Mass Spectrometry-Based Profiling of Histone Post-Translational Modifications in Uveal Melanoma Tissues, Human Melanocytes, and Uveal Melanoma Cell Lines – A Pilot Study
Bibliographic record
Abstract
Purpose: Epigenetic alterations in uveal melanoma (UM) are still neither well characterized, nor understood. In this pilot study, we sought to provide a deeper insight into the possible role of epigenetic alterations in the pathogenesis of UM and their potential prognostic relevance. To this aim, we comprehensively profiled histone post-translational modifications (PTMs), which represent epigenetic features regulating chromatin accessibility and gene transcription, in UM formalin-fixed paraffin-embedded (FFPE) tissues, control tissues, UM cell lines, and healthy melanocytes. Methods: FFPE tissues of UM (n = 24), normal choroid (n = 4), human UM cell lines (n = 7), skin melanocytes (n = 6), and uveal melanocytes (n = 2) were analyzed through a quantitative liquid chromatography-mass spectrometry (LC-MS) approach. Results: Hierarchical clustering showed a clear separation with several histone PTMs that changed significantly in a tumor compared to normal samples, in both tissues and cell lines. In addition, several acetylations and H4K20me1 showed lower levels in BAP1 mutant tumors. Some of these changes were also observed when we compared GNA11 mutant tumors with GNAQ tumors. The epigenetic profiling of cell lines revealed that the UM cell lines MP65 and UPMM1 have a histone PTM pattern closer to the primary tissues than the other cell lines analyzed. Conclusions: Our results suggest the existence of different histone PTM patterns that may be important for diagnosis and prognosis in UM. However, further analyses are needed to confirm these findings in a larger cohort. The epigenetic characterization of a panel of UM cell lines suggested which cellular models are more suitable for epigenetic investigations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".