Molecular Consequences of Proprotein Convertase 1/3 (PC1/3) Inhibition in Macrophages for Application to Cancer Immunotherapy: A Proteomic Study
Bibliographic record
Abstract
Macrophages provide the first line of host immune defense. Their activation triggers the secretion of pro-inflammatory cytokines and chemokines recruiting other immune cells. In cancer, macrophages present an M2 anti-inflammatory phenotype promoting tumor growth. In this way, strategies need to be develop to reactivate macrophages. Previously thought to be expressed only in cells with a neural/neuroendocrine phenotype, the proprotein convertase 1/3 has been shown to also be expressed in macrophages and regulated as a function of the Toll-like receptor immune response. Here, we investigated the intracellular impact of the down-regulation of the proprotein convertase 1/3 in NR8383 macrophages and confirmed the results on macrophages from PC1/3 deficient mice. A complete proteomic study of secretomes and intracellular proteins was undertaken and revealed that inhibition of proprotein convertase 1/3 orient macrophages toward an M1 activated phenotype. This phenotype is characterized by filopodial extensions, Toll-like receptor 4 MyD88-dependent signaling, calcium entry augmentation and the secretion of pro-inflammatory factors. In response to endotoxin/lipopolysaccharide, these intracellular modifications increased, and the secreted factors attracted naïve T helper lymphocytes to promote the cytotoxic response. Importantly, the application of these factors onto breast and ovarian cancer cells resulted in a decrease viability or resistance. Under inhibitory conditions using interleukin 10, PC1/3-knockdown macrophages continued to secrete inflammatory factors. These data indicate that targeted inhibition of proprotein convertase 1/3 could represent a novel type of immune therapy to reactivate intra-tumoral macrophages.
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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) | 0.001 | 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".