Inhibition of ERO1a and IDO1 improves dendritic cell infiltration into pancreatic ductal adenocarcinoma
Bibliographic record
Abstract
Introduction: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal and treatment resistant cancers. Due to its desmoplastic and hypoxic nature along with an abundance of myeloid cell infiltration and scarce T cell infiltration, PDAC is considered a cold tumor. Methods: Here we sought to investigate myeloid cell infiltration and composition in PDAC spheroids by targeting the hypoxia-associated pathways endoplasmic reticulum oxidoreductase 1 alpha (ERO1a) and indoleamine 2,3-dioxygenase 1 (IDO1). Using MiaPaCa2 spheroids with hypoxic core, we assessed the roles of ERO1a and IDO1 inhibition in modulating monocyte infiltration and differentiation, followed by characterizing immunomodulatory factors secreted using LC-MS/MS. Results: Inhibition of ERO1a and IDO1 significantly improved monocyte infiltration and differentiation into dendritic cells. LC-MS/MS analysis of the PDAC spheroid secretome identified downregulation of hypoxia and PDAC pathways, and upregulation of antigen presentation pathways upon inhibition of ERO1a and IDO1. Furthermore, immunomodulatory factors involved in immune infiltration and migration including interleukin-8, lymphocyte cytosolic protein 1, and transgelin-2, were upregulated upon inhibition of ERO1a and IDO1. Discussion: Collectively, our results show that inhibition of ERO1a and IDO1 modulates the tumor microenvironment associated with improved monocyte infiltration and differentiation into dendritic cells to potentially influence therapeutic responses in patients with PDAC.
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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".