Proteomics and phosphoproteomics profiling of the co-formulation of type I and II interferons, HeberFERON, in the glioblastoma-derived cell line U-87 MG
Bibliographic record
Abstract
Abstract HeberFERON is a co-formulation of Interferon (IFN)-α2b and IFN-γ in synergic proportions, with a demonstrated effect on skin cancer and other solid tumors. It has antiproliferative effects over glioblastoma multiform (GBM) clones and cell lines in culture, including U-87 MG. Omics studies in U-87 MG showed distinctive expression patterns compared to individual IFNs. Kinase signaling pathways dysregulation can also contribute to HeberFERON effects. Here, we report the first label-free quantitative proteomic and phosphoproteomic analyses to evaluate changes induced by HeberFERON after 72h incubation of U-87 MG cell line. LC-MS/MS analysis identified 7627 proteins with a fold change >2 (p<0.05); 122 and 211 were down- and up-regulated by HeberFERON, respectively. We identified 23549 peptides (5692 proteins) and 8900 phosphopeptides, 412 of these phosphopeptides (359 proteins) were differentially modified with fold change >2 (p<0.05). Proteomic enrichment analysis showed IFN signaling and its control, together to direct and indirect antiviral mechanisms were the main modulated processes. Enrichment analysis of phosphoproteome pointed to the cell cycle, cytoskeleton organization, translation and RNA splicing, autophagy, and DNA repair as biological processes represented. There is a high interconnection of phosphoproteins in a molecular network, where mTOR occupies a centric hub. HeberFERON regulates many phosphosites newly reported or with no clear association to kinases. Of interest is phosphosites increasing phosphorylation were mainly modified by CDK and ERK kinases, thus new cascades regulations can be determining the antiproliferation outcome. Our results contribute to a better mechanistic understanding of HeberFERON in the context of GBM. Significance of the Study HeberFERON is a co-formulation of IFN-α2b and -γ in synergic proportion, registered for skin basal cell carcinoma treatment, also demonstrating clinical effect over solid tumors, including GBM. GBM is a very lethal tumor, protected by the blood-brain barrier (BBB), highly mutated in proliferative signaling pathways with little treatment success. Interferons have been widely used in cancer; they pass BBB and act at JAK/STAT, PI3K/AKT/mTOR, and MAPKs cascades. We observed antiproliferative effects over GBM clones and cell lines in culture. U-87 MG is used as a model to understand the HeberFERON mechanism of action in GBM. We completed the first proteomic and label-free quantitative phosphoproteomic analysis after incubation of U-87 MG cell line with HeberFERON for 72h. The main contribution of this article is the description of phosphosites regulated in proteins participating in cell cycle, cytoskeleton organization, translation, autophagy, and DNA repair in a highly interconnected molecular network, where mTOR occupies a centric hub. Together with reported phosphosites, we described new ones and others with no associated kinases. Increased phosphorylation is mainly accounted by CDK and ERK kinases pointing to possibly new cascades regulations. This knowledge will contribute to the functional understanding of HeberFERON in GBM joined to general regulatory mechanisms in cancer cells.
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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 | 0.000 | 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 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".