One hit, two hits, three hits, more? Genomic changes in the development of retinoblastoma
Bibliographic record
Abstract
The childhood eye cancer retinoblastoma is initiated by the loss of both alleles of the prototypic tumor suppressor gene, RB1. However, a large number of cytogenetic and comparative genomic hybridization (CGH) studies have shown that these M1 and M2 mutational events--although necessary for initiation--are not the only genomic changes in retinoblastoma. Some of these subsequent changes, which we have termed M3 to Mn, are likely crucial for tumor progression not only in retinoblastoma but also in other cancers. Moreover, genes showing genomic change in cancer are more stable markers and, therefore, possible therapeutic targets than genes simply differentially expressed. In this review, we provide the first comprehensive summary of the genomic evidence implicating gain of 1q, 2p, 6p, and 13q, and loss of 16q in retinoblastoma oncogenesis, including karyotype, CGH, and microarray CGH data. We discuss the search for candidate oncogenes and tumor suppressor genes within these regions, including the candidates (KIF14, MDM4, MYCN, E2F3, DEK, CDH11, and others), plus associations between genomic changes and clinical parameters. We also review studies of other regions of the retinoblastoma genome, the epigenetic changes of aberrant methylation of MGMT, RASSF1A, CASP8, and MLH1, and the roles microRNAs might play in this cancer. Although many candidate genes have yet to be functionally validated in retinoblastoma, work in this field lays out a molecular cytogenetic pathway of retinoblastoma development. Candidate cancer genes carry diagnostic, prognostic, and therapeutic implications beyond retinoblastoma.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".