Insights into autotaxin- and lysophosphatidate-mediated signaling in the pancreatic ductal adenocarcinoma tumor microenvironment: a survey of pathway gene expression
Bibliographic record
Abstract
Lysophosphatidate (LPA)-mediated signaling is a vital component of physiological wound healing, but the pathway is subverted to mediate chronic inflammatory signaling in many pathologies, including cancers.LPA, as an extracellular signaling molecule, is produced by the enzyme autotaxin (ATX, gene name ENPP2) and signals through six LPA receptors (LPARs).Its signaling is terminated by turnover via the ecto-activity of three lipid phosphate phosphatases (LPPs, gene names PLPP1-3).Many pharmacological developments against the LPA-signaling axis are underway, primarily against ATX.An ATX inhibitor against pancreatic ductal adenocarcinoma (PDAC), a very aggressive disease with limited systemic therapeutic options, is currently in clinical trials, and represents the first in-class drug against LPA signaling in cancers.In the present study, we surveyed the expression of ATX, LPARs, and LPPs in human PDACs and their clinical outcomes in two large independent cohorts, the Cancer Genome Atlas (TCGA) and GSE21501.Correlation among gene expressions, biological function and the cell composition of the tumor microenvironment were analysed using gene set enrichment analysis and cell cyber-sorting with xCell.ENPP2, LPAR1, LPAR4, LPAR5, LPAR6, PLPP1, and PLPP2 were significantly elevated in PDACs compared to normal pancreatic tissue, whereas LPAR2, LPAR3, and PLPP3 where downregulated (all P≤0.003).Only ENPP2 demonstrated survival differences, with overall survival favoring ENPP2-high patients (hazard ration 0.5-0.9).ENPP2 was also the only gene with enriched gene patterns for inflammatory and tissue repair gene sets.Epithelial (cancer) cells had increased LPAR2, LPAR5 and PLPP2 expression, and decreased ENPP2, LPAR1, PLPP1, and PLPP3 gene expression (all P<0.02).Tumor fibroblasts had increased ENPP2, LPAR2, LPAR4, PLPP1, and PLPP3 expression and decreased LPAR2, LPAR5, and PLPP2 expression in both cohorts (all P≤0.01).Immune cell populations were not well correlated to gene expression in PDACs, but across both cohorts, cytolytic scores were increased in highexpressing ENPP2, LPAR1, LPAR6, PLPP1, and PLPP3 tumors (P<0.01).Overall, in PDACs, ENPP2 may switch from an anti-to-pro tumor promoting gene with disease progression.LPAR2 and PLPP2 inhibition are also predicted to have potential therapeutic utility.Future multi-omics investigations are necessarily to validate which LPA signaling components are high-value candidates for pharmacological manipulation in PDAC treatment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".