Creating a Catalog of Cancer Clonotype Drug Sensitivities with Single-CellGenome Sequencing

Stanford University, Stanford CA

Investigators

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Abstract

Project Summary Malignant neoplasms remain the second leading cause of death in the United States, with around 1,700,000 new diagnoses and 600,000 deaths annually. Most patients that succumb to cancer have advanced disease at diagnosis that is at least partially resistant to current treatment regimens. The ability to readily determine tumor genotypes by next-generation sequencing has created expectations of more precise treatment strategies. However, sequencing technologies have thus far been of limited clinical value due to their inadequate sensitivity, limiting genomic interrogations to the most abundant clonal populations, as well as their limited capacity to determine whether two variants are present in the same cell, preventing determinations of the clonal genotypes, or clonotypes. We have developed a single-cell whole-genome amplification method named primary template-directed amplification (PTA), which offers improved coverage and uniformity, as well as greater cell-to-cell reproducibility, than existing methods. PTA is amenable to performing massively parallel, automated, single-cell whole-genome amplification in microfluidic devices. In this project, we will use PTA to develop massively parallel single-cell DNA- sequencing methodologies to interrogate the genotypes of thousands of cells from each sample. This will enable us to determine the co-occurrence patterns of mutations with sensitivity that is proportional to the number of cells interrogated, and to identify clonotypes that undergo positive selection when primary acute lymphoblastic leukemia (ALL) cells are exposed to chemotherapy in vitro and in patients. We will then use these data to create a catalog ofALL clonotype drug sensitivities. Childhood ALL is the ideal disease to study as we develop our methodologies, as samples are readily available before and during treatment, require no special protocols for tissue dissociation, and have established culture conditions for studying drug resistance. With our novel tools and computational pipelines, we aim to provide an approach for studying a given malignant neoplasm not as a homogeneous group of cells, but as a diverse collection of distinct malignant populations that require individual characterization in order to understand and predict treatment response, as well as to develop efficacious therapies. Our studies are intended to provide a more detailed understanding of the clonal dynamics and mechanisms of treatment resistance of childhood ALL as patients undergo treatment and to investigate cancer clonal evolution at cellular-level resolution. The resulting catalog of drug resistances is intended to inform clone-directed precision treatment strategies for cancer.