Three-dimensional Telomere Signatures of Hodgkin- and Reed-Sternberg Cells at Diagnosis Identify Patients with Poor Response to Conventional Chemotherapy
Bibliographic record
Abstract
In classic Hodgkin lymphoma (HL) the malignant mononuclear Hodgkin (H) and multinuclear Reed-Sternberg (RS) cells are characterized by a distinct three-dimensional nuclear telomere organization with shortening of the telomere length and the formation of telomeric aggregates. We asked if the severity of these telomere changes correlates with the clinical behavior of the disease. We retrospectively evaluated three-dimensional telomere organization by quantitative fluorescent in situ hybridization (Q-FISH) of diagnostic biopsies from 16 patients who were good responders and compared them with 16 diagnostic biopsies of 10 patients with refractory or relapsing HL (eight initial biopsies, four confirming progressions, and four confirming relapses). The H cells from patients with refractory/relapsing disease contained a significantly higher percentage of very small telomeres (P = .027) and telomere aggregates (P = .032) compared with H cells of patients entering rapid remission. These differences were even more significant (P = .002 and P = .013, respectively) when comparing the eight initial diagnostic biopsies of refractory/relapsing HL with diagnostic biopsies of eight patients with ongoing long-lasting remission (mean of 47 months). This specific three-dimensional telomere Q-FISH signature identifies these highly aggressive mononuclear H cells at the first diagnostic biopsy and thus may offer a new molecular marker to optimize initial treatment.
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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".