Summary Our knowledge of copy number evolution during the expansion of primary breast tumors is limited 1 , 2 . To investigate this process, we developed a single cell, single-molecule DNA sequencing method and performed copy number analysis of 16,178 single cells from 8 triple-negative breast cancers (TNBCs) and 4 cell lines. Our data shows that breast tumors and cell lines are comprised of a large milieu of subclones (7–22) that are organized into a few (3–5) major superclones. Evolutionary analysis suggests that after clonal TP53 mutations, multiple LOH events and genome doubling, there was a period of transient genomic instability followed by ongoing copy number evolution during the primary tumor expansion. By subcloning single daughter cells in culture, we show that tumor cells re-diversify their genomes and do not retain isogenic properties. These data show that TNBCs continue to evolve chromosome aberrations and maintain a reservoir of subclonal diversity during primary tumor growth.

The functional impact of the vast majority of cancer somatic mutations remains unknown, representing a critical knowledge gap for implementing precision oncology. Here, we report the development of a moderate-throughput functional genomic platform consisting of efficient mutant generation, sensitive viability assays using two growth factor-dependent cell models, and functional proteomic profiling of signaling effects for select aberrations. We apply the platform to annotate >1,000 genomic aberrations, including gene amplifications, point mutations, indels, and gene fusions, potentially doubling the number of driver mutations characterized in clinically actionable genes. Further, the platform is sufficiently sensitive to identify weak drivers. Our data are accessible through a user-friendly, public data portal. Our study will facilitate biomarker discovery, prediction algorithm improvement, and drug development.

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

Liver regeneration is of major clinical importance in the setting of liver injury, resection, and transplantation. A20, a potent anti-inflammatory and NF-κB inhibitory protein, has established pro-proliferative properties in hepatocytes, in part through decreasing expression of the Cyclin Dependent Kinase Inhibitor, p21. Both C-terminal (7-Zinc fingers; 7Zn) and N-terminal (Nter) domains of A20 were required to decrease p21 and inhibit NF-κB. However, both independently increased hepatocyte proliferation, suggesting that additional mechanisms contributed to the pro-proliferative function of A20 in hepatocytes. We ascribed one of A20’s pro-proliferative mechanisms to increased and sustained IL-6 induced STAT3 phosphorylation, as a result of decreased hepatocyte expression of the negative regulator of IL-6 signaling, SOCS3. This novel A20 function segregates with its 7Zn not Nter domain. Conversely, total and partial loss of A20 in hepatocytes increased SOCS3 expression, hampering IL-6-induced STAT3 phosphorylation. Following liver resection in mice pro-proliferative targets downstream of IL-6/STAT3 signaling were increased by A20 overexpression and decreased by A20 knockdown. In contrast, IL-6/STAT3 pro-inflammatory targets were increased in A20 deficient livers, and decreased or unchanged in A20 overexpressing livers. Upstream of SOCS3, levels of its microRNA regulator miR203 were significantly decreased in A20-deficient livers. Altogether these results demonstrate that A20 enhances IL-6/STAT3 pro-proliferative signals in hepatocytes by down-regulating SOCS3, likely through a miR203-dependent manner. This finding together with A20 reducing the levels of the potent cell cycle brake p21 establishes its pro-proliferative properties in hepatocytes and prompts the pursuit of A20-based therapies to promote liver regeneration and repair.

We present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution.The source code of our study is available at https://github.com/KChen-lab/MEDALT.

To improve experimental reproducibility and translational potential of glioma research, it is important to identify the cell of origin, and subsequently apply this knowledge to establish culture conditions that allow the retention of native properties of tumor cells.

Chromosomal instability (CIN) and somatic copy number alterations (SCNA) play a key role in the evolutionary process that shapes cancer genomes. SCNAs comprise many classes of clinically relevant events, such as localised amplifications, gains, losses, loss-of-heterozygosity (LOH) events, and recently discovered parallel evolutionary events revealed by multi-sample phasing. These events frequently appear jointly with whole genome doubling (WGD), a transformative event in tumour evolution, which generates tetraploid or near-tetraploid cells. WGD events are often clonal, occuring before the emergence of the most recent common ancestor, and have been associated with increased CIN, poor patient outcome and are currently being investigated as potential therapeutic targets. While SCNAs can provide a rich source of phylogenetic information, so far no method exists for phylogenetic inference from SCNAs that includes WGD events. Here we present MEDICC2, a new phylogenetic algorithm for allele-specific SCNA data based on a minimum-evolution criterion that explicitly models clonal and subclonal WGD events and that takes parallel evolutionary events into account. MEDICC2 can identify WGD events and quantify SCNA burden in single-sample studies and infer phylogenetic trees and ancestral genomes in multi-sample scenarios. In this scenario, it accurately locates clonal and subclonal WGD events as well as parallel evolutionary events in the evolutionary history of the tumour, timing SCNAs relative to each other. We use MEDICC2 to detect WGD events in 2778 tumours with 98.8% accuracy and show its ability to correctly place subclonal WGD events in simulated and real-world multi-sample tumours, while accurately inferring its phylogeny and parallel SCNA events. MEDICC2 is implemented in Python 3 and freely available under GPLv3 at https://bitbucket.org/schwarzlab/medicc2.

Background: IFN␥ signaling is a major culprit in occlusive vascular disease. Results: The anti-inflammatory protein A20 negatively regulates IFN␥ signaling in vascular cells in vitro and in vivo. Conclusion: A20 impacts IFN␥ signaling by modulating basal IFN␤ and downstream STAT1 expression. Significance: This novel function of A20 supports its promise as a therapeutic target and prognostic marker for atherosclerotic disease.