Abstract 610: Short peptides for targeted apoptosis in cancer cells: development & evaluation of therapeutic applications.
Bibliographic record
Abstract
Abstract The ING proteins are type II tumor suppressors that are involved in the regulation of gene transcription, DNA repair, cellular senescence, tumorigenesis and apoptosis. Inactivation of apoptosis pathways is frequently observed in cancer cells, and it leads to a drastic decrease in the efficiency of available cancer treatments. Inactivation of INGs during the suppression of apoptosis tumors and greater sensitivity of cancer versus normal cells to the elevation of ING1 levels suggest that the INGs could serve as viable targets for cancer therapy. In this study we expand our previous observations that all ING proteins share a conserved sequence domain, the Lamin Interacting Domain (LID), which is unique to INGs in the human proteome. The overexpression of a recombinant peptide containing multiple fragments of the LID domain was previously shown to induce apoptosis in a rapid and efficient way in several cancer cell line models. Together, rather limited knowledge of the molecular mechanisms that mediated these apoptosis-inducing effects and the large size of the recombinant LID peptide precluded use of the LID for therapeutic purposes. Here we define the minimal portion of the LID domain that is capable of efficiently inducing apoptosis, and devise approaches to efficiently introduce it into cancer cells where we predict it will show a good therapeutic index by virtue of inducing apoptosis in cancer cells much more efficiently than in normal surrounding cells. Our preliminary in silico analysis of the LID protein structure indicated that LID peptides could interfere with several “master regulators” of cell cycle control and apoptosis, including Retinoblastoma and SMAC proteins. Overexpression of LID peptides could also interfere with the formation of functional ING1-HDAC chromatin modifying protein complexes by disrupting ING1-Lamin A interactions, thus leading to the loss of HDAC targeting and apoptosis. Our ongoing studies should help to identify the molecular mechanism(s) of LID-mediated apoptosis induction and identify the minimal required sequence of LID peptide that still displays potent apoptosis-inducing activity against tumor cells. Our long term goal is to further expand current understanding of apoptosis pathways and develop LID-based therapeutic for the selective induction of apoptosis in cancer cells. Citation Format: Oleksandr Boyko, Karl T. Riabowol. Short peptides for targeted apoptosis in cancer cells: development & evaluation of therapeutic applications. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 610. doi:10.1158/1538-7445.AM2013-610
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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) | 0.001 | 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) | 0.002 | 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".