Abstract 4657: Investigating the role of circulating bone cells in melanoma patients on immune checkpoint inhibitor therapy
Bibliographic record
Abstract
Abstract Bone metastasis is a frequent progression of metastatic melanoma affecting 20-40% of patients with metastatic melanoma. While immune checkpoint inhibitors have been revolutionary in the treatment of advanced melanoma, certain patient populations do not respond to immunotherapy. Clinical data from our own treated melanoma population at the MUHC has shown that patients with bone metastases respond poorly to immune checkpoint inhibitors and have worse outcomes when compared to patients without bone metastases. These findings have prompted the investigation into this observed phenomenon of treatment resistance. The bone microenvironment is known to be a key player in cancer progression and metastasis and has been shown to form a vicious cycle where cancer and bone cells interact symbiotically to promote tumor growth and enhance bone degradation. Bone cells that are released into the circulation during the dynamic process of bone metastasis can easily interact with immune cells and may disrupt the ability of the immune system to mount an effective anti-cancer response. In our cohort of 185 metastatic melanoma patients treated with immune checkpoint inhibitors, patients with bone metastasis have a 43% response rate versus 65% in patients with visceral metastases alone. In terms of the complete response (CR) rate, only 18% of patients with bone metastasis achieved a complete response compared to 52% of patients with visceral metastasis alone. The treatment resistance appears to be systemic in patients with bone metastasis; the response rate in lesions outside the bone is also reduced. In a subset of these patients with serial prospective blood collections, we profiled PBMCs to identify certain immune and bone cell populations in the circulation at a pre-treatment baseline, early on treatment 2-3 cycles and after 4-6 cycles depending on the regimen. Patients were grouped based on objective response to determine the relationship between clinical outcome and immune/bone cell profiles. Patients with bone metastasis and a poor response had reduced immune effector cells and increased osteocalcin positive bone cells in the circulation when compared to patients that achieved partial and complete responses. Immune and bone cell profiling is a novel method of evaluating melanoma patients undergoing immunotherapy and may serve as an effective predictor of response to immune checkpoint inhibitors. Citation Format: Nicholas Rozza, Catalin Mihalcioiu, Richard Kremer. Investigating the role of circulating bone cells in melanoma patients on immune checkpoint inhibitor therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4657.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".