Spatially mapping the single-cell immune landscapes of melanoma brain metastases using imaging mass cytometry.
Bibliographic record
Abstract
e21517 Background: Up to 60% of metastatic melanoma patients develop brain metastases, and 5% develop leptomeningeal disease (LD), which presents with the worst prognosis of any melanoma brain metastasis (MBM) infiltration pattern. Median survival duration for MBM is ~12 months, however for LD patients it can be < 10 weeks. The spatial immune landscape of MBM with and without LD remains poorly understood. Methods: To spatially characterize the tumor microenvironment (TME) of MBM, we performed CyTOF Imaging Mass Cytometry (CyTOF-IMC) on a highly multiplexed panel of 35 antibodies for 21 MBMs (13 with LD, 8 without LD). We performed a novel cell segmentation, cell type assignment and identification approach to identify cell lineages to spatially characterize the TME of MBMs, segmenting and classifying 130,000 cells into 19 cell types. Results: We found enrichment of dendritic cells in the direct neighbourhood of melanoma cells of patients with LD (p = 0.019) and trends towards elevation of anti-tumoral monocyte populations in the TME of patients without LD. To investigate survival outcomes, we divided our cohort into long (≥365days) and short-survivors ( < 365 days), and found significant elevation of anti-tumoral T-cell populations (Total T-cells, CD8+ T-cells, CD4+ T-cells and CD3+CD4-CD8- T-cells, p < 0.05), and closer proximity of T-cells (CD8+ & CD4+ T-cells) to melanoma cells (p < 0.05). Survival analysis using median cell-proportion for each T-cell subset showed statistically significant (p < 0.05) survival differences between patients with high and low cell-proportions of CD8+ T-cells and CD4+ T-cells, with similar trends observed for a subset of patients (n = 13) with LD and a subset of patients treated with ICIs (n = 10), and results were confirmed by a Cox Regression Model. Cellular neighborhood (CN) analysis was performed generating N = 12 stable CNs. We found patients with higher proportions of CN9 (M1-like-microglia/M2-like-microglia/melanoma), CN10 (M1-like-macrophages/M2-like-macrophages/melanoma) and CN12 (Cytotoxic-T-cells/Helper-T-cells/melanoma) was associated with longer overall survival after diagnosis with MBM (p < 0.01). Conclusions: Proportion and proximity of anti-tumoral monocyte and T-cell populations may play a key role in modulating tumor response and overall survival for patients with MBM, including for patients with LD or for patients treated with ICIs.
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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 | 0.001 | 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".