Abstract IA013: Rhabdomyosarcoma: visions through the looking glass
Bibliographic record
Abstract
Abstract Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children. Despite aggressive treatment clinical outcomes for RMS have not improved for three decades, emphasizing the need to uncover the molecular underpinnings of the disease. RMS has been presumed to originate from derailed muscle progenitors based on the histologic appearance and gene expression pattern of the tumors resembling embryonic developing skeletal muscle. However, an origin restricted to skeletal muscle does not explain RMS occurring in tissues devoid of skeletal muscle such as the prostate, bladder, and salivary gland. Previously, we described that activation of Sonic Hedgehog signaling through expression of a conditional, constitutively active Smoothened allele, SmoM2, under control of a presumed adipocyte-restricted adipose protein 2 (aP2)-Cre recombinase transgene in mice gives rise to aggressive skeletal muscle tumors. These tumors display the histologic and molecular characteristics of human embryonal fusion-negative RMS (FN-RMS). This model suggested a potential non-myogenic origin of FN-RMS and an avenue to explain FN-RMS development in anatomic sites devoid of skeletal muscle. Lineage tracing showed that RMS can originate from cell reprogramming and transdifferentiation of endothelial progenitor cells. Hedgehog pathway activation in committed endothelial progenitors results in Tbx1 expression and subsequent Myod1 expression driving a partially myogenic program characteristic of FN-RMS. Our work identifies reprogramming cell fate as a mechanism of transformation in pediatric sarcoma and illustrates that it is dangerous to assume the cell of origin from the characteristics of the tumor cell. The cell-reprogramming mechanism that shifts endothelial progenitors to muscle-like cells provides a unique system to define the core regulatory circuitry controlling RMS cell fate and to determine in vivo if targeting this network is a therapeutic vulnerability. Genomic profiling of human FN-RMS failed to uncover a unique mutation that drives oncogenesis. However, the PTEN cis-regulatory region is hypermethylated in more than 90% of all human FN-ERMS tumors, resulting in decreased expression. However, inhibiting the PI3K/AKT/mTOR pathway has had varied efficacy in RMS. In our RMS mouse model, PTEN localizes to the cytoplasm and nucleus, suggesting that PTEN could have functions other than regulating the PI3K/AKT/mTOR pathway. We demonstrate that Pten loss cooperates in RMS tumorigenesis and results in tumors more reflective of human FN-RMS. We show that Pten loss drives expression of the transcription factor PAX7 and identified PAX7 as a dependency in human FN-RMS. Furthermore, Pax7 deletion completely rescues the deleterious effects of Pten loss but also alters tumor cell fate, giving rise to a smooth muscle tumor. Thus, PTEN loss drives the expression of PAX7, a key member of the RMS core regulatory circuitry dictating tumor cell fate. This highlights a synthetic essential relationship between PTEN and PAX7 in FN-RMS tumor maintenance and tumor-fate decisions. Citation Format: Mark E. Hatley, Casey G. Langdon, Katherine E. Gadek, Matthew R. Garcia, Catherine J. Drummond, Jason A. Hanna, Hongjian E. Jin, Jerold E. Rehg. Rhabdomyosarcoma: visions through the looking glass [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 IA013.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".