Identification of Differentially Expressed Long Noncoding RNAs in Bladder Cancer
Bibliographic record
Abstract
PURPOSE: Loss of epigenetic gene regulation through altered long noncoding RNA (lncRNA) expression seems important in human cancer. LncRNAs have diagnostic and therapeutic potential, and offer insights into the biology disease, but little is known of their expression in urothelial cancer. Here, we identify differentially expressed lncRNAs with potential regulatory functions in urothelial cancer. EXPERIMENTAL DESIGN: The expression of 17,112 lncRNAs and 22,074 mRNAs was determined using microarrays in 83 normal and malignant urothelial (discovery) samples and selected RNAs with qPCR in 138 samples for validation. Significantly differentially expressed RNAs were identified and stratified according to tumor phenotype. siRNA knockdown, functional assays, and whole-genome transcriptomic profiling were used to identify potential roles of selected lncRNAs. RESULTS: We observed upregulation of many lncRNAs in urothelial cancer that was distinct to corresponding, more balanced changes for mRNAs. In general, lncRNA expression reflected disease phenotype. We identified 32 lncRNAs with potential roles in disease progression. Focusing upon a promising candidate, we implicate upregulation of AB074278 in apoptosis avoidance and the maintenance of a proproliferative state in cancer through a potential interaction with EMP1, a tumor suppressor and a negative regulator of cell proliferation. CONCLUSIONS: We report differential expression profiles for numerous lncRNA in urothelial cancer. We identify phenotype-specific expression and a potential mechanistic target to explain this observation. Further studies are required to validate lncRNAs as prognostic biomarkers in this disease.
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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 | 0.004 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".