Abstract B009: Establishing new cell lines from undifferentiated pleomorphic sarcoma for sarcoma research
Bibliographic record
Abstract
Abstract Undifferentiated pleomorphic sarcoma (UPS), also known as malignant fibrous histiocytoma (MFH), is a high-grade soft-tissue sarcoma (STS). Despite of importance, there are very few models for study. Here, we have established and characterized UPS-derived cell lines. Cells were obtained UPS tissues by mincing followed by extracting or dissociating using enzymes and cultured by regular culture environment. Cells were maintained and immortal for months without artificial treatment and tumorigenic in vivo study. The tissues from in vivo study and tissues from patients were compared if it is representative for UPS by immunohistochemistry. Transcriptome from tissues and cell lines were compared. Several genes were identified as specific in tumor tissues and cell lines. Fusion genes were also identified. This study showed that new UPS cell lines might be a good resource for UPS study to get new insights. Citation Format: Hye Jin You, Eun-Young Lee, Abu Rayhan, Hyun Guy Kang, June Hyuk Kim, Jongwoong Park. Establishing new cell lines from undifferentiated pleomorphic sarcoma for sarcoma research [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 B009.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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".