Multicellular Calcium Waves in Cancer-Associated Fibroblasts Regulate Neuronal Mimicry and Anisotropy Leading to Immune Exclusion
Bibliographic record
Abstract
Summary Stromal barriers exclude CD8+ T cells from accessing cancer cells and hamper immune-mediated tumour control. Through multi-pronged analysis of tumours that transition from immune inflamed to immune excluded, we reveal that the formation of stromal barriers is associated with the acquisition of neuronal gene expression programmes in cancer-associated fibroblasts (CAFs), including TUBB3 expression. This leads to neuronal mimicry, with stromal barrier formation underpinned by coordinated transient bursts of intracellular calcium release, similar to those observed in neuronal tissue. Blockade of calcium release through either pharmacological or molecular interventions, such as STC2 depletion, prevents CAF alignment and the build-up of CD8+ T cells at stromal boundaries. Nintedanib treatment prevents neuronal mimicry and restores immune-mediated tumour control. Thus, we uncover unexpected mimicry of neuronal behaviour in CAFs, document the mechanism by which it leads to immune exclusion, and identify ways to prevent the induction of neuronal mimicry and restore immune-mediated tumour control. Graphical Abstract
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.008 | 0.001 |
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".