Autotaxin Promotes Cancer Invasion via the Lysophosphatidic Acid Receptor 4: Participation of the Cyclic AMP/EPAC/Rac1 Signaling Pathway in Invadopodia Formation
Bibliographic record
Abstract
The ability of cancer cells to invade and metastasize is the major cause of death in cancer patients. Autotaxin (ATX) is a secreted lysophospholipase whose level of expression within tumors correlates strongly with their aggressiveness and invasiveness. ATX is the major enzyme involved in the production of lysophosphatidic acid (LPA), a phospholipid that is known to act mostly through its three first characterized receptors (LPA(1), LPA(2), and LPA(3)). Tumor cell invasion across tissue boundaries and metastasis are dependent on the capacity of invasive cancer cells to breach the basement membrane. This process can be initiated by the formation of the actin-rich cell protrusions, invadopodia. In this study, we show that ATX is implicated in the formation of invadopodia in various cancer cells types and this effect is dependent on the production of LPA. We further provide evidence that LPA(4) signaling in fibrosarcoma cells regulates invadopodia formation downstream of ATX, a process mediated through the activation of EPAC by cyclic AMP and subsequent Rac1 activation. Results using LPA(4) shRNA support the requirement of the LPA(4) receptor for cell invasion and in vivo metastasis formation. This work presents evidence that blocking the LPA receptor, LPA(4), in fibrosarcoma cells could provide an additional tool to improve the efficacy of treatment of metastasis in patients. Because LPA receptors and ATX are currently being targeted in preclinical trials, the current findings should stimulate future studies to evaluate the expression pattern and clinical outcome of LPA(4), together with other LPA receptors, in various cancer patients.
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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 | 0.001 |
| 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".