Dermatologic toxicity from novel therapy using antimicrobial peptide LL‐37 in melanoma: A detailed examination of the clinicopathologic features
Bibliographic record
Abstract
LL-37 is a naturally occurring 37-amino-acid peptide that is part of the innate immune system in human skin. Preclinical studies have showed that intra-tumoral injections of LL-37 stimulate the innate immune system by activation of plasmacytoid dendritic cells, which mediate tumor destruction. LL-37 intra-tumoral injections have been utilized in a phase 1 clinical trial for melanoma patients with cutaneous metastases. We report dermatologic toxicity in a 63-year-old woman with stage IIIC melanoma of the right calf and inguinal lymph nodes. She was previously treated with nivolumab and combination chemotherapy (cisplatin, vinblastine and dacarbazine) and subsequently treated with LL-37 injections upon progression of both prior regimens. She received a total of 8 weekly LL-37 injections, with interval clinical shrinkage of injected lesions. However, approximately 45 days after initiation of this therapy, she presented with multiple verrucous papules and a vesiculo-bullous lesion on the trunk and extremities. Clinically, most of these lesions were thought to be either squamous cell carcinoma or inflamed seborrheic keratosis. Histologically, 11 of the total 12 skin biopsies showed similar histopathologic features, with a prominent lichenoid inflammatory infiltrate admixed with eosinophils and an overlying atypical squamous epithelial proliferation with verrucous and keratoacanthoma-like features and varying degrees of keratinocytic atypia. Interestingly, a majority of the lesions did not show spongiosis (11/12). All lesions resolved within 2 months of cessation of LL-37 injection therapy. This case highlights adverse dermatological manifestations of LL-37 therapy, similar to the consequences of other novel therapies.
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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".