Abstract A24: Characterizing a novel “Minimalist Hybrid Protein” inhibitor designed to target Myc activity in cancer
Bibliographic record
Abstract
Abstract When deregulated, the c-Myc oncoprotein plays a key role in the development and progression of over 50% of all human cancers. As such, innovative and effective therapeutics are urgently needed to improve the treatment and survival of cancer patients, and we believe that directly modulating the activity of Myc would fill this important gap. Recent studies using a dominant negative protein, Omomyc, have provided evidence regarding the therapeutic value of inhibiting Myc activity in cancer. Specifically, perturbing Myc activity in vivo eradicates tumors without irreversible damage to normal cells, as demonstrated in mouse models of cancer. Using a similar yet novel strategy, we have generated a minimalist hybrid protein inhibitor known as MaxE47 (ME47), which is composed of the subdomains of different b-HLH-LZ and b-HLH transcription factor families. ME47 is designed to act as a competitive inhibitor of DNA E-box binding by the Myc/Max heterodimer. We hypothesize that ME47 can be used as a tool to better understand how best to interfere with oncogenic Myc and will lead to the development of Myc-targeted therapeutics. Using our prototype inhibitor, ME47, with Omomyc as a proof-of-concept control, we have established the cell systems and assays necessary to (1) evaluate the anti-cancer efficacy of our Minimalist Hybrid Proteins in human cancer cells, and (2) to determine their mechanism of action and specificity. Here we have demonstrated that ME47 significantly reduces anchorage-independent growth in soft agar and cell viability in tumor-derived breast cancer cell line MDA-MB-231, but not the non-transformed MCF10A breast cells. ME47 also significantly decreases tumor formation in xenograft mice. To begin to characterize the specificity and mechanism of action of ME47, luciferase reporter and chromatin immunoprecipitation assays were used to evaluate whether ME47 is Myc and/or E-box specific. Using luciferase reporter constructs fused to the promoters of established Myc target genes such as Nucleolin, we have also demonstrated that MaxE47 decreases the ability of Myc to activate target gene transcription. While this work is focused on the development of a Myc/Max E-box interaction inhibitor, Dr. Linda Penn's research group is also implementing BioID mass spectrometry to identify novel Myc interacting partners (see Penn lab abstract Dingar et al.). This work could potentially reveal new targets for a similar mode of disruptive inhibition, where a Minimalist Hybrid Protein designed to inhibit the association of the novel interacting partner and Myc would disrupt Myc activity. A direct inhibitor of Myc activity in cancer would re-define the field of Myc therapeutics and could develop into a valuable tool for personalized cancer medicine in those patients with deregulated Myc. The success we have had with our ME47 inhibitor suggests that we are progressing along the path to such an inhibitor, and we look forward to continuing our work with this inhibitor and other Minimalist Hybrid Proteins. Citation Format: K. Ashley Hickman, Lindsay C. Lustig, Dharmendra Dingar, Romina Ponzielli, Christina Bros, Warren W.C Chan, Jumi Shin, Linda J.Z Penn. Characterizing a novel “Minimalist Hybrid Protein” inhibitor designed to target Myc activity in cancer. [abstract]. In: Proceedings of the AACR Special Conference on Myc: From Biology to Therapy; Jan 7-10, 2015; La Jolla, CA. Philadelphia (PA): AACR; Mol Cancer Res 2015;13(10 Suppl):Abstract nr A24.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".