Please note that we have stopped the regular imports of Gene Expression Omnibus (GEO) data into ArrayExpress. This may not be the latest version of this experiment.
E-GEOD-62821 - EIF4E AND EIF4GI HAVE DISTINCT AND DIFFERENTIAL IMPRINTS ON MULTIPLE MYELOMA'S PROTEOME AND SIGNALING
Released on 29 October 2015, last updated on 8 December 2015
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. This study concentrated on a particular cancer model and studied the role of eIF4E and eIF4GI in the design of the cells' proteome. We used an unbiased, high throughput system to evaluate the individual importance of eIF4E and eIF4GI levels in MM. We used models of eIF4E or eIF4GI knocked down (KD) MM cell line RPMI 8226 and profiled their respective translated transcription factors (TF), often tumor suppressors or oncogenes. Furthermore, we assessed the KDs' microRNAs repertoires and cells' phenotype. Significant differences were observed between eIF4E and eIF4GI knockdown imprints.
transcription profiling by array
Metsada Pasmanik-Chor <firstname.lastname@example.org>, Attar-Schneider Oshrat, Liat Drucker, Michael Lishner, Shelly Tartakover-Matalon