Designer Frankenproteins That Halt the Proliferation of Myc-Driven Cancer Cells
Bibliographic record
Abstract
Abstract Overexpression of the proto-oncogene MYC occurs in >70% of cancers and is especially prevalent in breast cancer. Myc partners with transcription factor Max to bind to the E-box DNA response element. By patterning our frankenproteins on the basic region/helix–loop–helix/leucine zipper motif of Max, we designed MEF and MEF/C93 to bind to the E-box. In bacterial one-hybrid assays and quantitative electrophoretic mobility shift assay, both proteins bound specifically to the E-box with high sequence-specificity and affinity (Kd = 8 nM) rivaling native transcription factors. Quantitative PCR revealed that MEF and MEF/C93 selectively downregulated Myc target genes in Myc-dependent MDA-MB-231 breast cancer cells, but not in Myc-independent MCF-7 cells. Fluorescence colocalization demonstrated transport into cell nuclei. Our proteins displayed IC50 values of 1–2 μM in cell viability assays in MDA-MB-231, compared with ∼25 μM in MCF-7. These results demonstrate the specificity of targeting Myc-dependent cancer cells and mark significant progress toward protein-based therapies aimed at Myc-driven cancers.
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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 | 0.001 |
| 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".