Abstract 1445: Integrative genomics identifies actionable targets for therapy in medulloblastoma subgroups
Bibliographic record
Abstract
Abstract The application of high-resolution genomics to the study of medulloblastoma has recently led to a significant enhancement in our understanding of its pathogenesis, implicating new genes and gene families, previously uncharacterized molecular processes, and the existence of distinct biological subgroups: WNT, SHH, Group 3, and Group 4. Despite these advances, few genomic studies have profiled sufficient cases to identify recurrent genetic events, including those restricted to a particular molecular subgroup, making it difficult to discriminate driver genes from passengers. To specifically address these issues we have performed a comprehensive genome-wide copy number analysis of 1,250 frozen primary medulloblastomas and summarized their genomes by medulloblastoma subgroup using Affymetrix SNP6 arrays and a custom nanoString expression assay. Significant regions of interest were verified and validated both within the MAGIC cohort and in non-overlapping samples using a combination of FISH and a custom nanoString copy number assay. The most prevalent oncogenic events observed in medulloblastoma included those targeting known oncogenes and tumor suppressors such as members of the MYC family (MYCN, MYC, and MYCL1), cell cycle regulators (CCND2 and CDK6), genes involved in RTK/PI3K/mTOR signaling (PDGFRA, IRS2, PTEN, and TSC1), and components of the SHH pathway (GLI2 and PTCH1). Integration of our copy number data with nanoString results allowed for subgroup-specific genomic analyses and the identification of multiple novel candidates that appear to be targeted in a subgroup-restricted manner. Significant focal copy number aberrations affecting the chemokine receptor CXCR4 and candidate breast cancer oncogenes LMO4 and BCAS3 were revealed in SHH medulloblastoma, providing insight into novel pathways that likely cooperate with canonical SHH signaling in this subgroup. Similarly, we identified novel genetic events restricted to the poor prognosis Group 3 and Group 4 medulloblastomas, including recurrent high-level amplification of members of the TGFβ pathway (ACVR2A and ACVR2B) in Group 3 and apparent deregulation of the RB pathway (RB1, CCND2, and CDK6) in Group 4. Definitive elucidation of the genetic events contributing to the initiation, maintenance, and progression of medulloblastoma will be an essential prerequisite for the future development of rationally designed targeted therapies. Our current study of >1,200 medulloblastoma genomes has shown that medulloblastoma subgroups exhibit distinct genomics, and implicated novel actionable genes within the subgroups that may serve as attractive targets for future therapy. Prospective functional validation of our findings and the development of appropriate preclinical models faithfully recapitulating the genetics we have observed in subgroups of the human disease will be necessary for advances in the treatment of medulloblastoma. 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 1445. doi:1538-7445.AM2012-1445
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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) | 0.002 | 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".