microRNA evaluation of unknown primary lesions in the head and neck
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
Unknown primary malignancy in the head and neck is not an infrequent diagnosis for patients with metastatic cervical lymph nodes. Although linked with a relatively good prognosis following radiation treatment, widespread radiation is coupled with significant morbidity. Altered microRNA (miRNA) expression has been associated with both cancer progression and metastasis. We sought to determine whether miRNA expression analysis could be used as a diagnostic tool to discover the primary site of malignancy, within the head and neck. We used quantitative real-time PCR to identify miRNA expression profiles of squamous cell carcinoma of the tonsil, base of tongue and post-nasal space, as well as their corresponding metastatic lymph nodes, from 6 patients. Our results revealed that each cancer maintained its expression profile between the primary site and the nodal metastasis (r = 0.82, p < 0.0001). In addition, each anatomical sub-site maintained a distinct miRNA profile between individual patients (r = 0.79, p < 0.0001). Finally, between sub-sites, the miRNA profiles were distinct (p < 0.0001). As proof of principle, our study provides an indication that miRNA expression analysis may be useful to compare the primary lesion and local metastatic disease. This may be clinically relevant to predict the primary site of origin of metastatic disease, when the primary site remains obscure.
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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 it