LGG-03. Revealing MAPK-Activated Immune-Suppressive Myeloid Populations in Pediatric Low-Grade Gliomas Through Spatial Immune Mapping
Bibliographic record
Abstract
Abstract Pediatric low-grade gliomas (pLGG), the most common brain tumors in children, remain a significant cause of morbidity. Therefore, novel therapeutic strategies are urgently needed. Although some studies have characterized the tumor microenvironment (TME) of pLGG using bulk and/or single-cell RNA sequencing, little is known about the spatial proteomic architecture of pLGG and its relationship to clinico-molecular features. Our study utilized imaging mass cytometry and a panel of 28 metal-labeled antibodies to unravel the spatial organization of 120 primary pLGG samples from the LOGGIC Core BioClinical DataBank. Cellular neighborhood analysis mapped the spatial organization of pLGG TME and several clinical features (entity, tumor location, disease progression status, age and sex) were used to measure their putative association with the enrichment of key cell populations and structures. Here, we revealed myeloid cells - comprising resident microglia and diverse bone marrow-derived macrophages - as the predominant immune population in the TME, notably in optic pathway tumors, alongside limited T-lymphoid infiltrates. Importantly, we identified an immunophenotype signature based on the presence of myeloid cell populations that was significantly associated with disease progression in our cohort. Clinically, the myeloid cell populations, together with an increased expression of the immune checkpoint protein TIM-3, suggest the presence of an immunosuppressive environment. Notably, p-ERK positivity was high in the myeloid populations, indicating a possible link between TIM-3 and MAPK activity in myeloid cells. Spatial analysis unveiled intriguing cell interactions, including noteworthy myeloid interactions, and specific cellular neighborhoods consistently associated with progression-free survival (PFS) in all patients, and particularly those at risk of progression. Our study, the largest on pLGG TME to date, highlights the immunosuppressive role of diverse myeloid infiltrates and suggests combining TIM-3 with MAPK inhibition as a promising therapeutic strategy targeting both the TME and oncogenic MAPK activation in these debilitating tumors.
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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 | 0.001 |
| 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 | 0.001 |
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".