Abstract 3147: Stereotactic image-guided epigenome profiling reveals a neural stem cell evolutionary origin of diffuse gliomas
Bibliographic record
Abstract
Abstract Diffuse gliomas are malignant neoplasms originating in the parenchyma of the central nervous system whose cellular origin remains elusive. To determine the cellular and spatiotemporal origin of gliomas, we devised a three-dimensional reconstruction of tumor lineage. We used neuronavigation to acquire eight to twelve image-guided and spatially separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma, which we characterized using DNA methylation arrays. A total of 133 samples were obtained from regions with and without imaging abnormalities. Methylation profiles were analyzed to construct phyloepigenetic trees and subsequently projected on 3D image-derived tumor maps. Lineage analysis of these evolutionary trees indicated that the sampled gliomas largely evolved stochastically, suggesting that critical tumor drivers were acquired early in time. These results were further validated using 102 multi-region samples from 24 independent patients. Patristic (evolutionary) and cartesian (spatial) distances between pairs of tumor samples from the same patient demonstrated strong correlations, suggesting that this information could be used to determine trajectories of tumor evolution. Evolutionary and spatial distance metrics were combined with histologically obtained and computationally quantified cellularity and proliferation rates to model the direction and magnitude of tumor growth. In order to relate tumor lineage to brain anatomy we mapped patient imaging to a reference space (Montreal Neurological Institute, MNI). Samples mapping to regions of white matter were earlier in tumor lineage when compared to samples mapping to regions of gray matter, suggesting that white matter involvement is an early feature of tumor development. Samples early in tumor lineage were located closer to the ventricles when compared with samples late in lineage, suggesting that tumors grow outward from the ventricular lining. Finally, we used a tumor probability map constructed using imaging from over 500 unrelated patients to associate lineage to tumor probability. Results from this analysis indicated that periventricular areas of high tumor probability coincided with samples early in tumor lineage and cortical areas of low tumor probability coincided with samples late in tumor lineage. Taken together, our phylogeographic analysis of tumor development supports a neural progenitor cell-of-origin model, where neural stem cells in the subventricular zone of the lateral ventricles give rise to mature tumors. Citation Format: Floris P. Barthel, Niels Verburg, Russell Rockne, Roelant Eijgelaar, Kevin Anderson, Domenique Müller, Sergio Branciamore, Kevin C. Johnson, Pieter Wesseling, Philip C. de Witt Hamer, Roel G. Verhaak. Stereotactic image-guided epigenome profiling reveals a neural stem cell evolutionary origin of diffuse gliomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3147.
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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".