Profiling genomic copy number changes in retinoblastoma beyond loss of <i>RB1</i>
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Bibliographic record
Abstract
Loss of both RB1 alleles is rate limiting for development of retinoblastoma (RB), but genomic copy number gain or loss may impact oncogene(s) and tumor suppressor genes, facilitating tumor progression. We used quantitative multiplex polymerase chain reaction to profile "hot spot" genomic copy number changes for gain at 1q32.1, 6p22, and MYCN, and loss at 16q22 in 87 primary RB and 7 cell lines. Loss at 16q22 (48%) negatively associated with MYCN gain (18%) (Fisher's exact P = 0.031), gain at 1q32.1 (62%) positively associated with 6p "hot spot" gain (43%) (P = 0.033), and there was a trend for positive association between 1q and MYCN gain (P = 0.095). Cell lines had a higher frequency of MYCN amplification than primary tumors (29% versus 3%; P = 0.043). Novel high-level amplification of 1q32.1 in one primary tumor, confirmed by fluorescence in situ hybridization, strongly supports the presence of oncogene(s) in this region, possibly the mitotic kinesin, KIF14. Gene-specific quantitative multiplex polymerase chain reaction of candidate oncogenes at 1q32.1 (KIF14), 6p22 (E2F3 and DEK), and tumor suppressor genes at 16q22 (CDH11) and 17q21 (NGFR) showed the most common gene gains in RB to be KIF14 in cell lines (80%) and E2F3 in primary tumors (70%). The patterns of gain/loss were qualitatively different in 25 RB compared with 12 primary hepatocellular carcinoma and 12 breast cancer cell lines. Gene specific analysis of one bone marrow metastasis of RB, prechemotherapy and postchemotherapy, showed the typical genomic changes of RB pretreatment, which normalized after chemotherapy.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it