Disruption of SND1–MTDH Interaction by a High Affinity Peptide Results in SND1 Degradation and Cytotoxicity to Breast Cancer Cells <i>In Vitro</i> and <i>In Vivo</i>
Bibliographic record
Abstract
Abstract Staphylococcal nuclease domain-containing protein 1 (SND1) is a multifunctional oncoprotein overexpressed in breast cancer. Binding of metadherin (MTDH) to SND1 results in the stabilization of SND1 and is important in the initiation and progression of breast cancer. Disruption of such interaction is a potential therapeutic for breast cancer. SN1/2 domain of SND1 was used as bait in a phage display screening to identify a 12-amino acid peptide 4-2. The activity of peptide 4-2 was evaluated by ELISA, coimmunoprecipitation, MTS, Western blot analysis, and xenograft mouse model. Peptide 4-2 could disrupt SND1–MTDH interaction. Cell penetrating derivative of peptide 4–2 (CPP-4–2) could penetrate and kill breast cancer cells by disrupting SND1–MTDH interaction and degrading SND1. Tryptophan 10 (W10) of peptide 4-2 was essential in mediating cytotoxicity, SND1 interaction, SND1–MTDH disruption, and SND1 degradation. CPP-4-2 could inhibit the growth of breast cancer in a xenograft mouse model. The SND1-interacting peptide 4-2 could kill breast cancer cells both in vitro and in vivo by interacting with SND1, disrupting SND1–MTDH interaction, and inducing SND1 degradation. W10 was an essential amino acid in the activity of peptide 4-2.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".