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

How cell-to-cell copy number alterations that underpin genomic instability1 in human cancers drive genomic and phenotypic variation, and consequently the evolution of cancer2, remains understudied. Here, by applying scaled single-cell whole-genome sequencing3 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. In TNBC and HGSC, clone-specific high-level amplifications in known oncogenes were highly prevalent in tumours bearing fold-back inversions, relative to tumours with homologous recombination deficiency, and were associated with increased clone-to-clone phenotypic variation. Parallel haplotype-specific alterations were also commonly observed, leading to phylogenetic evolutionary diversity and clone-specific mono-allelic expression. Serrate variants were increased in tumours with fold-back inversions and were highly correlated with increased genomic diversity of cellular populations. Together, our findings show that cell-to-cell structural variation contributes to the origins of phenotypic and evolutionary diversity in TNBC and HGSC, and provide insight into the genomic and mutational states of individual cancer cells.

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 models1-7. 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 model8,9 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. Furthermore, in TNBC PDX models with mutated TP53, inferred fitness coefficients from CNA-based genotypes accurately forecast experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDXs resulted in cisplatin-resistant clones emerging from low-fitness phylogenetic lineages in the untreated setting. Conversely, high-fitness clones from treatment-naive controls were eradicated, signalling an inversion of the fitness landscape. Finally, upon release of drug, selection pressure dynamics were reversed, indicating a fitness cost of treatment resistance. Together, our findings define clonal fitness linked to both CNA and therapeutic resistance in polyclonal tumours.

Manipulating disorder within cathodes of alkali-ion batteries.

The fact that ordered materials are rarely perfectly crystalline is widely acknowledged among materials scientists, but its impact is often overlooked or underestimated when studying how structure relates to properties. Various investigations demonstrate that intrinsic and extrinsic defects, and disorder generated by physicochemical reactions, are responsible for unexpectedly detrimental or beneficial functionalities. The task remains to modulate the disorder to produce desired properties in materials. As disorder is often correlated with local interactions, it is controllable. In this Review, we explore the structural disorder in cathode materials as a novel approach for improving their electrochemical performance. We revisit cathode materials for alkali-ion batteries and outline the origins and beneficial consequences of disorder. Focusing on layered, cubic rocksalt and other metal oxides, we discuss how disorder improves electrochemical properties of cathode materials and which interactions generate the disorder. We also present the potential pitfalls of disorder that must be considered. We conclude with perspectives for enhancing the electrochemical performance of cathode materials by using disorder.

A Mechanistic Insight into the Oxygen Redox of Li-Rich Layered Cathodes and their Related Electronic/Atomic Behaviors Upon Cycling.

Li-rich cathodes are extensively investigated as their energy density is superior to Li stoichiometric cathode materials. In addition to the transition metal redox, this intriguing electrochemical performance originates from the redox reaction of the anionic sublattice. This new redox process, the so-called anionic redox or, more directly, oxygen redox in the case of oxides, almost doubles the energy density of Li-rich cathodes compared to conventional cathodes. Numerous theoretical and experimental investigations have thoroughly established the current understanding of the oxygen redox of Li-rich cathodes. However, different reports are occasionally contradictory, indicating that current knowledge remains incomplete. Moreover, several practical issues still hinder the real-world application of Li-rich cathodes. As these issues are related to phenomena resulting from the electronic to atomic evolution induced by unstable oxygen redox, a fundamental multiscale understanding is essential for solving the problem. In this review, the current mechanistic understanding of oxygen redox, the origin of the practical problems, and how current studies tackle the issues are summarized.

Age-correlated protein and transcript expression in breast cancer and normal breast tissues is dominated by host endocrine effects.

The magnitude and scope of intrinsic age-correlated and host endocrine age-correlated gene expression in breast cancer is not well understood. From age-correlated gene expression in 3,071 breast cancer transcriptomes and epithelial protein expression of 42 markers in 5,001 breast cancers and 537 normal breast tissues, we identified a majority of age-correlated genes as putatively regulated by age-dependent estrogen signaling. Surprisingly, these included genes encoding the chromatin modifier EZH2 (which had a negative age correlation) and associated H3K27me3 (which had an inverse, positive age correlation). Among The Cancer Genome Atlas lung, thyroid, kidney and prostate transcriptomes, the largest overlap with breast cancer in age-correlated transcripts was lung cancer, for which about one-third of overlapping age-correlated transcripts appeared to be estrogen regulated. Age-quartile-stratified outcomes analysis of 3,500 breast cancers using EZH2, H3K27me3, FOXA1 and BCL2 proteins revealed distinct age-related prognostic significance. Age correlation in gene expression may thus be an important factor in ER, EZH2, H3K27me3 and other biomarker assessment and treatment strategies.