Abstract A18: Characterization of checkpoint inhibitors in the tumor microenvironment (TME) and peripheral blood in endemic Burkitt Lymphoma
Bibliographic record
Abstract
Abstract Introduction: The tumor microenvironment and the interaction between immune checkpoint inhibitors (ICIs) and tumor cells are essential to understand for designing future immunotherapy strategies. In this study, we aim to characterize the tumor microenvironment (TME) in children diagnosed with endemic Burkitt lymphoma (eBL), the most common pediatric cancer in Africa. A history of chronic malaria (Plasmodium falciparum) and Epstein-Barr virus (EBV) coinfections are both risk factors in the etiology of eBL. Methods: Using multicolor flow cytometry and single-cell RNA sequencing, we analyzed the expression of immune checkpoint inhibitors in T cells from the tumor microenvironment and from peripheral blood mononuclear cells (PBMC) of eBL patients, along with age-matched controls with different malaria exposure. Additionally, CD8 T-cell infiltration was confirmed by immunohistochemistry. Results: PD-1+ CD4 T cells from eBL PBMCs were increased in number compared to healthy controls from the malaria-endemic area (p=0.03). Both CD4 and CD8 T cells from eBL PBMCs reveal higher frequency of TIGIT expressers compared to healthy controls (non-malaria endemic) (p=0.002, p=0.007 respectively). PD1+ TIGIT+ IFNG- memory CD4 T cells phenotype from eBL PBMCs was increased upon short stimulation with PMA/ionomycin, as well as “naive-like” CD95+ PD1high TIGIT+ CTLA4+ IFNG+ CD8T cells. Tumor samples from 4 eBL patient were used on single-cell analysis; we observed activated T-cells profile that highly upregulated TIGIT within the tumor microenvironment. We also noticed relatively low expression of other ICIs such as PD1, TIM3, LAG3, and CTLA4. Base on all these data, we calculated an exhaustion score that was higher than the cytotoxicity score in our eBL-derived tumor-infiltrating lymphocytes (TILs). In addition, we use immunohistochemistry staining to confirm CD8 T-cell infiltration and ICI expression in eBL tumor fine needle aspirates. Our future directions will employ TIGIT blockade inhibitor studies of CD8 T cells, in order to increase expansion and function of CD8 TILs. Our results will help support future development of ICI therapies in endemic Burkitt lymphoma. Citation Format: Priya Saikumar-Lakshmi, Cliff Oduor, Catherine Forconi, Patrick Marsh, John Michael Ong’echa, Jeffrey Bailey, Ann Moormann. Characterization of checkpoint inhibitors in the tumor microenvironment (TME) and peripheral blood in endemic Burkitt Lymphoma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A18.
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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) | 0.001 | 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 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".