Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies

Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies

Efficacy of ONC201 in Desmoplastic Small Round Cell Tumor

Desmoplastic Small Round Cell Tumor (DSRCT) is a rare sarcoma tumor of adolescence and young adulthood, which harbors a recurrent chromosomal translocation between the Ewing’s sarcoma gene (EWSR1) and the Wilms’ tumor suppressor gene (WT1). Patients usually develop multiple abdominal tumors with liver and lymph node metastasis developing later. Survival is poor using a multimodal therapy that includes chemotherapy, radiation and surgical resection, new therapies are needed for better management of DSRCT. Triggering cell apoptosis is the scientific rationale of many cancer therapies. Here, we characterized for the first time the expression of pro-apoptotic receptors, tumor necrosis-related apoptosis-inducing ligand receptors (TRAILR1-4) within an established human DSRCT cell line and clinical samples. The molecular induction of TRAIL-mediated apoptosis using agonistic small molecule, ONC201 in vitro cell-based proliferation assay and in vivo novel orthotopic xenograft animal models of DSRCT, was able to inhibit cell proliferation that was associated with caspase activation, and tumor growth, indicating that a cell-based delivery of an apoptosis-inducing factor could be relevant therapeutic agent to control DSRCT