Unique somatic and malignant expression patterns implicate PIWI-interacting RNAs in cancer-type specific biology
Bibliographic record
Abstract
Human PIWI-interacting RNAs (piRNAs) are known to be expressed in germline cells, functionally silencing LINEs and SINEs. Their expression patterns in somatic tissues are largely uncharted. We analyzed 6,260 human piRNA transcriptomes derived from non-malignant and tumour tissues from 11 organs. We discovered that only 273 of the 20,831 known piRNAs are expressed in somatic non-malignant tissues. However, expression patterns of these piRNAs were able to distinguish tissue-of-origin. A total of 522 piRNAs are expressed in corresponding tumour tissues, largely distinguishing tumour from non-malignant tissues in a cancer-type specific manner. Most expressed piRNAs mapped to known transcripts, contrary to "piRNA clusters" reported in germline cells. We showed that piRNA expression can delineate clinical features, such as histological subgroups, disease stages, and survival. PiRNAs common to many cancer types might represent a core gene-set that facilitates cancer growth, while piRNAs unique to individual cancer types likely contribute to cancer-specific biology.
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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) | 0.001 | 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".