Small Noncoding RNA Expression in Cancer
Bibliographic record
Abstract
Despite an inability to encode proteins, small noncoding RNAs (sncRNAs) have critical functions in the regulation of gene expression. They have demonstrated roles in cancer development and progression and are frequently dysregulated. Here we review the biogenesis and mechanism of action, expression patterns, and detection methods of two types of sncRNAs frequently described in cancer: miRNAs and piRNAs. Both miRNAs and piRNAs have been observed to play both oncogenic and tumor-suppressive roles, with miRNAs acting to directly regulate the mRNA of key cancer-associated genes, while piRNAs play crucial roles in maintaining the integrity of the epigenetic landscape. Elucidating these important functions of sncRNAs in normal and cancer biology relies on numerous in silico workflows and tools to profile sncRNA expression. Thus, we also discuss the key detection methods for cancer-relevant sncRNAs, including the discovery of genes that have yet to be described.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.008 |
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".