Application Note
Cancer Heterogeneity

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Accurate Single-cell Genomic Analysis Holds theKey to Understanding Cancer Heterogeneity
Advances in genomic technologies have significantly improved our understanding of cancer heterogeneity.
Single-cell whole genome sequencing enables the genetic characterization of distinct tumor cells, providing
actionable information for treatment decisions and disease management. In this Application Note, we discuss anovel and accurate method for single-cell whole genome amplification—Primary Template-directed Amplification(PTA)—and provide examples of how it supports the detection of low-frequency variants in populations of cells.
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Cancer heterogeneity
drives outcomes
In 2020, 10 million people lost their lives
to cancer, and twice as many new cases
were reported worldwide.1 These numbers
are staggering, despite 50 years of intense
global research.
Key insights into the heterogeneous
nature of cancer on both a cellular andmolecular level came from Peter Nowell's
1976 "clonal theory of cancer" (Figure 1),
which laid the foundation for improved“PTA is our methodof choice if you want
reproducible, efficient,and evenly amplified
genomes from single cells
for single nucleotide variant
detection.”
Christopher A. Walsh, MD P hD
Bullard Professor of Neurology,Harvard Medical School,
Chief, Division of Genetics and Investigator,
Howard Hughes Medical Institute,Children's Hospital Boston

Normal cell

Tumor
population 1

Tumor
population 2

Tumor
population 3

Clonalmutation

Sub-clonal mutations(exist in a subset of cancer cells)

Figure 1. The clonal theory of cancer states that tumor initiation occurs by an induced change ina single, previously normal cell which makes it "neoplastic" and provides it with a selective growthadvantage over adjacent normal cells. Mutations that favor immune escape, tumor survival, metastasis,and therapy resistance arise continually, persist in small cell populations, and accumulate over time.

disease management and modern, targeted therapies.2 Since then, everadvancing genomic technologies have unlocked the genetic basis of cancer
at increasing resolution. Nevertheless, most of our knowledge derives frombulk omics approaches. Analysis of mixed cell populations masks the complex
heterogeneity within and across tumors, revealing only the most abundantvariants in a sample. The promise of precision medicine will only be realized
through routine genomic analysis of single pathogenic cells, which allows for
extremely sensitive detection of conserved, rare and de novo variant alleles.
To date, widespread adoption of this approach has been hampered due to thelimitations of existing single-cell whole genome amplification (WGA) methods.

PTA enables accurate single-cell genomics
Primary Template-directed Amplification (PTA) is a novel, isothermal methodthat employs innovative chemistry to drive whole genome amplification ofultra-low quantities of DNA from the primary template. This significantly reduces
challenges associated with existing WGA approaches (such as variable coverage
and allelic dropout), and enables the detection of single-nucleotide variants(SNVs), translocations, and copy number variation (CNV) from a single assay.3
For Research Use Only. Not for use in diagnostic procedures.

Cancer Heterogeneity
To demonstrate the ability of PTA to discern discrete SNVs atsingle-cell resolution, we induced resistance in the AML cell line
MOLM-13 through exposure to the tyrosine kinase inhibitor
quizartinib. Whole genome sequencing (WGS) of individual
parental and resistance cells confirmed that single-cell analysis
significantly increases variant allele frequency (VAF) sensitivity(Figure 2). In an additional study, CNV analysis of a wellcharacterized, hypertriploid breast cancer cell line (SKBR3) wasperformed. CNV heterogeneity (not distinguishable in a bulksample) was clearly observed between individual single cells(Figure 3). In addition, PTA supports the analysis of single-celltumor mutation burden (TMB).4Conclusion
BioSkryb’s ResolveDNA™ Whole Genome Sequencing Workflow
employs PTA to enable accurate and scalable single-cellsequencing. Our BaseJumper Bioinformatics Platform isdesigned to sort, analyze and interpret very large data sets. This
novel data collection and processing platform provides an orderof magnitude of improvement in sensitivity over conventionalbulk sequencing methods.

Learn more about PTA, and how we may support
your efforts to understand cancer heterogeneityand improve cancer outcomes.

Figure 2. Digital detection of somatic alleles in single cells. Parental andquizartinib-resistant AML cells were both found to contain the FLT3 internal
tandem duplication (FLT3 ITD, left). An additional, secondary, missense
mutation (N841K) was detected in resistant cells only (right). This mutation,
which is likely a key driver of drug resistance, emerged as dominant inresistant cells, after being rare in the parental population (confirmed by qPCR).

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Figure 3. Bulk vs single-cell CNV analysis.
Compared to a normal, primary single breastepithelial cell (A), where the chromosome
structure appears to be intact (diploid), theDNA from a bulk SKBR3 sample (B) displayeda high degree of copy number variation. CNV
heterogeneity was clearly observed at the singlecell level. In one single cell (C) the CNV pattern inchromosome 1 was similar to the bulk DNA (bluepanel), whereas the degree of duplication wasless in another cell (D). Differential CNV patterns
were observed on the single-cell level for almost
every other chromosome, with the most striking
examples highlighted in yellow. Given thateach 500 kb window represents multiple genes,genomic differences between these individual
cells are significant.

References
1. Sung J, et al. CA Cancer J Clin 2021;71:209-249.
doi: 10.3322/caac.21660.
2. Nowell, PC. Science 1976; 194(4260):23-28.
doi: 10.1126/science.959840.
3. Gonzalez V, et al. bioRxiv. 2020 Nov;
doi: 10.1101/2020.11.20.391961.
4. West JAA, et al. Manuscript in preparation.

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