Abstract 2085: Targeting the translation initiation complex component eIF4G1 in melanoma
Bibliographic record
Abstract
Abstract The translation initiation factor 4F (eIF4F) complex assembly is a rate-limiting step in mRNA translation. eIF4F subunits including eIF4A, eIF4E, and eIF4G, are often upregulated in cancer and neurodegeneration diseases. Elevated eIF4F level/activity has been correlated with poor prognosis and drug resistance. Leveraging our findings with the small molecule SBI-756, which interacts with eIF4G1 and impairs eIF4F complex assembly, we set to map domains that are required for SBI-756 activity. A CRISPR screen using sgRNAs that target different sequences on eIF4G1 led to the identification of the MA3 domain, as a putative binding site for SBI-756. Deletion/mutation of the eIF4G1 MA3 domain attenuated melanoma cells and spheroids growth. Polysome profiling assays confirmed attenuated translation activity, which resembled those seen with SBI-756. In silico virtual screen identified 64 small molecules (out of >10 million) that interact with the MA3 domain. Of these, we have selected four that effectively attenuated melanoma growth in culture. Analogs developed for these four compounds were more potent in impairing the assembly of the eIF4F complex, inhibition of protein translation and the 2D and 3D growth of melanoma cells. RNA-sequencing analysis highlighted altered expression of genes implicated in apoptosis, UPR, cell cycle, and ROS pathways, leading us to test possible combination with pathways that may complement the above. Among those, autophagy inhibitors synergized with our lead compound, M19-6, resulting in efficient melanoma cell death, using notably lower concentrations of these inhibitors. Our findings identify the eIF4G1 MA3 domain as an important player in eIF4F assembly and a potential target for cancer therapy. Citation Format: Yongmei Feng, Mariia Radaeva, Hyungsoo Kim, Anagha Deshpande, Ani Deshpande, Predrag Jovanovic, Rabi Murad, Ivan Topisirovic, Steven Olson, Artem Cherkasov, Ze'ev Ronai. Targeting the translation initiation complex component eIF4G1 in melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2085.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".