Skin colonization by circulating neoplastic clones in cutaneous T-cell lymphoma
Bibliographic record
Abstract
Mycosis fungoides (MF) is a mature T-cell lymphoma currently thought to develop primarily in the skin by a clonal expansion of a transformed, resident memory T cell. However, this concept does not explain the key characteristics of MF, such as the debut with multiple, widespread skin lesions or inability of skin-directed therapies to provide cure. The testable inference of the mature T-cell theory is the clonality of MF with respect to all rearranged T-cell receptor (TCR) genes. Here, we used a whole-exome sequencing approach to detect and quantify TCR-α, β, and γ clonotypes in tumor cell clusters microdissected from MF lesions. This method allowed us to calculate the tumor cell fraction of the sample and therefore an unequivocal identification of the TCR clonotypes as neoplastic. Analysis of TCR sequences from 29 patients with MF stage I to IV proved the existence of multiple T-cell clones within the tumor cell fraction, with a considerable variation between patients and between lesions from the same patient (median, 11 clones; range, 2-80 clones/sample). We have also detected multiple neoplastic clones in the peripheral blood in all examined patients. Based on these findings, we propose that circulating neoplastic T-cell clones continuously replenish the lesions of MF, thus increasing their heterogeneity by a mechanism analogous to the consecutive tumor seeding. We hypothesize that circulating neoplastic clones might be a promising target for therapy and could be exploited as a potential biomarker in MF.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".