Patient-matched tumours, plasma, and cell lines reveal tumour microenvironment- and cell culture-specific microRNAs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
MicroRNAs (miRNAs) are small non-coding RNA molecules that are present in all cell types and bodily fluids and are commonly dysregulated in cancer. miRNAs in cancer have been studied by measuring levels in cell lines, tumour tissues, and in circulation; however, no study has specifically investigated miRNA expression in patient-matched samples across all three sample types. Canine osteosarcoma is a well-established spontaneously occurring model of human osteosarcoma for which matched samples are available. We analysed a panel of miRNAs by real-time quantitative PCR and compared across patients and sample types. While some miRNAs are highly expressed in all three sample types, tumour tissue and cell lines had the most in common. There were several miRNAs that were highly expressed in plasma and tumour tissue but not in cell lines and likely represent miRNAs produced in the tumour microenvironment. Two highly expressed miRNAs were exclusive to plasma and are known to be expressed in circulating cells. This study highlights the importance of considering sample type when studying miRNAs in cancer and demonstrates the power of using patient-matched samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it