Abstract A12: Role of eIF5-mimic protein 1 (5MP1) for translational control in cancer
Bibliographic record
Abstract
Abstract In eukaryotic translation initiation, both the m7G-capped mRNA and the small ribosomal subunit (SSU) are activated through eukaryotic initiation factors bound to Met-tRNAIMet, which allows formation of the 48S ribosome pre-initiation complex (PIC) with the small subunit attached to the mRNA 5' end. The PIC subsequently scans for a start codon, upon which it forms the ribosome initiation complex, ready for the polypeptide elongation, with the large subunit joined together. eIF5 is a crucial component of the multi-initiation factor complex (MFC) involved in the SSU activation and subsequent start codon selection by the 48S complex through its GTPase activating function (GAP). Paradoxically, however, overexpression turns eIF5 into an inhibitor of translation and decreases the accuracy of translation initiation, thereby allowing non-AUG initiation. Translation regulatory protein termed eIF5-mimic protein (5MP) exists in nearly all the eukaryotes except in nematodes, yeasts and some protozoans. Humans encode two of its copies, 5MP1 and 5MP2. It interacts with eIF2 and eIF3, major MFC components, and induces translation of ATF4 mRNA with regulatory uORFs. ATF4 is a pro-oncogenic transcription factor whose expression endorses tumor survival during stress conditions (hypoxia and nutritional deprivation) encountered by cancer cells in their development and metastasis. Moreover, preliminary study using yeast as a model system suggests that the universal role of 5MP in eukaryotic translation initiation is to increase the accuracy of translation initiation through inhibiting mis-initiation caused by excessive amount of eIF5. Here we examined the role of 5MP1 and 5MP2 in cultured human cells and found that 5MP1 expression suppresses non-AUG initiation of a luciferease reporter gene that occurs normally at a low level or at a higher level due to eIF5 overexpression, depending on its ability to bind the PIC. Furthermore, ribosome profiling studies in human cells show that expression of 5MP1 by itself inhibits non-AUG initiation of endogenous genes, such as GUG-initiated NAT1/eif4g2 and CUG-initiated c-Myc. These results indicate that 5MP in general suppresses non-AUG initiation through competing with eIF5 that occurs free of the ribosome. In support of the role of 5MP in cancer progression, 5MP1 knockdown and 5MP2 knockdown reduce the tumorigenicity of fibrosarcoma and salivary mucoepidermoid carcinoma, respectively. To test the model that 5MP promotes tumorigenicity through enhancing ATF4 expression, we examined correlation between eIF5 or 5MP expression and that of ATF4 target genes, using cancer genomics database. 5MP2 and eIF5 approximately correlated with the same subset of ATF4 targets in certain cancer types, but 5MP1 correlated with more ATF4 targets in more cancer types. These results not only confirm that eIF5 and 5MP promote tumorigenesis through up-regulating ATF4, but also suggest that 5MP1 has a greater role in cancer by unknown mechanism. Related to this point, we found a good correlation between 5MP1 and c-Myc expression in most types of cancers, and moreover c-Myc appears to be physically associated with 5MP1 promoters. Furthermore, in breast cancer high levels of 5MP1 are associated with poor prognosis, whereas high eIF5 levels correlate with more positive clinical outcomes. These results together suggest that, although up-regulation of ATF4 by eIF5 or 5MP is important, 5MP1 specially may play a major role in c-Myc-driven tumors, wherein a wider variety of ATF4 target genes are activated through 5MP1-ATF4 axis. The contrasting roles of 5MP1 and eIF5 in patient prognosis and accurate initiation suggests that suppression of non-AUG initiation may favor carcinogenesis. Collectively, future studies are warranted to establish the role of 5MP1 in cancer. Citation Format: Chelsea Moore, Sarah Gillaspie, Ji Wan, Eric Aube, Abbey Anderson, Chingakham Singh, Michael Witcher, Ivan Topisirovic, Shu-Bing Qian, Katsura Asano. Role of eIF5-mimic protein 1 (5MP1) for translational control in cancer. [abstract]. In: Proceedings of the AACR Special Conference on Translational Control of Cancer: A New Frontier in Cancer Biology and Therapy; 2016 Oct 27-30; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2017;77(6 Suppl):Abstract nr A12.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".