Abstract 4872: ICGC PedBrain Tumor - Next-generation sequencing identifies novel subgroup-specific mutations and copy number aberrations in medulloblastoma
Bibliographic record
Abstract
Abstract Introduction: The International Cancer Genome Consortium (ICGC) is a worldwide network aiming to provide comprehensive molecular genetic profiles of 50 clinically and societally important tumors. A major focus of the ICGC PedBrain Tumor project is medulloblastoma (MB) - the most common malignant brain tumor in childhood. Importantly, recent work has shown that MB is not a single disease, but is in fact comprised of 4 distinct molecular subgroups (WNT, SHH, Group 3, Group 4). Using an integrative next-generation sequencing-based approach, we have investigated tumorigenic events underlying medulloblastoma, with the aim of identifying novel diagnostic or prognostic markers, and therapeutic targets. Methods: The whole genome of 50 tumor-normal DNA pairs, plus the whole exome or 2,500 target genes in a further 100 sample pairs from different histological and transcriptomic subgroups, was sequenced on an Illumina HiSeq platform. Sequencing-based high-resolution copy-number data was also generated for all cases. Results: Overall, a smaller number of non-synonymous somatic mutations was seen than in most adult malignancies. The number of somatic changes also clearly showed a positive correlation with patient age, suggesting either longer-term selection for more weakly transforming alterations, or the acquisition of additional passenger mutations in tumors which grew over a longer period. Whilst some point mutations and small InDels affected known MB or cancer-related genes (e.g. CTNNB1, PTCH1, MLL2), the vast majority were in genes which have not previously been implicated in medulloblastoma. Furthermore, even the most recurrently altered genes were mutated in <20% of samples overall, although several showed a clear enrichment in distinct subgroups. Pathway analysis revealed chromatin modification as one of the most frequently altered cellular processes, with hits in multiple pathway members. Novel copy-number alterations were also identified. For example, a pattern of catastrophic chromosome shattering (‘chromothripsis’) was observed almost exclusively in the SHH tumor subgroup. Conclusion: Next-generation sequencing of this large tumor cohort has provided a number of new insights into this deadly pediatric tumor. The overriding pattern is one of enormous heterogeneity, but integration with molecular subgrouping shows clear enrichment of certain alterations. This first stage of the ICGC PedBrain project has demonstrated the power of next-gen sequencing approaches to reveal significant new insights, providing a number of novel targets for potential therapeutic intervention. It also, however, indicates the importance of personalised approaches to treatment optimisation, and shows the scale of the coming challenge in terms of functionally validating the huge number of novel mutations. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4872. doi:1538-7445.AM2012-4872
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".