Investigation of Pediatric Rhabdomyosarcoma Recurrence through Single-Cell Sequencing
Background:
Metastatic rhabdomyosarcoma (RMS) is a devastating disease with poor 5-year survival rates (less than 30%). Outcomes for these patients have not changed in the last 30 years, underscoring the need for a better biologic understanding of RMS. This proposal centers on the observation that RMS tumors shrink when treated with chemotherapy but recur after completing treatment. For this to occur, a minority of cells within a tumor survive treatment to re-grow. We have developed a research plan to characterize these cells, in the belief that understanding how tumors recur will provide a window to new RMS therapies.
Project Goal:
We will use an experimental model from patient RMS tumors that are expanded in mice. Critically, these tumors shrink when treated and return after completing therapy, mimicking the clinical experience. We have adapted genomic technologies that enable us to sequence single cells within these tumors before and after recurrence. These studies will establish a cell-by-cell atlas of RMS and will be a resource for future investigation. To extend our studies, we have developed a novel “barcoding” strategy to track individual cells within tumors across time; this approach allows us to address which specific cells within tumors survive therapy. The findings from this study have the potential to identify new therapeutic avenues for a disease with poor outcomes. This approach is applicable to any number of solid tumors; the completion of this study will forge a new direction for the evaluation and understanding of a variety of pediatric solid tumors.
Project Update 2024:
Over the last 3 years, we have taken advantage of new single-cell sequencing technologies to evaluate pediatric rhabdomyosarcoma (RMS), a childhood tumor of muscle. Using single-cell RNA-sequencing, We have built an “atlas” and shown that the diversity of RMS tumor cells mimics that of normal muscle development. We have also performed single-cell sequencing of patient-derived xenografts, human tumors that grow in immunodeficient mice, and shown that those xenografts match the cellular diversity of their original tissue. We have leveraged this information to identify specific cells that persist during therapy. Using a combination of computational biology and experimental patient-derived models of RMS, we have shown that combining conventional chemotherapy with drugs targeted against the persistent cell population can result in better outcomes. Over the final year of funding, we have expanded on this understanding by working with other research teams located around the globe to harmonize and standardize our findings. We have applied this unified model of RMS heterogeneity to understand the process of recurrence in the fusion-positive variant of RMS. Collectively, this work funding by ALSF sets the stage for the development of biomarker assays to track tumor evolution during therapy and the testing of targeted agents with the express purpose of preventing tumor recurrence.