Proteomics and Phospho-Proteomics Profiling of the Co-Formulation of Type I and II Interferons, HeberFERON, in the Glioblastoma-Derived Cell Line U-87 MG
Bibliographic record
Abstract
HeberFERON, a co-formulation of Interferon (IFN)-α2b and IFN-γ, has effects on skin cancer and other solid tumors. It has antiproliferative effects over glioblastoma multiform (GBM) clones and cultured cell lines, including U-87 MG. Here, we report the first label-free quantitative proteomic and phospho-proteomic analyses to evaluate changes induced by HeberFERON after 72 h incubation of U-87 MG that can explain the effect on cellular proliferation. LC-MS/MS, functional enrichment and networking analysis were performed. We identified 7627 proteins; 122 and 211 were down- and up-regulated by HeberFERON (fold change > 2; p < 0.05), respectively. We identified 23,549 peptides (5692 proteins) and 8900 phospho-peptides; 523 of these phospho-peptides (359 proteins) were differentially modified. Proteomic enrichment showed IFN signaling and its control, direct and indirect antiviral mechanisms were the main modulated processes. Phospho-proteome enrichment displayed the cell cycle as one of the most commonly targeted events together with cytoskeleton organization; translation/RNA splicing, autophagy and DNA repair, as represented biological processes. There is a high interconnection of phosphoproteins in a molecular network; mTOR occupies a centric hub with interactions with translation machinery, cytoskeleton and autophagy components. Novel phosphosites and others with unknown biological functionality in key players in the aforementioned processes were regulated by HeberFERON and involved CDK and ERK kinases. These findings open new experimental hypotheses regarding HeberFERON action. The results obtained contribute to a better understanding of HeberFERON effector mechanisms in the context of GBM treatment.
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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 | 0.000 | 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".