Abstract A009 Single cell transcriptomic signature of Li-Fraumeni Syndrome soft tissue sarcomas
Bibliographic record
Abstract
Abstract Li-Fraumeni Syndrome (LFS) is a genetic predisposition disorder associated with pathogenic germline Tp53 mutations. A subset of LFS-associated neoplasms occurs at an increased risk within the first 5 years of life, with the most common being soft tissue sarcomas (STS). Histological characterization of STS is one of the primary approaches to guiding treatment. However, the heterogeneity of STS has necessitated a further understanding of the molecular etiology of these tumors. Examining sarcomas using a single-cell transcriptomic approach has shown unique subsets of cells with dysregulations in cell fate and differentiation. Within LFS-associated tumors, including LFS-STS a major event in tumorigenesis is the copy-neutral loss of heterozygosity (LOH). LOH was determined to occur much earlier than cancer onset in LFS, suggesting a dormancy period from the LOH until tumorigenesis; cancer-defining events in LFS are likely occurring prenatally. During embryogenesis, Tp53 is involved in differentiation and pluripotency regulation, as well as cell cycle control and apoptosis. Here we hypothesize that the emergence of STS in LFS mice is associated with distinct disturbances in the cell fate and differentiation pathways. Specifically, there will be deficits in cell fate determination and the organization of cells across multiple cell types in LFS-Sarcomas. Single-cell RNAseq was performed on spontaneous tumors and healthy matched muscle tissue from male and female C57BL/6J Trp53R172H/WT mice. Cell types were determined based on differential gene expression between clusters defined by principal component analysis. Despite tumor heterogeneity between mice, there were consistent disruptions of developmental pathways among tumor cells. Moreover, when comparing matched cell types across tumor and healthy muscle tissue we observed dysregulation of pathways promoting tumorigenesis, and cell fate determination in cells originating from tumor tissue. For the first time to our knowledge, this study examines the single-cell transcriptome of LFS-STS. Current literature has speculated on the presence of an early precancer state of LFS-associated tumors. This study will provide evidence to determine whether this precancer state can be determined in tumor samples, and identify elements that constitute this state. Moreover, we will determine changes in supporting non-tumor cells and whether they also exhibit dysregulations in cell state and differentiation. Together these findings will hopefully contribute to improvements in molecular subtyping across STS, and particularly within LFS individuals. Citation Format: Ashby Kissoondoyal, David Malkin. Single cell transcriptomic signature of Li-Fraumeni Syndrome soft tissue sarcomas [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A009.
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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) | 0.001 | 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".