CD24 as a Potential Therapeutic Target in Patients with B-Cell Leukemia and Lymphoma: Current Insights
Bibliographic record
Abstract
CD24 is a highly glycosylated glycophosphatidylinositol (GPI)-anchored protein that is expressed in many types of differentiating cells and some mature cells of the immune system as well as the central nervous system. CD24 has been extensively used as a biomarker for developing B cells as its expression levels change over the course of B cell development. Functionally, engagement of CD24 induces apoptosis in developing B cells and restricts cell growth in more mature cell types. Interestingly, CD24 is also expressed on many hematological and solid tumors. As such, it has been investigated as a therapeutic target in many solid tumors including ovarian, colorectal, pancreatic, lung and others. Most of the B-cell leukemias and lymphomas studied to date express CD24 but its role as a therapeutic target in these malignancies has, thus far, been understudied. Here, I review what is known about CD24 biology with a focus on B cell development and activation followed by a brief overview of how CD24 is being targeted in solid tumors. This is followed by an assessment of the value of CD24 as a therapeutic target in B cell leukemia and lymphoma in humans, including an evaluation of the challenges in using CD24 as a target considering its pattern of expression on normal cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".