Systematic identification and characterization of the methyl proteome for cancer intervention
Bibliographic record
Abstract
M of Lys and Arg residues has emerged as a prevalent post-translational modification (PTM) occurring on numerous non-histone proteins, drastically extending its role beyond the known histone code. We have developed an approach that combines mass spectrometry with peptide arrays and bioinformatics to systematically identify protein methylation and quantify dynamic changes in the methylome associated with tumorigenesis or drug resistance. Our studies not only led to the identification of numerous novel methylation sites, but also generated new insights into how protein methylation regulates cellular functions such as DNA damage repair, apoptosis and drug resistance. With recent advances in mass spectrometry, the stage is now set to decode the methyl proteome and to elucidate, systematically, the mechanisms of interplay between histone and non-histone methylation and between methylation and other types of PTM for cancer diagnosis and intervention.
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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 | 0.000 |
| 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) | 0.000 | 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".