Abstract 1430: Characterization of the medulloblastoma splice-ome reveals subgroup-specific changes in alternative splicing and isoform expression patterns
Bibliographic record
Abstract
Abstract Medulloblastoma candidate gene approaches have previously identified alternative splicing and isoform expression changes affecting genes critical for cerebellar development and medulloblastoma pathogenesis. Here we present a bioinformatic characterization of the medulloblastoma splice-ome in 103 primary tumors and 14 normal cerebella samples. Medulloblastomas display a statistically significant increase in alternative splicing relative to normal fetal cerebella (2.3-times; P<6.47E-8), with splicing patterns that are specific to each molecular subgroup. Unsupervised hierarchical clustering of alternatively spliced genes accurately assigns medulloblastomas to their correct subgroup. One-third of all medulloblastomas (n=26) display a ‘hyper-spliced’ phenotype, with median splicing levels four-times greater than non-hyperspliced tumors. Hyperspliced medulloblastomas show a relatively worse overall survival (P<3.08E-2), and are seen across all molecular subgroups. Our analysis identifies previously reported splicing events targeting ERBB4 (mixed MB), GLI1 (SHH) and PTCH1 (SHH), supporting our approach. Subgroup-specific pathway analysis of alternatively spliced genes reveals extensive deregulation of neuronal pathways in non-WNT medulloblastomas, with the specific targeting of genes important for axonal guidance, synaptic transmission and neuronal differentiation. Finally, we present evidence for putative regulation of alternative splicing by antisense transcription. These data further demonstrate the differences between medulloblastoma subgroups, and highlight alternative splicing and isoform expression as a mechanism contributing to the transcriptional heterogeneity between subgroups, and perhaps to subgroup specific pathogenic mechanisms. 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 1430. doi:1538-7445.AM2012-1430
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".