Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data.

Dysregulated DNA replication is a cause and a consequence of aneuploidy in cancer, yet the interplay between copy number alterations (CNAs), replication timing (RT) and cell cycle dynamics remain understudied in aneuploid tumors. We developed a probabilistic method, PERT, for simultaneous inference of cell-specific replication and copy number states from single-cell whole genome sequencing (scWGS) data. We used PERT to investigate clone-specific RT and proliferation dynamics in  >50,000 cells obtained from aneuploid and clonally heterogeneous cell lines, xenografts and primary cancers.

Tracking clonal evolution of drug resistance in ovarian cancer patients by exploiting structural variants in cfDNA.

Drug resistance is the major cause of therapeutic failure in high-grade serous ovarian cancer (HGSOC). Yet, the mechanisms by which tumors evolve to drug resistant states remains largely unknown. To address this, we aimed to exploit clone-specific genomic structural variations by combining scaled single-cell whole genome sequencing with longitudinally collected cell-free DNA (cfDNA), enabling clonal tracking before, during and after treatment.

Ongoing genome doubling promotes evolvability and immune dysregulation in ovarian cancer.

Whole-genome doubling (WGD) is a critical driver of tumor development and is linked to drug resistance and metastasis in solid malignancies. Here, we demonstrate that WGD is an ongoing mutational process in tumor evolution. Using single-cell whole-genome sequencing, we measured and modeled how WGD events are distributed across cellular populations within tumors and associated WGD dynamics with properties of genome diversification and phenotypic consequences of innate immunity.

Single-cell mtDNA dynamics in tumors is driven by coregulation of nuclear and mitochondrial genomes.

The extent of cell-to-cell variation in tumor mitochondrial DNA (mtDNA) copy number and genotype, and the phenotypic and evolutionary consequences of such variation, are poorly characterized. Here we use amplification-free single-cell whole-genome sequencing (Direct Library Prep (DLP+)) to simultaneously assay mtDNA copy number and nuclear DNA (nuDNA) in 72,275 single cells derived from immortalized cell lines, patient-derived xenografts and primary human tumors. Cells typically contained thousands of mtDNA copies, but variation in mtDNA copy number was extensive and strongly associated with cell size.

Identification of transcriptional programs using dense vector representations defined by mutual information with GeneVector.

Deciphering individual cell phenotypes from cell-specific transcriptional processes requires high dimensional single cell RNA sequencing. However, current dimensionality reduction methods aggregate sparse gene information across cells, without directly measuring the relationships that exist between genes. By performing dimensionality reduction with respect to gene co-expression, low-dimensional features can model these gene-specific relationships and leverage shared signal to overcome sparsity.

Single-cell DNA replication dynamics in genomically unstable cancers.

Dysregulated DNA replication is both a cause and a consequence of aneuploidy, yet the dynamics of DNA replication in aneuploid cell populations remains understudied. We developed a new method, PERT, for inferring cell-specific DNA replication states from single-cell whole genome sequencing, and investigated clone-specific DNA replication dynamics in >50,000 cells obtained from a collection of aneuploid and clonally heterogeneous cell lines, xenografts and primary cancer tissues. Clone replication timing (RT) profiles correlated with future copy number changes in serially passaged cell lines.

The Search for Genomic Biomarkers of Response to Immunotherapy in Ovarian Cancer.

Immune checkpoint blockade has been ineffective in ovarian cancer, and there is an ongoing effort to identify biomarkers of therapeutic benefit. Despite promising preclinical data, a substudy of the IMagyn050 trial found that patients with homologous recombination deficient tumors did not have improved progression-free survival with the addition of the PD-L1 inhibitor atezolizumab. See related article by Landen et al.

Ovarian cancer mutational processes drive site-specific immune evasion.

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability patterned by distinct mutational processes, tumour heterogeneity and intraperitoneal spread. Immunotherapies have had limited efficacy in HGSOC, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour foci determine the immunological states of the tumour microenvironment. Here we carried out an integrative analysis of whole-genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumour sites from 42 treatment-naive patients with HGSOC.

Single-cell genomic variation induced by mutational processes in cancer.

How cell-to-cell copy number alterations that underpin genomic instability in human cancers drive genomic and phenotypic variation, and consequently the evolution of cancer, remains understudied. Here, by applying scaled single-cell whole-genome sequencing to wild-type, TP53-deficient and TP53-deficient;BRCA1-deficient or TP53-deficient;BRCA2-deficient mammary epithelial cells (13,818 genomes), and to primary triple-negative breast cancer (TNBC) and high-grade serous ovarian cancer (HGSC) cells (22,057 genomes), we identify three distinct 'foreground' mutational patterns that are defined by cell-to-cell structural variation. Cell- and clone-specific high-level amplifications, parallel haplotype-specific copy number alterations and copy number segment length variation (serrate structural variations) had measurable phenotypic and evolutionary consequences.

Resource-efficient pooled sequencing expands translational impact in solid tumors.

Intratumoral genetic heterogeneity (ITH) poses a significant challenge to utilizing sequencing for decision making in the management of cancer. Although sequencing of multiple tumor regions can address the pitfalls of ITH, it does so at a significant increase in cost and resource utilization. We propose a pooled multiregional sequencing strategy, whereby DNA aliquots from multiple tumor regions are mixed prior to sequencing, as a cost-effective strategy to boost translational value by addressing ITH while preserving valuable residual tissue for secondary analysis.

Clonal fitness inferred from time-series modelling of single-cell cancer genomes.

Progress in defining genomic fitness landscapes in cancer, especially those defined by copy number alterations (CNAs), has been impeded by lack of time-series single-cell sampling of polyclonal populations and temporal statistical models. Here we generated 42,000 genomes from multi-year time-series single-cell whole-genome sequencing of breast epithelium and primary triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), revealing the nature of CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy. Using a new Wright-Fisher population genetics model to infer clonal fitness, we found that TP53 mutation alters the fitness landscape, reproducibly distributing fitness over a larger number of clones associated with distinct CNAs.