<scp>MYCN</scp>overexpression is associated with unbalanced copy number gain, altered nuclear location, and overexpression of chromosome arm 17q genes in neuroblastoma tumors and cell lines
Bibliographic record
Abstract
MYCN amplification and MYCN overexpression are poor prognostic factors in neuroblastoma. Tumors with unbalanced chromosome arm 17q gain are often associated with MYCN amplification; however, the relationship between chromosome 17 copy number status and MYCN expression is not known. We investigated the relationship between MYCN expression and chromosome 17 copy number, nuclear location, and gene expression. By performing dual-colored fluorescence in situ hybridization on 16 primary neuroblastomas, we found that those with unbalanced gain of 17q have high MYCN expression, those with no gain have medium expression, and those with numerical gain have low expression (P < 0.0001). We also found that the nuclear location of 17q correlates with chromosome 17 copy number status: copies in tumors with unbalanced gain and no gain of chromosome 17 occupy a more central location than those in tumors with balanced gain (P < 0.0001). We show that a more central nuclear location of 17q coincides with increased expression of genes found within this chromosome arm. To further understand the association between MYCN expression and chromosome 17, we overexpressed MYCN in two low-expressing MYCN cell lines, SHEP and GIMEN. We found that both cell lines had an unbalanced gain of chromosome 17q, a more central nuclear location of the region and increased expression of the 17q genes. Therefore, this study indicates, for the first time, a functional relationship between MYCN overexpression and the gain of 17q in neuroblastoma.
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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) | 0.001 | 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".