Dynamic single cell imaging of cancer stem cells and clonality in fusion-negative rhabdomyosarcoma

Rhabdomyosarcoma (RMS) accounts for 50% of all soft-tissue childhood sarcomas and is characterized by tumor cells that molecularly and morphologically resemble undifferentiated skeletal muscle. Treatment involves an aggressive regimen of chemotherapy followed by surgical resection and/or radiation therapy. Although survival rates can be as high as 70-90% in low-risk or localized disease, patients with oligoclonal or relapsed disease have extremely poor prognoses. Thus, there is a clinical imperative to identify novel therapeutic targets, particularly ones that could reduce clonality and suppress cancer stem cell self-renewal. Our lab has recently shown that fusion-negative (FN-)RMS contain four dominant tumor cell states: proliferative, ground, mesenchymal cancer stem cells (mCSCs) and differentiated muscle. Importantly, the mCSCs are largely quiescent under normal growth conditions but re-enter the cell cycle to promote tumor growth following stress. This suggests that mCSCs are likely responsible for driving therapy resistance and relapse. Building on our previous successes in live imaging cancer stem cells using transgenic zebrafish models that express fluorophores under control of developmentally restricted muscle promoters, we are now developing similar approaches to drive fluorescent protein expression in human FN-RMS cell lines to trace lineage fate and to witness the division history of mCSCs in real time. Using a combination of CRISPR/Cas9 gene inactivation and these newly developed tools, we are poised to identify new self-renewal pathways by the direct, live-cell imaging of FN-RMS engrafted into optically clear, immune-deficient zebrafish. In addition, we are also using tumor clonality as a surrogate of increased tumor aggression and cancer stem cell potential in the zebrafish RAS-induced RMS model. We have adapted the transgenic zebrafish model of kRASG12D-induced RMS to analyze tumor clonality using multispectral Zebrabow and GESTALT, a CRISPR barcoding technique that tracks cell fate. Using RMS-specific gene expression datasets that are associated with cancer stem cells, we are now screening for genes that elevate tumor clonality, increase tumor penetrance and accelerate tumor growth. Ultimately, by developing these lineage tracing tools in both human RMS cell lines and our transgenic Zebrafish RMS model, we will identify new modulators of the mCSC transcriptional cell states and possible therapeutic targets.