A Four-Chemokine Signature Is Associated with a T-cell–Inflamed Phenotype in Primary and Metastatic Pancreatic Cancer
Bibliographic record
Abstract
Abstract Purpose: The molecular drivers of antitumor immunity in pancreatic ductal adenocarcinoma (PDAC) are poorly understood, posing a major obstacle for the identification of patients potentially amenable for immune-checkpoint blockade or other novel strategies. Here, we explore the association of chemokine expression with effector T-cell infiltration in PDAC. Experimental Design: Discovery cohorts comprised 113 primary resected PDAC and 107 PDAC liver metastases. Validation cohorts comprised 182 PDAC from The Cancer Genome Atlas and 92 PDACs from the Australian International Cancer Genome Consortium. We explored associations between immune cell counts by immunohistochemistry, chemokine expression, and transcriptional hallmarks of antitumor immunity by RNA sequencing (RNA-seq), and mutational burden by whole-genome sequencing. Results: Among all known human chemokines, a coregulated set of four (CCL4, CCL5, CXCL9, and CXCL10) was strongly associated with CD8+ T-cell infiltration (P < 0.001). Expression of this “4-chemokine signature” positively correlated with transcriptional metrics of T-cell activation (ZAP70, ITK, and IL2RB), cytolytic activity (GZMA and PRF1), and immunosuppression (PDL1, PD1, CTLA4, TIM3, TIGIT, LAG3, FASLG, and IDO1). Furthermore, the 4-chemokine signature marked tumors with increased T-cell activation scores (MHC I presentation, T-cell/APC costimulation) and elevated expression of innate immune sensing pathways involved in T-cell priming (STING and NLRP3 inflammasome pathways, BATF3-driven dendritic cells). Importantly, expression of this 4-chemokine signature was consistently indicative of a T-cell–inflamed phenotype across primary PDAC and PDAC liver metastases. Conclusions: A conserved 4-chemokine signature marks resectable and metastatic PDAC tumors with an active antitumor phenotype. This could have implications for the appropriate selection of PDAC patients in immunotherapy trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 teacher head, 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".