Expansion and Characterization of Tumour Derived T Lymphocytes from Undifferentiated Pleomorphic Sarcoma
Bibliographic record
Abstract
Sarcoma is a group of rare bone and soft tissue tumours with over 50 distinct subtypes. Survival rate of metastatic sarcoma is poor due to the lack of efficacious treatments and therapeutic strategies such as adoptive cell therapy (ACT), which utilizes TDLs, has drawn significant interest due to its precedence in treating metastatic melanoma. However, the low abundance of sarcoma TDLs may be a limiting factor during ACT, which necessitates a large quantity. Additionally, IL-2’s use during ACT promotes FOXP3+ and terminal T cells and may further exacerbate this challenge. As such, this study optimized the Tumour Fragment and Rapid Expansion protocols to robustly expand sarcoma TDLs. Non-IL-2 gamma chain cytokines were also identified as promising IL-2 alternatives to promote T helper and CD8 TDLs with clinically favorable memory phenotype and pro-inflammatory functionality. Future approaches to ACT could explore IL-7+IL-15+IL-21 to expand TDLs, and PD-1 and TIM-3 blockades as adjuvants.
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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 | 0.001 |
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".