Quantitative expression profiling guided by common retroviral insertion sites reveals novel and cell type–specific cancer genes in leukemia
Bibliographic record
Abstract
Proviral insertional mutagenesis is a powerful tool for the discovery of cancer-associated genes. The ability of integrated proviruses to affect gene expression over long distances combined with the lack of methods to determine the expression levels of large numbers of genes in a systematic and truly quantitative manner have limited the identification of cancer genes by proviral insertional mutagenesis. Here, we have characterized a new model of proviral insertional mutagenesis-induced lymphoid tumors derived from Eed Polycomb group gene mutant mice and quantitatively determined the expression levels of all genes within 100 kb of 20 different retroviral common insertion sites (CISs) identified in these tumors. Using high-throughput quantitative reverse transcription-polymerase chain reaction (Q-RT-PCR), we document an average of 13 CIS-associated genes deregulated per tumor, half of which are leukemia subtype-specific, while the others are coordinately deregulated in the majority of tumors analyzed. Interestingly, we find that genes located distantly from common proviral integration sites are as frequently deregulated as proximal genes, with multiple genes affected per integration. Our studies reveal an unsuspected conservation in the group of genes deregulated among phenotypically similar subtypes of lymphoid leukemias, and suggest that identification of common molecular determinants of this disease is within reach.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".