Abstract 4725: The 3D nuclear telomere organization of Hodgkin-cells is different between patients entering rapid remission and patients with refractory or relapsing disease
Bibliographic record
Abstract
Abstract Our recent study has utilized innovative 3D Q- FISH and three-dimensional (3D) imaging to define the 3D nuclear telomere organization in mono-nucleated Hodgkin (H) and multi-nucleated Reed-Sternberg (RS) cells of Hodgkin's lymphoma (HL) derived cell lines and diagnostic patient biopsies (Leukemia. 2009). These characteristics were found in both, classical EBV negative and EBV-associated, LMP1 expressing HL (Lab Invest. 2010). However, it is still unknown whether the 3D telomere profile at diagnostic biopsy is different in patients entering rapid remission after initiation of standard chemotherapy (ABVD) compared to patients with refractory or relapsing disease. In this study, we investigated by 3D telomere Q-FISH diagnostic biopsies of HL patients entering rapid complete remission and diagnostic biopsies from patients with refractory or relapsing disease. 8 diagnostic biopsies of 8 patients entering rapid remission (after 1-4 cycles of ABVD) and 8 diagnostic biopsies of 5 patients including 2 with primary refractory disease (progressing after 4-8 cycles of ABVD) and 3 cases relapsing 1-3 years after late remission (post 6 -8 cycles of ABVD) were analyzed the 3D telomeric structure by 3D Q-FISH and TeloView software (Cytometry A. 2005). We found that RS-cells of all patients from both groups showed significant increase in very short telomeres when compared to the mononuclear precursor H-cells (p<0.01). Additionally, the number of telomere aggregates was significantly higher in RS cells than in H cells in both, the rapid remission group (p<0.001) and the refractory or relapse group (p<0.01). Most importantly, all diagnostic biopsies of the relapse group contained a very high percentage of very small telomeres in both, H-cells (72.4 ± 0.1%) and RS-cells (84.6 ± 9.9%). These differences were highly significant compared the percentage of very small telomeres of the rapid remission group for both, H-cells (40.0± 0.2%) (p=0.002) and RS-cells (59.9 ± 0.2%) (p=0.008). Remarkably, the percentage of very short telomeres was even higher in H-cells of the relapse group than in RS-cells of the rapid remission group. The average number of telomere aggregates per H-cell was significantly higher in the relapse group (3.8 ± 1.9) compared to that one in the rapid remission group (1.3 ± 0.6) (p=0.0003). RS-cells in the relapse contained still more telomere aggregates compared to RS cells of the remission group (5.8 ± 2.8 versus 3.1 ± 1.1) (p=0.03). However, H-cells of the relapse group contained already more aggregates than RS cells of the remission group (p: no significant). These results indicate that the 3D nuclear telomere organization of H and RS cells in refractory or relapsing patients is different from that of patients in rapid remission. In particular, the 3D nuclear telomere profile of H-cells allows identifying aggressive disease already at diagnosis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4725. doi:10.1158/1538-7445.AM2011-4725
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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 | 0.000 |
| 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) | 0.003 | 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".