Patterns of aneuploidy in stage IV clear cell renal cell carcinoma revealed by comparative genomic hybridization and spectral karyotyping
Bibliographic record
Abstract
We report the use of spectral karyotyping (SKY) and comparative genomic hybridization (CGH) to describe the numerous genomic imbalances characteristic of stage IV clear cell renal cell carcinoma (CCRCC). SKY and CGH were performed on 10 cell lines established from nephrectomy specimens, and CGH on uncultured material from five of the primary renal tumors. The mutational status of VHL (3p25) and MET (7q31), genes implicated in renal carcinogenesis, were determined for each case. Each case showed marked aneuploidy, with an average number of copy alterations of 14.6 (+/-2.7) in the primary tumors and 19.3 (+/-4.6) in the cell lines. Both whole-chromosome and chromosome-segment imbalances were noted by CGH: consistent losses or gains included +5q23-->ter (100%), -3p14-->ter (80%), and +7 (70%). All VHL mutations and 83% of the genomic imbalances found in the primary tumors were also found in the cell lines derived from them. SKY showed many complex structural rearrangements that were undetected by conventional banding analysis in these solid tumors. All cases with VHL inactivation had 3p loss and 5q gain related primarily to unbalanced translocations between 3p and 5q. In contrast, gains of chromosome 7 resulted primarily from whole-chromosome gains and were not associated with mutations of MET. SKY and CGH demonstrated that genomic imbalances in advanced RCC were the result of either segregation errors [i.e., whole chromosomal gains and losses (7.8/case)] or chromosomal rearrangements (10.7/case), of which the majority were unbalanced translocations.
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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 | 0.001 | 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".