CD9 is a leukemic stem cell-specific marker in human acute myeloid leukemia
Bibliographic record
Abstract
Abstract Background: Leukemia stem cells (LSCs) are responsible for the initiation, progressing and relapse of acute myeloid leukemia (AML). Therefore, the therapy strategy of targeting LSCs is hopeful to eradicate AML. In this study, we aimed to identify LSCs-specific surface markers and uncover the underlying mechanism of AML LSCs.Methods: Microarray gene expression data were used to investigate the candidate AML-LSCs specific markers. CD9 expression was evaluated by flow cytometry (FC) in AML cell lines, patients with AML and normal donors. The biological characteristics of CD9-positive (CD9+) cells were analyzed by in vitro proliferation, chemotherapeutic drug resistance, migration and in vivo xenotransplantation assays. The molecular mechanism involved in CD9+ cell function was investigated by gene expression profiling. Effects of alpha-2-macroglobulin (A2M) on CD9+ cells were analyzed in the aspects of proliferation, drug resistance and migration.Results：CD9, as a cell surface protein, is specifically expressed on AML LSCs, but barely can be detected on normal hematopoietic stem cells (HSCs). CD9+ cells exhibits more resistance to chemotherapy drugs and higher migration potential than CD9-negative (CD9-) cells. More importantly, CD9+ cells possess the ability to reconstitute human AML in immunocompromised mice and promote leukemia growth, suggesting CD9+ cells define the LSCs population. Furthermore, we identified A2M as an important role in CD9+ LSCs stemness maintenance. Knock down of A2M impairs drug-resistance and migration of CD9+ cells.Conclusion: Our findings suggested that CD9 is a new biomarker of AML LSCs and may serve as a promising therapeutic target.
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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".