Elevated<i>ARG1</i>expression in primary monocytes-derived macrophages as a predictor of radiation-induced acute skin toxicities in early breast cancer patients
Bibliographic record
Abstract
Radiation therapy (RT) the front-line treatment after surgery for early breast cancer patients is associated with acute skin toxicities in at least 40% of treated patients. Monocyte-derived macrophages are polarized into functionally distinct (M1 or M2) activated phenotypes at injury sites by specific systemic cytokines known to play a key role in the transition between damage and repair in irradiated tissues. The role of M1 and M2 macrophages in RT-induced acute skin toxicities remains to be defined. We investigated the potential value of M1 and M2 macrophages as predictive factors of RT-induced skin toxicities in early breast cancer patients treated with adjuvant RT after lumpectomy. Blood samples collected from patients enrolled in a prospective clinical study (n = 49) were analyzed at baseline and after the first delivered 2Gy RT dose. We designed an ex vivo culture system to differentiate patient blood monocytes into macrophages and treated them with M1 or M2-inducing cytokines before quantitative analysis of their "M1/M2" activation markers, iNOS, Arg1, and TGFß1. Statistical analysis was performed to correlate experimental data to clinical assessment of acute skin toxicity using Common Toxicity Criteria (CTC) grade for objective evaluation of skin reactions. Increased ARG1 mRNA significantly correlated with higher grades of erythema, moist desquamation, and CTC grade. Multivariate analysis revealed that increased ARG1 expression in macrophages after a single RT dose was an independent prognostic factor of erythema (p = 0 .032), moist desquamation (p = 0 .027), and CTC grade (p = 0 .056). Interestingly, multivariate analysis of ARG1 mRNA expression in macrophages stimulated with IL-4 also revealed independent prognostic value for predicting acute RT-induced toxicity factors, erythema (p = 0 .069), moist desquamation (p = 0 .037), and CTC grade (p = 0 .046). To conclude, our findings underline for the first time the biological significance of increased ARG1 mRNA levels as an early independent predictive biomarker of RT-induced acute skin toxicities.
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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) | 0.001 | 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".