Continuous immune composition retains longitudinal information beyond coarse ecological-context labels in pediatric leukemia

Abstract Background Single-cell pediatric leukemia datasets capture substantial variation in cellular composition, but apparent ecological states can be confounded by leukemia lineage, project structure, annotation differences, malignant-cell composition, and compositional constraints. We developed a Bayesian framework to test whether harmonized single-cell-derived immune composition provides longitudinal information beyond coarse ecological-context labels in continuous-time Ornstein–Uhlenbeck (OU) models of a prespecified semiquantitative leukemia-state trajectory. Results We reprocessed two public Single-cell Pediatric Cancer Atlas (ScPCA) leukemia projects using common cell-type mapping and constructed a cross-project immune composition from T/natural-killer (TNK), B-lineage, and myeloid compartments. Among 104 compositionally eligible participants, coarse $$\:k=2$$ clustering was reproducible under bootstrap resampling and showed limited association with project or diagnosis. Within 99 B-cell acute lymphoblastic leukemia (B-ALL) participants, it separated 73 TNK-dominant and 26 B/Myeloid-shifted profiles with minimal project association. However, poor concordance between raw-composition and centered log-ratio-derived assignments indicated representation-sensitive context membership. We therefore evaluated continuous ecological composition separately from coarse context labels in a corrected longitudinal analysis of 34 participants contributing 241 observations and 207 transitions. Higher B-lineage composition was associated with a lower effective OU attractor $$\:\mu\:$$ in both B-only and B+myeloid models, whereas coarse context effects were unresolved. True leave-one-participant-out validation modestly favored B-only over OU-only in aggregate, but predictive differences were heterogeneous across participants; context-only and ecology-plus-context models provided no incremental advantage. A directionally consistent B-associated signal was observed in a secondary ordinal-state analysis. Simulations using observed irregular sampling schedules supported recovery of moderate ecological effects, while posterior-predictive analyses showed improved uncertainty calibration with continuous ecological composition. Conclusions Pediatric leukemia single-cell composition contains reproducible coarse immune structure, but stable clustering does not imply a longitudinally predictive ecological state. Continuous B-lineage composition retained more longitudinal information than discrete ecological-context labels, although its participant-level predictive contribution was modest. This framework distinguishes descriptive ecological coarse-graining from ecological covariates that add information to stochastic longitudinal models while avoiding interpretation of OU mean reversion as direct evidence of stabilizing selection or fixed leukemia ecotypes.

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Journal
BMC Bioinformatics
Published
2026-10-16
DOI
https://doi.org/10.1186/s12859-026-06679-7
Primary Topic
Single-cell and spatial transcriptomics
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article
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article

Continuous immune composition retains longitudinal information beyond coarse ecological-context labels in pediatric leukemia

Seung-Hwan Kim
BMC Bioinformatics
Single-cell and spatial transcriptomics
article

Continuous immune composition retains longitudinal information beyond coarse ecological-context labels in pediatric leukemia

Seung-Hwan Kim
article en

Abstract

Abstract Background Single-cell pediatric leukemia datasets capture substantial variation in cellular composition, but apparent ecological states can be confounded by leukemia lineage, project structure, annotation differences, malignant-cell composition, and compositional constraints. We developed a Bayesian framework to test whether harmonized single-cell-derived immune composition provides longitudinal information beyond coarse ecological-context labels in continuous-time Ornstein–Uhlenbeck (OU) models of a prespecified semiquantitative leukemia-state trajectory. Results We reprocessed two public Single-cell Pediatric Cancer Atlas (ScPCA) leukemia projects using common cell-type mapping and constructed a cross-project immune composition from T/natural-killer (TNK), B-lineage, and myeloid compartments. Among 104 compositionally eligible participants, coarse $$\:k=2$$ clustering was reproducible under bootstrap resampling and showed limited association with project or diagnosis. Within 99 B-cell acute lymphoblastic leukemia (B-ALL) participants, it separated 73 TNK-dominant and 26 B/Myeloid-shifted profiles with minimal project association. However, poor concordance between raw-composition and centered log-ratio-derived assignments indicated representation-sensitive context membership. We therefore evaluated continuous ecological composition separately from coarse context labels in a corrected longitudinal analysis of 34 participants contributing 241 observations and 207 transitions. Higher B-lineage composition was associated with a lower effective OU attractor $$\:\mu\:$$ in both B-only and B+myeloid models, whereas coarse context effects were unresolved. True leave-one-participant-out validation modestly favored B-only over OU-only in aggregate, but predictive differences were heterogeneous across participants; context-only and ecology-plus-context models provided no incremental advantage. A directionally consistent B-associated signal was observed in a secondary ordinal-state analysis. Simulations using observed irregular sampling schedules supported recovery of moderate ecological effects, while posterior-predictive analyses showed improved uncertainty calibration with continuous ecological composition. Conclusions Pediatric leukemia single-cell composition contains reproducible coarse immune structure, but stable clustering does not imply a longitudinally predictive ecological state. Continuous B-lineage composition retained more longitudinal information than discrete ecological-context labels, although its participant-level predictive contribution was modest. This framework distinguishes descriptive ecological coarse-graining from ecological covariates that add information to stochastic longitudinal models while avoiding interpretation of OU mean reversion as direct evidence of stabilizing selection or fixed leukemia ecotypes.

BMC Bioinformatics
Fisher College (US)
Good health and well-being
Openalex Percentile: Top 24%
Single-cell and spatial transcriptomics
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