Immunotherapy for Cutaneous T-Cell Lymphoma: Current Landscape and Future Developments
Bibliographic record
Abstract
Mycosis fungoides (MF) and Sézary syndrome (SS) are chronic, progressive primary cutaneous T-cell lymphomas (CTCLs) for which there are no curative treatments. Skin-directed therapies, such as phototherapy, radiation therapy, or topical nitrogen mustard, provide only short-term remissions. Numerous attempts with different chemotherapeutic regimes failed to achieve meaningful clinical responses. Immunotherapy seems to be a promising avenue to achieve long-term disease control in CTCL. There is compelling evidence indicating that MF and SS are immunogenic lymphomas, which can be recognized by the patient's immune system. However, CTCL uses different strategies to impair host's immunity, eg, via repolarizing the T-cell differentiation from type I to type II, recruiting immunosuppressive regulatory T-cells, and limiting the repertoire of lymphocytes in the circulation. Many currently used therapies, such as interferon-α, imiquimod, extracorporeal phototherapy, and allogeneic bone marrow transplant, seem to exert their therapeutic effect via activation of the antitumor cytotoxic response and reconstitution of the host's immune system. It is likely that novel immunotherapies such as immune checkpoint inhibitors, cancer vaccines, and chimeric antigen receptor-T cells will help to manage CTCL more efficiently. We also discuss how current genomic techniques, such as estimating the mutational load by whole genome sequencing and neoantigen calling, are likely to provide clinically useful information facilitating personalized immunotherapy of CTCL.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".