Lymphoma stem cells: enough evidence to support their existence?
Bibliographic record
Abstract
While leukemia-originating stem cells are critical in the initiation and maintenance of leukemias, the existence of similar cell populations that may generate B-cell lymphoma upon mutation remains uncertain. Here we propose that committed lymphoid progenitor/precursor cells with an active V-D-J recombination program are the initiating cells of follicular lymphoma and mantle cell lymphoma when targeted by immunoglobulin (IG)- gene translocations in the bone marrow. However, these pre-malignant lymphoma-initiating cells cannot drive complete malignant transformation, requiring additional cooperating mutations in specific stem-cell programs to be converted into the lymphoma-originating cells able to generate and sustain lymphoma development. Conversely, diffuse large B-cell lymphoma and sporadic Burkitt's lymphoma derive from B lymphocytes that acquire translocations through IG-hyper-mutation or class-switching errors within the germinal center. Although secondary reprogramming mutations are generally required, some cells such as centroblasts or memory B cells that have certain stem cell-like features, or lymphocytes with MYC rearrangements that deregulate self-renewal pathways, may bypass this need and directly function as the lymphoma-originating cells. An alternative model supports an aberrant epigenetic modification of gene sets as the first occurring hit, which either leads to retaining stem-cell features in hematopoietic stem or progenitor cells, or reprograms stemness into more committed lymphocytes, followed by secondary chromosomal translocations that eventually drive lymphoma development. Isolation and characterization of the cells that are at the origin of the different B-cell non-Hodgkin's lymphomas will provide critical insights into the disease pathogenesis and will represent a step towards the development of more effective therapies.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".