Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics

Abstract

Many cancers have substantial genomic heterogeneity within a given tumor, and to fully understand that diversity requires the ability to perform single cell analysis. We performed targeted sequencing of a panel of single nucleotide variants (SNVs), deletions, and IgH sequences in 1,479 single tumor cells from six acute lymphoblastic leukemia (ALL) patients. By accurately segregating groups of cooccurring mutations into distinct clonal populations, we identified codominant clones in the majority of patients. Evaluation of intraclonal mutation patterns identified clone-specific punctuated cytosine mutagenesis events, showed that most structural variants are acquired before SNVs, determined that KRAS mutations occur late in disease development but are not sufficient for clonal dominance, and identified clones within the same patient that are arrested at varied stages in B-cell development. Taken together, these data order the sequence of genetic events that underlie childhood ALL and provide a framework for understanding the development of the disease at single-cell resolution.single-cell genomics | acute lymphoblastic leukemia | intratumor heterogeneity | clonal evolution | cytosine mutagenesis A more comprehensive understanding of how malignancies develop could facilitate the rational development of novel anticancer treatment and prevention strategies. Large projects that aim to comprehensively characterize somatic mutations in cancer samples have cataloged many of the recurrent genomic lesions in a wide variety of tumors (1). However, these studies do not measure the correlated cooccurrence of genomic lesions between different cells, which is required for understanding the clonal structure of a tumor as well as for rigorously determining temporal ordering of mutation acquisition. Other studies have provided some temporal resolution of mutation segregation patterns from diagnosis to disease recurrence, allowing for post hoc inference of intratumor clonal heterogeneity at diagnosis (2-5). However, approaches that rely on mutant allele frequencies to determine clonal structure require multiple samples from the same patient and are unable to resolve clones with mutations present at similar frequencies, which is a prerequisite to unambiguously determine the clonal structure and delineate the evolution of the disease (3-5). In principle, single cell genomics provides the most rigorous method to determine the clonal heterogeneity of tumors; as discussed below, there have been recent advances in this approach, but technical limitations have until now prevented it from fully addressing the questions of interest.Studies of pediatric acute lymphoblastic leukemias (ALL) have provided a limited ordering of the genetic events that underlie childhood leukemogenesis by studying prediagnostic samples. For example, ETV6 -RUNX1 translocations, which occur in about a third of patients under 10 y of age, have been shown to occur in utero by tracking the translocation back to neonatal blood spots (6, 7). In addition, a recent report ...

A generic, cost-effective, and scalable cell lineage analysis platform

“…Most of the MS panel is designed for (A) MSs of type AC on the X Chromosome to allow for monoallelic MS calling Wasserstrom et al 2008;Reizel et al 2011;Segev et al 2011;Shlush et al 2012) and for (B) the longest MS loci possible, which exhibit a higher mutation rate in vivo (Ellegren 2004;Supplemental Table S2). Notably, primers were designed such that the entire MS will be covered within a 150-bp Examples of single-cell analyses to reconstruct clonal/lineage analysis Wang et al 2012;Xu et al 2012;Gawad et al 2014;Lohr et al 2014;Lodato et al 2015) (Navin et al 2011;Cai et al 2014;Wang et al 2014) ) Salipante et al 2010;Reizel et al 2011Reizel et al , 2012Shlush et al 2012;Evrony et al 2015) read (see Methods). (2) We modified the second PCR to apply a sample barcode by utilizing combinations of forward and reverse PCR primer combinations, resulting in a dual indexed NGS library (Supplemental Fig.…”

“…5, see below). We thus opted to evaluate the platform on cancerous cells, which harbor microsatellite instability (MSI), as cancer is the major application of clonal analysis and cell lineage reconstruction (Ding et al 2012;Gawad et al 2014;Lohr et al 2014;Wang et al 2014). We designed a novel controlled ex vivo experiment utilizing DU145, a human male prostatic carcinoma cell line, via an automated cell picking device (CellCelector, ALS) ( Fig.…”

“…Due to the high cost and low efficiency of SC WGS, some also validate their findings using bulk analysis in order to detect the distribution of mutations in the population . Another method for lineage analysis utilizes bulk whole-genome (or -exome) sequencing in order to detect patient-/tumor-specific putative genomic variants, followed by custom targeted enrichment (Gawad et al 2014;Lohr et al 2014). The mutations found in these methods are highly effective as targeting candidates as they provide a patient-specific signal, which differs between cells with a high precision.…”

Construction of thousands of single cell genome sequencing libraries using combinatorial indexing

“…One of the primary applications of single cell genome sequencing is in the profiling of tumor heterogeneity and understanding clonal evolution in cancer as it relates to treatment resistance [5][6][7] . We posited that the high throughput of SCI-seq and coverage uniformity using the xSDS method of nucleosome depletion may facilitate an in depth analysis of tumor heterogeneity by single cell CNV analysis.…”

“…The booming field of single cell sequencing continues to shine light on the abundance and breadth of genomic heterogeneity between cells in a variety of contexts, including somatic gains or losses of megabasepair-sized regions of the genome in the mammalian brain [1][2][3][4] , and tumor heterogeneity and clonal evolution [5][6][7] . Single cell genome sequencing studies have taken one of two approaches: high depth of sequencing per cell for purposes of single nucleotide variant detection 2,8 , or low-pass sequencing to identify copy number variants (CNVs) and the presence of aneuploidy 1,9,10 .…”