SBI-0640756 Attenuates the Growth of Clinically Unresponsive Melanomas by Disrupting the eIF4F Translation Initiation Complex
Bibliographic record
Abstract
Disrupting the eukaryotic translation initiation factor 4F (eIF4F) complex offers an appealing strategy to potentiate the effectiveness of existing cancer therapies and to overcome resistance to drugs such as BRAF inhibitors (BRAFi). Here, we identified and characterized the small molecule SBI-0640756 (SBI-756), a first-in-class inhibitor that targets eIF4G1 and disrupts the eIF4F complex. SBI-756 impaired the eIF4F complex assembly independently of mTOR and attenuated growth of BRAF-resistant and BRAF-independent melanomas. SBI-756 also suppressed AKT and NF-κB signaling, but small-molecule derivatives were identified that only marginally affected these pathways while still inhibiting eIF4F complex formation and melanoma growth, illustrating the potential for further structural and functional manipulation of SBI-756 as a drug lead. In the gene expression signature patterns elicited by SBI-756, DNA damage, and cell-cycle regulatory factors were prominent, with mutations in melanoma cells affecting these pathways conferring drug resistance. SBI-756 inhibited the growth of NRAS, BRAF, and NF1-mutant melanomas in vitro and delayed the onset and reduced the incidence of Nras/Ink4a melanomas in vivo. Furthermore, combining SBI-756 and a BRAFi attenuated the formation of BRAFi-resistant human tumors. Taken together, our findings show how SBI-756 abrogates the growth of BRAF-independent and BRAFi-resistant melanomas, offering a preclinical rationale to evaluate its antitumor effects in other cancers.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".