Haematogenous seeding in mycosis fungoides and Sézary syndrome: current evidence and clinical implications
Bibliographic record
Abstract
Cutaneous T-cell lymphomas (CTCLs) are a heterogeneous group of diseases characterized by abnormal neoplastic T-cell growth in the skin. Mycosis fungoides (MF), the most common CTCL, manifests as erythematous skin patches and/or plaques, tumours or erythroderma. The disease may involve blood, lymph nodes and rarely viscera. Sézary syndrome (SS) is a unique leukaemia/lymphoma syndrome related to MF, which presents with blood and skin involvement at diagnosis. The pathogenesis of MF/SS is not fully elucidated. The presence of skin lesions at distant sites underpins a hypothesis that MF/SS lesions may develop through haematogenous seeding. Phenotypic similarities between malignant and normal T cells led to the notion that disease-initiating mutations occur in specific subtypes of mature T cells, which are responsible for most CTCLs. However, this mature T-cell precursor model is not always consistent with clinical observations and research on MF/SS pathogenesis. Here, we review evidence supporting an alternative model of pathogenesis for MF/SS involving haematogenous seeding as a key process responsible for the initiation and progression of the disease. According to this hypothesis, malignant transformation occurs at an early stage of T-cell development (probably in bone marrow or thymus), yielding circulating neoplastic T cells which colonize the skin where the microenvironment is most permissive for proliferation and evolution. These mutated precursor cells seed the skin where they find a suitable niche to develop into clinically perceptible disease. Subsequently, malignant T cells can re-enter the bloodstream, re-seed pre-existing lesions and seed new areas of the skin, causing synchronous and convergent changes in the transcriptomic profile of lesions and tumours, and clinical disease progression - 'consecutive haematogenous seeding' captures this temporal phenomenon. This model radically changes the current understanding of CTCL pathogenesis, transforming it from a primarily cutaneous disease with secondary involvement of blood, to a systemic disease, where the spread of malignant cells through the blood to the skin is not a phenomenon of advanced disease but is an essential component of pathogenesis. This understanding of MF/SS could have several clinical implications, including standardizing our approach to assessing blood tumour burden, potential advances in prognosis and monitoring, and investigating combination treatments to improve patient outcomes.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".