Abstract A12: Identifying MYC post-translational modifications using a mass spectrometry-based approach
Bibliographic record
Abstract
Abstract MYC activity is regulated by a complex network of signaling cascades and protein interactions, some of which result in post-translation modifications (PTMs). For example, phosphorylation of the regulatory threonine 58 (T58) and serine 62 (S62) plays a pivotal role in regulating MYC stability and activity. Loss of this regulatory pathway in cancer can lead to MYC dysregulation and contribute to tumorigenesis. Despite their important role, the majority of MYC PTMs arising downstream of different signaling cascades and their consequences on regulating MYC activity remain largely unknown. To capture the broad spectrum of MYC PTMs, a mass spectrometry (MS)-based approach is being pursued to attain high sequence coverage and enable the identification of PTMs throughout the protein. MYC was overexpressed in the HEK293T cell line, immunoprecipitated, digested, and analyzed on the Velos Orbitrap MS. This analysis facilitated the identification of a range of MYC PTMs, including phosphorylation, sumoylation, ubiquitination and acetylation. Phosphorylation was readily detectable at residues T58 and S62, consistent with previous reports. Additionally, we also observed a previously reported phosphorylation cluster involving residues T343/S344/S347/S348, suggesting that these sites might play a role in regulating MYC function. Indeed, converting these residues to alanine to prevent phosphorylation resulted in a gain-of-function mutant (See Penn Lab poster Lorenco et al.). Another phosphorylation was observed mapping to residues S71 and/or S81. Mutating these sites to alanine also potentiated MYC transformation, highlighting the role of PTMs in regulating MYC function. A MYC sumoylation site was identified on lysine 326 (K326) and is subject of ongoing investigation (See Penn Lab poster Kalkat et al.). Additionally, we will discuss approaches presently underway to increase sequence coverage and identify additional MYC PTMs. PTMs play an important role in regulating the activity of transcription factors, including that of MYC. Moreover, PTMs can contribute to the dysregulation of its activity in cancer. Thus, mapping the array of PTMs in MYC, understanding their role in regulating MYC function, and elucidating the pathways that converge on these PTMs may pave the way for the development of novel therapeutic strategies aimed at targeting MYC-induced tumorigenesis. Citation Format: Diana Resetca, Manpreet Kalkat, Corey Lourenco, Pak-Kei Chan, Tharan Srikumar, Brian Raught, Linda Penn. Identifying MYC post-translational modifications using a mass spectrometry-based approach. [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 A12.
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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 | 0.001 |
| 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".