Abstract A022: Targeting of soft tissue sarcoma cancer stem cells improves doxorubicin-sensitivity <i>in vitro</i>
Bibliographic record
Abstract
Abstract Soft tissue sarcomas (STS) are rare tumors encompassing over 70 distinct histopathological subtypes that share a common treatment strategy comprising surgical resection, radiation, and chemotherapy in certain situations. Disease progression and failure to respond to anthracycline based chemotherapy, a standard first-line agent, is associated with poor outcomes. Recurrence and chemo-resistance represent significant barriers to improving patient survival. We are interested in the contribution of STS cancer stem cells (STS-CSCs) to the phenomenon of chemo-resistance to doxorubicin. Specifically, we hypothesized the presence of a common genetic signature across unique STS subtypes involved in CSC-regulation that could be targeted to improve the efficacy of existing treatment regimens. To this end, STS-CSCs were profiled by flow cytometry using the Aldeflour assay. This is a well-established technique to measure the aldehyde dehydrogenase activity of cells which is high in the stem cell population. This fluorescently labels Aldefluor bright and dim cells as CSCs and non-CSCs, respectively. The abundance of the CSC population in several STS cell lines modeling dedifferentiated liposarcoma, leiomyosarcoma, and undifferentiated pleomorphic sarcoma were assessed by Aldeflour assay. In order to gain insight into the molecular pathways active in STS-CSCs, Aldeflour-bright and -dim populations were isolated by FACs and analyzed by RNA-sequencing. Gene-set enrichment analysis of genes upregulated in STS-CSCs identified a signature for the histone methyltransferase Enhancer of Zeste homolog 2 (EZH2), part of the polycomb repressive complex 2 (PRC2) responsible for H3K27 methylation. As an epigenetic modulator, increased EZH2 expression and activity potentiates decreased activity of genes involved in growth suppression and thereby has oncogenic activity. EZH2 can be inhibited with small molecules such as Tazemetostat, an approved treatment for metastatic and locally advanced epithelioid sarcoma. To test the effects of EZH2 inhibition on STS-CSCs, we first generated doxorubicin resistance STS cell lines by serial selection with increasing concentrations of doxorubicin. We identified a positive correlation between CSC abundance and doxorubicin IC50 in the resistant cell lines. Further, co-treatment of doxorubicin and tazemetostat was not only synergistic in the parent cell lines, but restored chemosensitivity in doxorubicin resistant lines. These data confirm the presence of shared genetic programs across distinct subtypes of STS that are unique to CSCs and amenable to therapeutic targeting. Citation Format: Edmond F. O'Donnell, Maria Muñoz, Lor Randall, Janai R. Carr-Ascher. Targeting of soft tissue sarcoma cancer stem cells improves doxorubicin-sensitivity in vitro [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 A022.
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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) | 0.003 | 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".