TGF-β induced CXCL13 in CD8+ T cells is associated with tertiary lymphoid structures in cancer
Bibliographic record
Abstract
Abstract Coordinated immune responses against human tumors are frequently characterized by tertiary lymphoid structures (TLS) which predict improved prognosis. The development of TLS is dependent on the chemokine CXCL13, reported to be secreted by dendritic cells and follicular helper T cells only. We report the unexpected finding that CXCL13 is also secreted by activated CD8+ T cells following stimulation by transforming growth factor beta (TGF-β). Using single cell RNA sequencing we found that expression of CXCL13 in CD8+ T cells was restricted to the intraepithelial CD103+ population. Accordingly, CD8+ T cells activated in the presence of TGF-β simultaneously upregulated CD103 and secreted CXCL13. CXCL13 expression was strongly correlated with neo-antigen burden and cytolytic gene signatures in bulk tumors. In line with this, TLS were abundant in neo-antigen-high, CD103+ T cell-enriched tumors. TGF-β thus appears to play a role in coordinating immune responses against human tumors through CD8-dependent CXCL13-associated formation of TLS.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".