Abstract A025: Profiling tumor infiltrating immune cells for better understanding tumor status and better response to therapeutic strategy in soft tissue sarcomas
Bibliographic record
Abstract
Abstract The tumor microenvironment is closely associated with tumor development and progression, which is made up of tumor cells, blood vessels, immune cells, fibroblast, and so on. Especially, immune cells within tumor microenvironments have been attracted in clinicians and researchers for unexpected therapeutic responses. Even in sarcoma, which is rare, and heterogenous leading to few options for cure, immune therapy has been tried and shown to be promising. However, the information of immune cells within soft tissue sarcomas were limited, which mostly have been obtained and characterized by omics-based analyses or tissue staining such as immunohistochemistry. Here, we established platform to profile tumor infiltrating immune cells by flow cytometry. About thirty sarcoma tissues were obtained, in which tumor infiltrating immune cells were profiled. The profiled data were confirmed by immunohistochemistry for correlation. It was shown that infiltrated leukocytes and CD3+ T cells were remarkably increased, whereas NKT and CD4+ T cells were decreased in tumor tissues compared to adjacent normal tissues. M1 macrophage was also increased in tumor tissues. High CD3+ T cell population was positively correlated with CD8+ T cells and PD1+ CD8+ T cell population. Especially, PD1+CD8+ T cells are usually expressed exhaustion-related conditions and low levels of cytotoxic immune cells. This study provides resources to understand immune cell population of soft tissue sarcoma, and will gain a fundamental matrix to study immunotherapy. These studies might show the possibility to find potential prognostic and immunotherapeutic targets. Citation Format: Eun-Young Lee, Hyun Guy Kang, June Hyuk Kim, Jong Woong Park, Seog Yun Park, Tak Yun, Hye Jin You. Profiling tumor infiltrating immune cells for better understanding tumor status and better response to therapeutic strategy in soft tissue sarcomas [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A025.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".