Chromosome 6p amplification and cancer progression
Bibliographic record
Abstract
Chromosomal imbalances represent an important mechanism in cancer progression. A clear association between DNA copy-number aberrations and prognosis has been found in a variety of tumours. Comparative genomic hybridisation studies have detected copy-number increases affecting chromosome 6p in several types of cancer. A systematic analysis of large tumour cohorts is required to identify genomic imbalances of 6p that correlate with a distinct clinical feature of disease progression. Recent findings suggest that a central part of the short arm of chromosome 6p harbours one or more oncogenes directly involved in tumour progression. Gains at 6p have been associated with advanced or metastatic disease, poor prognosis, venous invasion in bladder, colorectal, ovarian and hepatocellular carcinomas. Copy number gains of 6p DNA have been described in a series of patients who presented initially with follicle centre lymphoma, which subsequently transformed to diffuse large B cell lymphoma. Melanoma cytogenetics has consistently identified aberrations of chromosome 6, and a correlation with lower overall survival has been described. Most of the changes observed in tumours to date map to the 6p21-p23 region, which encompasses approximately half of the genes on all of chromosome 6 and one third of the number of CpG islands in this chromosome. Analyses of the genes that cluster to the commonly amplified regions of chromosome 6p have helped to identify a small number of molecular pathways that become deregulated during tumour progression in diverse tumour types. Such pathways offer promise for new treatments in the future.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".