Abstract 1500: Mediators of CD8+ cytotoxic T lymphocyte infiltration in pancreatic cancer
Bibliographic record
Abstract
Abstract Pancreatic cancer continues to have the highest mortality rate of all solid cancers, with a 5-year overall survival of approximately 8%. Despite recent progress in other malignancies, immunotherapy remains ineffective against pancreatic cancer. Previous work from our group and others has shown that tumors with mismatch repair (MMR) and homologous repair (HR) deficiency have increased immune activity, likely attributable to the inherently increased mutational and neoantigen load in these patients. However, there remains a subset of pancreatic cancer patients with increased CD8+ T cell infiltration, despite lacking these specific mutational signatures. Furthermore, an increasing body of evidence has shown that mutational burden and neoantigen load only partially explain the T cell-inflamed phenotype seen in tumors, implicating the presence of additional mechanisms that drive T cell infiltration in cancer. Several recent studies have highlighted the importance of proper CD8+ T cell priming by antigen presenting cells (APCs), particularly Batf3+ dendritic cells (DCs), and subsequent tumor infiltration via chemokines for immunotherapy to be effective. In this study, we investigated the involvement of chemokines in cytotoxic T lymphocyte infiltration in pancreatic cancer. Using a bioinformatics-driven approach, we analyzed 78 treatment-naïve, primary pancreas cancer resections for associations between CD8+ tumour infiltrating lymphocytes (TILs) and chemokine expression by RNAseq. A panel of chemokines, including CCL4, CCL5, CXCL9, CXCL10, and CXCL11, was highly associated with CD8+ TILs (p < 0.001). Segregating 173 tumour-enriched patient RNAseq samples based on expression of CXCL9 and CXCL10, we found those with higher expression of these chemokines had increased immune activation signatures. Importantly, this included increased MHC I presentation, presence of Batf3+ DCs, and T cell/APC co-stimulation (p < 0.001), while we observed no differences in conventional predictors of CD8+ T cell infiltration such as SNV counts or neoantigens between groups. These results were consistent across ICGC and TCGA data sets. Moreover, these results were also recapitulated in 72 tumor-enriched liver metastases, suggesting an underlying immunobiology that may occur in both primary and metastatic sites. The cellular sources of these chemokines, as determined by immunohistochemical analysis, and the role of tumor-sensing innate immune pathways leading to CD8+ T cell priming, by pathway and differential gene expression analysis, are currently being investigated. Taken together, these results demonstrate a potential role for these chemokines in recruiting CD8+ T cells in pancreatic cancer. Understanding mediators driving cytotoxic T cell infiltration will help identify mechanisms leading to proper CD8+ T cell priming and homing into tumors, to stratify patients amenable for known and novel immunotherapies. Citation Format: Joan Miguel Romero, Barbara Grünwald, Ashton Connor, Gun Ho Jang, Prashant Bavi, Aaditeya Jhaveri, Mehdi Masoomian, Sandra Fischer, Amy Zhang, Robert E. Denroche, Tracy McGaha, Faiyaz Notta, Pamela Ohashi, Grainne O'Kane, Julie Wilson, Jennifer Knox, Steven Gallinger. Mediators of CD8+ cytotoxic T lymphocyte infiltration in pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1500.
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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 | 0.001 | 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) | 0.002 | 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".