Targeting chronic lymphocytic leukemia with N-methylated thrombospondin-1–derived peptides overcomes drug resistance
Bibliographic record
Abstract
Chronic lymphocytic leukemia (CLL), the most common adulthood leukemia in Western countries, is a very heterogeneous disease characterized by a peripheral accumulation of abnormal CD5+ B lymphocytes in the immune system. Despite new therapeutic developments, there remains an unmet medical need for CLL. Here, we demonstrate that the use of N-methylated thrombospondin-1 (TSP-1)-derived peptides is an efficient way to kill the malignant CLL cells, including those from high-risk individuals with poor clinical prognosis, del11q, del17p, 2p gain, or complex karyotype. PKT16, our hit N-methylated peptide, triggers the elimination of the leukemic cells, sparing the nontumor cells, including the hematopoietic precursors, and reduces the in vivo tumor burden of a CLL-xenograft mice model. A complementary analysis underscores the improved cytotoxic efficiency of PKT16 compared with the previously described TSP-1-derived probes, such as PKHB1. PKT16 elicits an original caspase-independent programmed necrotic mode of cell death, different from necroptosis or ferroptosis, implicating an intracellular Ca2+ deregulation that provokes mitochondrial damage, cell cycle arrest, and the specific death of the malignant CLL cells. The activation of the Gαi proteins and the subsequent drop of cyclic adenosine monophosphate levels and protein kinase A activity regulate this cytotoxic cascade. Remarkably, PKT16 induces the molecular hallmarks of immunogenic cell death, as defined by the calreticulin plasma membrane exposure and the release of adenosine triphosphate and high-mobility group box 1 protein from the dying CLL cells. Thus, PKT16 appears to be able to stimulate an anticancer in vivo immune response. Collectively, our results pave the way toward the development of an efficient strategy against CLL.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".