Molecular cytogenetic analysis of medulloblastomas and supratentorial primitive neuroectodermal tumors by using conventional banding, comparative genomic hybridization, and spectral karyotyping
Bibliographic record
Abstract
OBJECT: Medulloblastomas and related primitive neuroectodermal tumors (PNETs) of the central nervous system are malignant, invasive embryonal tumors with predominantly neuronal differentiation that comprise 20% of pediatric brain tumors. Cytogenetic analysis has shown that alterations in chromosome 17, particularly the loss of 17p and the formation of isochromosome 17q, as well as the gain of chromosome 7 are the most common changes among this group of tumors. Comparative genomic hybridization (CGH) studies have largely confirmed these cytogenetic findings and have also identified novel regions of gain, loss, and amplification. The advent of more sophisticated multicolored fluorescence in situ hybridization (FISH) procedures such as spectral karyotyping (SKY) now permits complete recognition of all aberrations including extremely complex rearrangements. The authors report a retrospective analysis of 19 medulloblastoma and five PNET cases studied using combinations of classic banding analysis, FISH, CGH, and SKY to examine comprehensively the chromosomal aberrations present in this tumor group and to attempt to identify common structural rearrangement(s). METHODS: The CGH data demonstrate gains of chromosomes 17q and 7 in 60% of the tumors studied, which confirms data reported in the current literature. However, the authors have also combined the results of all three molecular cytogenetic assays (Giemsa banding, CGH, and SKY) to reveal the frequency of chromosomal rearrangement (gained, lost, or involved in structural rearrangement). CONCLUSIONS: The combined results indicate that chromosomes 7 and 17 are the most frequently rearranged chromosomes (10.1% and 8.9%, respectively, in all rearrangements detected). Furthermore, chromosomes 3 (7.8%), 14 (7%), 10 (6.7%), and 22 (6.5%) were also found to be frequently rearranged, followed by chromosomes 6 (6.5%), 13 (6.2%), and 18 (6.2%). Eight (33%) of 24 tumors exhibited high-level gains or gene amplification. Amplification of MYCN was identified in four tumors, whereas amplification of MYCC was identified in one tumor. One tumor exhibited a high-level gain of chromosome 9p. Additionally, desmoplastic medulloblastomas and large-cell medulloblastomas exhibited higher karyotype heterogeneity, amplification, and aneusomy than classic medulloblastomas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".