Abstract A18: Uncovering molecular subgroups and a novel cancer driver, ACVR1, in diffuse intrinsic pontine gliomas
Bibliographic record
Abstract
Abstract Diffuse intrinsic pontine glioma (DIPG) is a devastating paediatric brain tumor with no effective therapy and near 100% fatality. The failure of most therapies can be attributed to the delicate location of these tumors and choosing therapies based on assumptions that DIPGs are molecularly similar to adult disease. Recent studies have unravelled the unique genetic make-up of this brain cancer with nearly 80% harbouring a K27M-H3.3 or K27M-H3.1 mutation. However, DIPGs are still thought of as one disease with limited understanding of the genetic drivers of these tumors. Here we apply methylation profiling, whole genome sequencing, expression profiling, and copy number analysis to discover that DIPGs are three molecularly distinct subgroups (H3-K27M, Silent, and MYCN) and uncover a mutations in a novel driver, ACVR1 in 20% of DIPGs. Mutations in ACVR1 were constitutively activating, leading to SMAD phosphorylation and increased expression of downstream activin signalling targets ID1 and ID2. The MYCN subgroup is not associated with histone mutations and is instead characterized by hypermethylation and chromothripsis of chromosome 2p with high-level amplifications of MYCN, ID2, and KIDINS220. The Silent subgroup affects younger children, has genomes with minimal genomic instability and fewer mutations, over-expresses WNT pathway genes, as well as genes with known cancer association such as MDM2, MSMP and ADAM33. The H3-K27M subgroup is highly K27M-H3 mutated and associated with additional hits including activating mutations in ACVR1, frequent RB1 and TP53 deletions, PVT-1/MYC or PDGFRA gains/amplifications, genomic instability and alternative lengthening of telomeres. Our results show that this seemingly homogeneous entity in fact comprises three distinct subgroups with different demographic and molecular features. This complexity needs to be considered when designing new therapeutic approaches in order to improve outcome for these children. Citation Format: Pawel Buczkowicz, Christine Hoeman, Patricia Rakopoulos, Sanja Pajovic, Andrew Morrison, Eric Bouffet, Ute Bartels, Oren Becher, Cynthia Hawkins. Uncovering molecular subgroups and a novel cancer driver, ACVR1, in diffuse intrinsic pontine gliomas. [abstract]. In: Proceedings of the AACR Special Conference on Pediatric Cancer at the Crossroads: Translating Discovery into Improved Outcomes; Nov 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;74(20 Suppl):Abstract nr A18.
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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".