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, and 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 called terminator displacement amplification (TDA), which offers improved coverage and uniformity, as well as greater cell-to-cell reproducibility, than existing methods. TDA is amenable to performing massively parallel, automated, single-cell whole-genome amplification in microfluidic devices. In this project, we will use TDA 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 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 use these data to create a catalog of ALL clonotype drug sensitivities. Childhood ALL is ideal for studying 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 and 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 with cellular-level resolution. The resulting catalog of drug resistances is intended to inform clone-directed precision treatment strategies for cancer.
Despite being the underlying cause of the persistence and recurrence of malignant neoplasms that result in poor patient outcomes, the resistance of cancers to treatment remains poorly understood and difficult to predict. This proposal describes innovative high- throughput single-cell DNA-sequencing methodologies for determining the genotypes of thousands of cells from the same sample at the time of diagnosis, as well as after exposure to specific drugs. The project seeks to use the data obtained by these methods to create a catalog of cancer clonotype drug resistances that will be used to inform treatment selection, enabling higher-resolution precision cancer medicine. !
