ConDoR: Tumor phylogeny inference with a copy-number constrained mutation loss model

Abstract

Tumors consist of subpopulations of cells that harbor distinct collections of somatic mutations. These mutations range in scale from single nucleotide variants (SNVs) to large-scale copy-number aberrations (CNAs). While many approaches infer tumor phylogenies using SNVs as phylogenetic markers, CNAs that overlap SNVs may lead to erroneous phylogenetic inference. Specifically, an SNV may be lost in a cell due to a deletion of the genomic segment containing the SNV. Unfortunately, no current single-cell DNA sequencing (scDNA-seq) technology produces accurate measurements of both SNVs and CNAs. For instance, recent targeted scDNA-seq technologies, such as Mission Bio Tapestri, measure SNVs with high fidelity in individual cells, but yield much less reliable measurements of CNAs. We introduce a new evolutionary model, the constrained k-Dollo model, that uses SNVs as phylogenetic markers and partial information about CNAs in the form of clustering of cells with similar copy-number profiles. This copy-number clustering constrains where loss of SNVs can occur in the phylogeny. We develop ConDoR (Constrained Dollo Reconstruction), an algorithm to infer tumor phylogenies from targeted scDNA-seq data using the constrained k-Dollo model. We show that ConDoR outperforms existing methods on simulated data. We use ConDoR to analyze a new multi-region targeted scDNA-seq dataset of 2153 cells from a pancreatic ductal adenocarcinoma (PDAC) tumor and produce a more plausible phylogeny compared to existing methods that conforms to histological results for the tumor from a previous study. We also analyze a metastatic colorectal cancer dataset, deriving a more parsimonious phylogeny than previously published analyses and with a simpler monoclonal origin of metastasis compared to the original study.

Code availability: Software is available at https://github.com/raphael-group/constrained-Dollo.

Figure 1:

Overview of the ConDoR algorithm. ConDoR takes as input: (a) A clustering of cells based on copy-number profiles and (b) variant and total read counts from scDNA-seq data. ConDoR employs the Constrained k-Dollo model to construct the (c) constrained k-Dollo phylogeny with mutation losses (dashed box) allowed only between cells from distinct copy-number clusters and the (d) mutation matrix.

Figure 2:

ConDoR outperforms existing methods in recovering the mutation matrix and the tumor phylogeny on simulated data. (a) Normalized mutation matrix error and (b) pairwise ancestral relation accuracy for each method compared to the simulated ground truth. Box plots show the median and the interquartile range (IQR), and the whiskers denote the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively.

Figure 3:

ConDoR provides insights into the evolution and spatial clonal architecture of a pancreatic ductal adenocarcinoma tumor using scDNA-seq data from two different regions of the tumor. (a) t-SNE plot showing results of clustering (details in the “Methods” section) of cells into 3 clusters (C0, C1 and C2) according to copy number profiles. (b) Constrained 1-Dollo phylogeny computed by ConDoR with edges labeled by the gain or loss of mutations, and vertices labeled by the copy-number cluster and the fraction of cells from samples S1 and S2 that are attached at that vertex. (c) Reduction in normalized total read count for amplicon AMPL257637 (which contains mutations MGMT 1 and MGMT 2) in cells from cluster C2 compared to cells in cluster C1 (p < 5.8×10⁻³³, a one-sided KS test), supporting the loss of these mutations in the cells belonging to copy-number cluster C2. (d) Observed mutation matrix obtained by discretizing read counts of the 7 mutations, with cells grouped by copy number cluster as indicated in the first column. Box plots show the median and the interquartile range (IQR), and the whiskers denote the lowest and highest values within 1.5 times the IQR from the first and third quartiles, respectively.

Figure 4:

ConDoR infers a phylogeny that is consistent with the copy-number clones in a metastatic colorectal cancer dataset. (a) The ConDoR phylogeny shows loss of bridge mutations FHIT and ATP7B, and suggests monoclonal origin of the liver metastasis. (b) Losses inferred by ConDoR are supported by copy-number profiles from whole genome sequencing data of 42 cells from the same patient in the original study [38] (heatmap showing copy-number profiles adapted from [38]). Mutations LRP1B, LINGO2_1 and NR4A3 lie in regions (black boxes) that decrease in copy-number between the clusters that label the vertices on the edge in the phylogeny where the corresponding mutation ((bold text in (a)) is lost : P→M1 for LRP1B and LINGO2_1, and M1→M2 for NR4A3.