Abstract 2492: Integrated genomics on molecular subgroups in medulloblastoma
Bibliographic record
Abstract
Abstract Medulloblastoma is the most common malignant brain tumor in childhood. Molecular studies from several groups around the world demonstrated that medulloblastoma is not one disease but comprises a collection of distinct molecular subgroups. However, all these studies reported on different numbers of subgroups. The current consensus is that there are only four major subgroups, which are now called WNT, SHH, Group 3 and Group 4. A better understanding of each of these molecular subtypes is urgently warranted to improve treatment strategies and the overall survival of patients and ultimately also the quality of life for those that survive medulloblastoma. We used the data of seven independent studies on medulloblastoma for further characterization of these molecular subtypes. All cases (n = 550) were analyzed by expression profiling and for most cases SNP or array-CGH data were available. Data are presented for all medulloblastomas together and for each subgroup separately. For validation purposes we compared the results of this meta-analysis with another large medulloblastoma cohort (n = 408) for which subgroup information was obtained by immunohistochemistry. Results from both cohorts are highly similar and show how distinct the molecular subtypes are with respect to their transcriptome, DNA copy number aberrations, demographics, and survival. Interestingly, the data also showed how different medulloblastomas are between infants, children and adults. In infants, for instance, almost all medulloblastomas are classified as SHH or Group 3, whereas in adults most medulloblastomas are of the SHH subtype and almost never of Group 3. Recent next generation sequencing data (whole genome and exome) generated in our laboratory for a large series of pediatric and adult medulloblastomas show that the spectrum of genetic mutations is also very different, not only between the molecular subtypes, but also between the different age categories. All these data clearly show that medulloblastoma is not one disease. Results from these molecular analyses will form the basis for prospective multi-center studies and will have an impact on how the different variants of medulloblastoma will be treated in the future. 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 2492. doi:1538-7445.AM2012-2492
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".