A GM-CSF and IL-4 Fusion Cytokine Triggers Conversion of B-Cells to Tumoricidal Effectors
Bibliographic record
Abstract
Abstract Abstract 1048 We have previously demonstrated that coupling of GMCSF at the N-terminus of common γ-chain interleukins IL2, IL15 and IL21 leads to meaningful gain-of function activity in interleukin-responsive lymphomyeloid cells. Considering the physiological and immunological importance of IL4 that is a member of γ-chain interleukins, we tested the bioactivity of a novel fusion cytokine consisting of a fusion between GM-CSF and IL-4 (GIFT4). We observed that GIFT4 leads to a pan-STAT hyper-phosphorylation response in resting splenic B-cells distinct from IL4 only and that treated B-cells up-regulated expression of MHCI/II, CD80 and CD86, secreted IL-12, IL-1a, IL-6, and substantial amounts of CCL3 and GM-CSF, akin to recently described innate response activator (IRA) B-cells (Science 335, 597, 2012). In vivo delivery of recombinant GIFT4 protein to normal mice leads to homeostatic expansion of splenic B cells and plasma cells as well as humoral hyper-responsiveness to antigenic challenge. We further showed that B16F0 melanoma cells engineered to secrete GIFT4 are immune-rejected in a B-cell dependent manner. The clinical effect was abolished when B16F0-GIFT4 cells were implanted in B-cell deficient μMT, CD4−/−, CD8−/− or FcγR−/− mice consistent with a pivotal for B cells, their T-cell helper function and antibody-dependent cell-mediated cytotoxicity for the observed melanoma-specific therapeutic effect. Thus, GIFT4 defines a novel engineered cytokine that mediates endogenous expansion of B-cells with potent immune helper and antigen-specific effector function. We propose that GIFT4 protein could serve as a novel immunotherapeutic agent and defines a previously unrecognized potential of B-cells as tumoricidal effectors. Disclosures: No relevant conflicts of interest to declare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".