Implications of differential transcription start site selection on chronic myeloid leukemia and prostate cancer cell protein expression
Bibliographic record
Abstract
The relevance of minor transcription start sites in broad promoters is not well understood. We have studied AGAP2 expression in prostate cancer and chronic myeloid leukemia (CML), showing transcription is initiated from alternative transcription start sites (TSSs) within a single TSS cluster, producing cancer-type-specific AGAP2 mRNAs with small differences in their 5′ UTR length. Interestingly, in the CML cell lines where the 5′ UTR is longer, AGAP2 protein levels are lower. We demonstrate that the selection of an upstream TSS involved the formation of a G quadruplex in the 5′ UTR, decreasing polysome formation. After developing a bioinformatics pipeline to query data from the FANTOM project and the NCl-60 human tumor cell lines screen, we found HK1 expression can also be regulated by the same mechanism. Overall, we present compelling data supporting TSS selection within a TSS cluster play a role in protein expression and should not be ignored.
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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 | 0.000 | 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) | 0.002 | 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".