Genomic dissection of tumor heterogeneity and progression

Division Of Basic Sciences - Nci

Investigators

Linked publications & trials

Abstract

The first aim of this project is to use single cell sequencing to understand the complexities of cell types and cell to cell heterogeneity that is present within pediatric solid tumors. In this work, we are focusing on generating comprehensive gene expression profiling of the cells present within tumors that occur in patients with NF1. To date we have collected and analyzed surgical specimens from Plexiform Neurofibromas (PN), Atypical Neurofibromas (AN) and Malignant Peripheral Nerve Sheath Tumors (MPNST). Over the past two years, we have generated high gene coverage sequencing on 600,000 single cells from 24 patients with NF1 nerve tumors including histologically validated PN, ANF and MPNST. Our dataset generated to date includes single-cell sequencing of PN and ANF. From these experiments, we capture the landscape of cellular heterogeneity within these tumors. Within PNs we have identified at least 21 unique cell populations including a variety of stromal and immune cell types. This rich dataset details the transcriptional profile of each of these populations and highlights both known and novel cell types. Following the same procedure, we have generated scRNAseq data from 300,000 cells from three MPNST tumors and 10 PDX MPNST models. Preliminary examples of this dataset were published this year in collaborative efforts with investigators at Memorial Sloan Kettering and Washington University. These works discovered the recurrence and importance of chromosome 8 amplification in MPNST and an interesting cellular population with cancer stem cell like properties. Additionally, we have made progress integrating the human findings with genetically engineered model systems of NF1 based nerve tumors. Currently, we are finalizing this dataset to describe the multitude of cell-to-cell interactions within these tumors to dissect potential tumor specific vulnerabilities. Given the difficulty in obtaining multiple sequential tumor biopsy specimens from patients with solid tumors, we have undertaken a project to assay cell free DNA to assess disease status in NF1 patients. In this work we have developed an assay that marries low pass whole genome sequencing with NF1 specific targeted capture deep sequencing of selected genes. This work has culminated in publication of our classifier which uses tumor fraction from blood specimens to provide a clinical tool that could be used to differentiate between MPNST and the benign Plexiform Neurofibroma. Currently we are evaluating our assays value using samples collected on the actively enrolling clinical trial SARC031 (NCT03433183) MEK Inhibitor Selumetinib (AZD6244) in Combination with the mTOR Inhibitor Sirolimus for Patients With MPNST. Another application of cell free DNA technology is correlating the changes observed in the circulating tumor DNA with the changes observed on re-staging imaging as a measure of response of a tumor to therapy. These efforts are currently underway. Secondary efforts to pair the circulating tumor DNA with an on-treatment tumor biopsy to observe correlation and description of the global genomic changes in the circulating tumor DNA to discover mechanisms of tumor evolution are being explored. The second aim of this work is to develop novel barcoding strategies married with single cell sequencing that can be used in preclinical model systems to model tumor cell resistance and survival. Single cell sequencing can dissect the gene expression profile of thousands of cells in parallel but is limited in its ability to track populations of cells under a selective pressure. Within the current year we completed pilot experiments that highlighted the need to add a feature to our experimental system which enabled tracking a particular cell over time and as it replicated. To accomplish this, we have incorporated a unique sequence DNA barcode into each cell within a pool of cells (greater than 10 million unique barcodes in 10 separate pools). Importantly, our vector generates a polyadenylated expressed gene that is compatible with capture using single cell RNA sequencing methods. Experiments have been completed which demonstrated that we are able to detect the expressed DNA barcodes within the scRNAseq data over time and with cell population expansion. Current experiments are employing the single cell barcoding strategy to understand the heterogenous tumor cell responses to topoisomerase inhibitors and small molecules targeting epigenetic modifiers. We anticipate that this will enable discernment of the expression profiles of individual surviving cells and definition of new therapeutic targets.