, ToppGene).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4414192&req=5

Figure 1: RPMI 8226 eIF4E/eIF4GI KDs demonstrated distinct dissimilarities in transcribed genes' repertoires and TFsRPMI 8226 cells were transfected with negative or anti eIF4E siRNA or anti eIF4GI siRNA. Total RNA was extracted 120 h post transfection and applied to whole genome Affymetrix microarray chips. Significantly altered gene lists were generated in comparison to negative control (p < 0.05 and 1.25 fold expression difference). Genelists were compared using Venny and newly produced lists of common and exclusive components of eIF4E/eIF4GI KDs (Venn diagram) were analyzed: (A) whole genome (B) panels of altered TFs deduced from whole genome data using bioinformatics tools (Webgestalt, ToppGene).
Mentions: In our preceding studies we showed dependence of specific known targets on eIF4E/eIF4GI [12–14]. In those studies we used a KD model of eIF4E or eIF4GI in MM cell lines and demonstrated reduced targets' expression 96 hours post-transfection without reciprocal effect [13, 14]. Here, we obtained lists of genes with the Affymetrix microarrays depicting changes in expression upon eIF4E/eIF4GI KD 120 hours post-transfection. Using the nonparametric Kolmogorov-Smirnov we concluded that the data distribution is not normal. Hence, we applied the Wilcoxon signed ranks test and determined significant differences between the KDs' gene lists output (pv = 0.00048). These results suggested that there is a distinct dissimilarity in the effects of eIF4E and eIF4GI KDs on the transcribed genes' repertoire (Figure 1A), as most of the genes were unique to each treatment and only a small fraction was common. Differences between eIF4E and eIF4GI KDs were further characterized employing various bioinformatics tools (material and methods).

Bottom Line: Previously, we have shown that eIF4E/eIF4GI attenuation (siRNA/Avastin) deleteriously affected MM cells' fate and reduced levels of eIF4E/eIF4GI established targets.We showed different imprints for eIF4E and eIF4GI in all assayed aspects.These results promote our understanding of the relative contribution and importance of eIF4E and eIF4GI to the malignant phenotype and shed light on their function in eIF4F translation initiation complex.

View Article: PubMed Central - PubMed

Affiliation: Oncogenetic Laboratory, Meir Medical Center, Kfar Saba, Israel.

ABSTRACT
Accumulating data indicate translation plays a role in cancer biology, particularly its rate limiting stage of initiation. Despite this evolving recognition, the function and importance of specific translation initiation factors is unresolved. The eukaryotic translation initiation complex eIF4F consists of eIF4E and eIF4G at a 1:1 ratio. Although it is expected that they display interdependent functions, several publications suggest independent mechanisms. This study is the first to directly assess the relative contribution of eIF4F components to the expressed cellular proteome, transcription factors, microRNAs, and phenotype in a malignancy known for extensive protein synthesis-multiple myeloma (MM). Previously, we have shown that eIF4E/eIF4GI attenuation (siRNA/Avastin) deleteriously affected MM cells' fate and reduced levels of eIF4E/eIF4GI established targets. Here, we demonstrated that eIF4E/eIF4GI indeed have individual influences on cell proteome. We used an objective, high throughput assay of mRNA microarrays to examine the significance of eIF4E/eIF4GI silencing to several cellular facets such as transcription factors, microRNAs and phenotype. We showed different imprints for eIF4E and eIF4GI in all assayed aspects. These results promote our understanding of the relative contribution and importance of eIF4E and eIF4GI to the malignant phenotype and shed light on their function in eIF4F translation initiation complex.

Show MeSH
Related in: MedlinePlus