Abstract 1184: Clonal evolution of diffuse intrinsic pontine glioma
Bibliographic record
Abstract
Abstract Diffuse intrinsic pontine gliomas (DIPG) are devastating tumours arising in the pons of children. Despite collaborative efforts, patient prognosis remains dismal with a median survival of 10 months and a 2+ year survival at ~5%. Previous efforts have identified the genetic drivers of DIPG revealing recurrent K27M mutations in histone H3 HIST1H3B or variant H3F3A which have been shown to dysregulate global lysine K27 methylation patterns of the tumour. Additional genetic hits including those in P53 and ACVR1 have also been identified. Previously, we showed that these driver mutations were conserved across all sites of DIPG dissemination, while secondary genetic hits showed subclonal enrichment. Here, we aim to investigate how DIPGs evolve with respect to both genetic (SNVs, CNVs) and non-genetic (epigenetics and transcriptomic) factors. We hypothesized that the genetic evolution of the disease will interplay with both the tumour's epigenetic changes and RNA expression to better explain DIPG development. To date, we have collected a total of 43 samples (range 3-12) from both the primary and disseminated site of 7 DIPG samples with matched normal brain. All samples have been subjected to whole exome sequencing, whole transcriptome sequencing (RNAseq) and MethylationEPIC analysis. The mutation burden across the samples ranged from 1.8-4.7 SNVs/Mb, with the exclusion of 4 sample locations that had acquired a hypermutant phenotype (range: 7.3-36.4 SNVs/Mb). Histone H3 mutations were the most frequent, being detected across all sampling locations in 6 of the 7 patients (5 in H3F3A and 1 in HIST1H3B). P53 mutations or LOH were detected in 4 patients, all of which also harboured a H3F3A mutation. No ACVR1 mutations were detected in this dataset. The final patient harboured MYCN, MYC-PVT1, and ID2 amplifications consistent with the MYCN subtype of DIPG. Clonal evolution analysis revealed distinct tumour heterogeneity in 6/7 samples, with the MYCN driven tumour appearing homogenous throughout all disseminated sites. In the remaining 6 samples, an average of 5 clones (range 4-11) were identified. H3F3A, HIST1H3B and P53 mutations were universally observed in the truncal clone of tumours and maintained throughout all sampling sites. Events driving subclones included PDGFRA amplification, MET amplification, PTEN loss, PIK3R1 mutations and hypermutant driving POLE and POLH mutations. Our preliminary work here provides insight into the genetic evolution of DIPGs. This work suggests that DIPG are heterogeneous in their development, but maintain homogeneity of the key tumour driver events throughout dissemination. However, due to the strong therapeutic potential of subclonal events described here, it remains important that the tumour's genetic complexity is not underestimated. Future goals looks to integrate both epigenetic and transcriptomic data into the evolution of DIPG to provide a clear and concise roadmap of how these tumours develop. Citation Format: Scott T. Ryall, Robert Siddaway, Arun Ramani, Andrei Turinsky, Michael Brudno, Cynthia Hawkins. Clonal evolution of diffuse intrinsic pontine glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1184.
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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 | 0.000 |
| 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) | 0.002 | 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".