The HGF/c-Met Axis Synergizes with G-CSF in the Mobilization of Hematopoietic Stem/Progenitor Cells
Bibliographic record
Abstract
As granulocyte-colony-stimulating factor (G-CSF)-induced mobilization of hematopoietic stem/progenitor cells (HSPCs) increases human serum levels of hepatocyte growth factor (HGF), our aim was to investigate the role of HGF and its receptor, c-Met, in the mobilization of HSPC. CD34(+) cells and leukocytes were isolated from the bone marrow (BM) of normal donors and the peripheral blood (PB) of patients mobilized with G-CSF and chemotherapy. Plasma HGF levels were evaluated by ELISA and HGF and c-Met expression by RT-PCR, fluorescence-activated cell sorter (FACS) analysis, and confocal microscopy. Because matrix metalloproteinases (MMPs) facilitate migration across extracellular matrix (ECM) and basement membranes, we also examined expression of MMP-9 and membrane type 1 (MT1)-MMP in hematopoietic cells after HGF stimulation. We found that plasma HGF levels in mobilized (m)PB were higher in patients who are good mobilizers and correlated with their white blood cell (WBC) and CD34(+) cell counts. Moreover, HGF and c-Met expression was significantly higher in mPB CD34(+) cells and leukocytes than in their steady-state BM counterpart cells and was up-regulated by G-CSF. Like G-CSF, HGF increased the secretion of MMP-9 and the expression of MT1-MMP in leukocytes, which was abrogated by the c-Met inhibitor K-252a. This inhibitor also significantly reduced the trans-Matrigel migration of mPB CD34(+) cells toward HGF. Our results suggest that G-CSF-mediated HSPC mobilization occurs in part through the HGF/c-Met axis in HSPC and myeloid cells, eliciting increased production of matrix-degrading enzymes and subsequently facilitating egress of HSPC.
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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".