T-Cells with Extremely Short Telomeres and High Telomerase Activity in T-Cell Prolymphocytic Leukemia (T-PLL): The Ideal Target for Telomerase Inhibition.
Bibliographic record
Abstract
Abstract T-cell prolymphocytic leukemia (T-PLL) is a rare aggressive lymphoproliferative disease characterized by the expansion of a T-cell clone derived from immuno-competent post-thymic T-lymphocytes. Important mechanisms involved in expansion of human malignant cells are reactivation of telomerase, an enzyme complex, which is able to compensate the loss of telomere repeats by cell division, and maintenance or elongation of telomere length. To investigate the role of telomeres and telomerase we measured telomere length by automated multicolor flow-FISH and telomerase activity by telomeric repeat amplification protocol in subsets of peripheral blood leukocytes from 11 newly diagnosed or relapsed patients with sporadic T-PLL. In addition, we analyzed the effect of the selective telomerase inhibitor BIBR1532 on T-PLL cells in short-term culture assays. The average telomere length in the clonal T-cells of all samples analyzed was extremely short (mean ± std: 1.53 kb ± 0.65 kb) compared to the non-clonal T-cells (5.03 kb ± 0.71 kb; p=0.012). The average telomere length for B-cells in these patients was 6.37 kb ± 0.71 kb (n=6). Telomere length values of the clonal T-cells were all below the 1st percentile of telomere length values observed in T-cells from healthy aged-matched controls whereas non-clonal T-cells and B-cells fell between the 1st and 99th percentile of the normal distribution. Interestingly, telomere length in the clonal T-cells remained stably short at 1.0 kb ± 0.6 kb without further telomere loss in one patient over a period of 18 months. No cell doublets indicative of fused or bridged chromosomes and telomere dysfunction were observed. Clonal T-cells exhibited high levels of telomerase activity almost comparable to levels of the positive control K562 whereas there was no measurable telomerase activity in normal, unstimulated T-cells. Telomerase levels even correlated inversely with telomere length in clonal T-cells (r=−0.91, n=6). In addition, we could induce a dose-dependent cytotoxicity of T-PLL cells with the telomerase inhibitor BIBR1532 (viable cells as percentage of untreated controls (viability index) in % after 10 days of cell culture (mean ± std) with 0, 10, 40, 100 μM BIBR1532: 100 ± 0, 54 ± 14.3, 27.5 ± 11.7, 2.6 ± 1.6, n=6) whereas no effect was observed in normal, unstimulated T-cells (viability index in % (mean ± std) after 10 days with 0, 10, 40, 100 μM BIBR1532: 100 ± 0, 100.8 ± 8.6, 96.9 ± 7.9, 103.1 ± 22.4, n=3). In summary, clonal T-cells in T-PLL exhibit extremely short telomeres which could explain the genomic instability with cytogenetic aberrations. The high levels of telomerase found in T-PLL cells are sufficient to stably maintain the critically short telomeres and allow clonal expansion. In addition, we can demonstrate that inhibition of telomerase in vitro in the situation of T-PLL cells with already very short telomeres and high telomerase levels leads to rapid cytotoxicity of the T-cell clone without a time delay before telomeres get critically short as observed in the situation of longer telomeres. Targeting telomerase and telomeres seems therefore an attractive strategy for the future treatment of this devastating disease.
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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) | 0.001 | 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".