Isolation of specific and biologically active peptides that bind cells from patients with acute myeloid leukemia (AML)
Bibliographic record
Abstract
PURPOSE: In a departure from conventional strategies to improve treatment outcome for myeloid malignancies, we report the isolation of leukemia-specific peptides using a phage display library screened with freshly obtained human myeloid leukemia cells. RESULTS: A phage display library was screened by 5 rounds of biopanning with freshly isolated human AML cells. Individual colonies were randomly picked and after purification, biologic activity (growth and differentiation) on fresh AML cells was profiled. Ten peptides were synthesized for further biological studies. Multiple peptides were found to selectively bind to acute myeloid leukemia (AML) cells. The peptides bound to leukemia cells, were internalized and could induce proliferation and/or differentiation in the target patient cells. Two of the peptides, HP-A2 and HP-G7, appeared to have a novel mechanism of inducing differentiation since they did not cause G1 arrest in cycling cells even as the expression of the differentiation marker CD11b increased. CONCLUSION: Peptide induced differentiation of leukemia cells offers a novel treatment strategy for myeloid malignancies, whereas their ability to induce proliferation could be harnessed to make cells more sensitive to chemotherapy. Conceptually, these leukemia specific peptides can also be used to refine diagnosis, document minimal residual disease, and selectively deliver toxins to malignant cells.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".