Prevalence and heterogeneity of circulating tumour cells in metastatic cutaneous melanoma
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
We previously demonstrated that circulating tumour cells (CTCs) are detectable by the MelCAM and high molecular weight melanoma-associated antigen (HMW-MAA)-dependent CellSearch platform. However, CTCs which do not express these capture and detection markers are not detectable by CellSearch. Consequently, we explored the use of isolation by size of epithelial tumour cells (ISET), a marker independent, filtration-based device to determine the prevalence and heterogeneity of CTCs in metastatic cutaneous melanoma patients. Ninety patients were prospectively recruited and blood samples taken before treatment. Patients' blood was filtered using the ISET platform. CTCs were enumerated using dual immunohistochemistry with positive selection by S100 expression and exclusion of leucocytes and endothelial cells expressing CD45 or CD144, respectively. A panel of markers (Melan-A, MITF, MelCAM, high molecular melanoma-associated antigen, CD271 and MAGEC) was also examined. Fifty-one patients (57%) had CTCs (range 1-44 CTCs/4 ml blood) and 12 patients also had circulating tumour microemboli. Seven patients had S100- CTCs, 11 patients' CTCs were S100+ and 33 patients had S100+ and S100- CTCs. Substantial intrapatient and interpatient heterogeneity was observed for all other melanoma-associated markers. CTCs in metastatic cutaneous melanoma are detectable using the flexible marker-independent ISET platform. CTCs display significant marker expression heterogeneity implying that marker-dependent platforms would not detect all CTCs and multimarker assays are now required to reveal the biological significance of this CTC heterogeneity.
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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 | 0.001 | 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 it