A Transcriptionally Distinct CXCL13+CD103+CD8+ T-cell Population Is Associated with B-cell Recruitment and Neoantigen Load in Human Cancer
Bibliographic record
Abstract
Abstract The chemokine CXCL13 mediates recruitment of B cells to tumors and is essential for the formation of tertiary lymphoid structures (TLSs). TLSs are thought to support antitumor immunity and are associated with improved prognosis. However, it remains unknown whether TLSs are formed in response to the general inflammatory character of the tumor microenvironment, or rather, are induced by (neo)antigen-specific adaptive immunity. We here report on the finding that the TGFβ-dependent CD103+CD8+ tumor-infiltrating T-cell (TIL) subpopulation expressed and produced CXCL13. Accordingly, CD8+ T cells from peripheral blood activated in the presence of TGFβ upregulated CD103 and secreted CXCL13. Conversely, inhibition of TGFβ receptor signaling abrogated CXCL13 production. CXCL13+CD103+CD8+ TILs correlated with B-cell recruitment, TLSs, and neoantigen burden in six cohorts of human tumors. Altogether, our findings indicated that TGFβ plays a noncanonical role in coordinating immune responses against human tumors and suggest a potential role for CXCL13+CD103+CD8+ TILs in mediating B-cell recruitment and TLS formation in human tumors.
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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) | 0.003 | 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".