Expression analysis of 6p22 genomic gain in retinoblastoma
Bibliographic record
Abstract
To identify gene(s) targeted by 6p22 genomic gain, present in more than 50% retinoblastoma tumors, we used real-time RT-PCR to quantify the expression of seven genes in normal human retina and retinoblastoma. Six genes are located in the quantitative multiplex PCR-defined 0.6 Mb minimal region of gain at 6p22 (DEK, AOF1, TPMT, NHLRC1, KIF13A, and NUP153), and E2F3 is 2 Mb away from the minimal region of gain on 6p22. E2F3, DEK, KIF13A, and NUP153 were most frequently overexpressed in retinoblastoma with 6p genomic gain, compared with the normal adult human retina. E2F3 and DEK mRNA levels were increased in all human tumors showing 6p22 gain, as well as in mouse retinoblastoma induced by SV40 large T antigen expression in developing retina, compared with the normal controls (adult human retina and 7-day-old mouse retina, respectively). Only DEK showed statistically significant correlation of expression and genomic copy number (P = 0.019). E2F3 and DEK, but not NUP153, showed developmental regulation. E2F3 and DEK mRNA overexpression was always associated with protein overexpression, determined by immunoblotting or immunofluorescent staining of primary tumors, relative to the adjacent normal retina. E2F3 was strongly expressed in actively proliferating cells, while DEK was overexpressed in all tumor cells. Taking into account the proliferation-promoting role of E2F3, implication of E2F3 in bladder and prostate cancer, and the translocation and overexpression of DEK in leukemia, we conclude that either DEK or E2F3 (or both) are targeted by the 6p22 gain in 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 | 0.000 | 0.000 |
| 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".