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Record W2051494228 · doi:10.1002/gcc.10209

Patterns of aneuploidy in stage IV clear cell renal cell carcinoma revealed by comparative genomic hybridization and spectral karyotyping

2003· article· en· W2051494228 on OpenAlexaff
Christian P. Pavlovich, Hesed Padilla‐Nash, Danny Wangsa, Michael L. Nickerson, Vera Y. Matrosova, W. Marston Linehan, Thomas Ried, John L. Phillips

Bibliographic record

VenueGenes Chromosomes and Cancer · 2003
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsSKiN Health
Fundersnot available
KeywordsComparative genomic hybridizationKaryotypeBiologyChromosomal translocationRenal cell carcinomaChromosomeAneuploidyCarcinogenesisClear cell renal cell carcinomaChromosome 7 (human)GeneticsChromosome 3Cancer researchMolecular biologyPathologyCancerGeneMedicine

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.250
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2003
Admission routes1
Has abstractyes

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