The Vascular Endothelial Growth Factor (VEGF) Autocrine Survival Signaling Pathway in Chronic Lymphocytic Leukemia (CLL) Is Regulated by Lysophosphatidic Acid (LPA).
Bibliographic record
Abstract
Abstract Vascular endothelial growth factor (VEGF) is a survival and angiogenesis factor that has been the target of chemotherapy in a variety of cancers including chronic lymphocytic leukemia (CLL). The VEGF survival response is regulated by an autocrine loop where cells constitutively express VEGF and activate the VEGF receptors leading to up-regulation of anti-apoptotic Bcl-2 members and prevention of apoptosis. Herein, we have demonstrated that VEGF is elevated in the plasma of CLL patients compared to normal individuals. We have previously shown that the growth factor, lysophospatidic acid (LPA), is a survival factor in CLL and its receptor LPA1 is up-regulated in CLL cells (J Biol Chem, 280:9498, 2005). Now, we demonstrate that inhibiting VEGF receptor activation blocks the survival response seen with LPA in CLL. LPA treatment was found to induce VEGF mRNA and protein levels within 1 hour. LPA receptor inhibitor Ki16425 blocked the VEGF production and reversed the protective effect of LPA against apoptosis. Combining LPA and VEGF failed to increase survival responses in these cells. In addition, LPA protection against fludarabine and TRAIL induced apoptosis was eliminated using the VEGF receptor kinase inhibitor, epigallocatechin-3-gallate (EGCG), which is present in green tea, or VEGFR:Fc, that inhibits VEGF receptor activation. Furthermore, LPA induced AKT activation and up-regulation of the expression of the Bcl-2 family member, Mcl-1, were eliminated by the VEGF receptor inhibitor. Thus, the protective effect of LPA against apoptosis in CLL is related to increased production of VEGF. Targeting the LPA pathway similar to the VEGF pathway may thus be a novel approach for the treatment of CLL.
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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".