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Mutation signatures in cancer genomes reflect endogenous and exogenous mutational processes, offering insights into tumour etiology, features for prognostic and biologic stratification and vulnerabilities to be exploited therapeutically. We present a novel machine learning formalism for improved signature inference, based on multi-modal correlated topic models (MMCTM) which can at once infer signatures from both single nucleotide and structural variation counts derived from cancer genome sequencing data. We exemplify the utility of our approach on two hormone driven, DNA repair deficient cancers: breast and ovary (n = 755 samples total). We show how introducing correlated structure both within and between modes of mutation can increase accuracy of signature discovery, particularly in the context of sparse data. Our study emphasizes the importance of integrating multiple mutation modes for signature discovery and patient stratification, and provides a statistical modeling framework to incorporate additional features of interest for future studies.

Studies involving acoustic telemetry typically use stationary acoustic receivers arranged in an array or grid. Unmanned surface vehicle (USV)-based mobile receivers offer advantages over the latter approach: the USV can be programmed to autonomously carry a receiver to and from target locations, more readily adapting to a survey’s spatial scope and scale. This work examines the acoustic detection performance of a low-cost USV developed as a flexible sensing platform. The USV was fitted with an acoustic receiver and operated over multiple waypoints set at increasing distances from the transmitter in two modes: drifting and station-keeping. While drifting, the USV was allowed to drift from the waypoint; while station-keeping, the USV used its thruster to hold position. Detection performance of the USV was similar to that of stationary receivers while drifting, but significantly worse while station-keeping. Noise from the USV thruster was hypothesized as a potential cause of poor detection performance during station-keeping. Detection performance varied with the depth of the tethered receiver such that detection range was greater during the deepest (4.6 m) trials than during shallower (1.1 and 2.9 m) trials. These results provide insight and guidance on how a USV can be best used for acoustic telemetry, namely, navigating to a planned waypoint, drifting and lowering the receiver to a desired depth for listening, and then navigating to the next waypoint.

Assessing tumour gene fitness in physiologically-relevant model systems is challenging due to biological features of in vivo tumour regeneration, including extreme variations in single cell lineage progeny. Here we develop a reproducible, quantitative approach to pooled genetic perturbation in patient-derived xenografts (PDXs), by encoding single cell output from transplanted CRISPR-transduced cells in combination with a Bayesian hierarchical model. We apply this to 181 PDX transplants from 21 breast cancer patients. We show that uncertainty in fitness estimates depends critically on the number of transplant cell clones and the variability in clone sizes. We use a pathway-directed allelic series to characterize Notch signaling, and quantify TP53 / MDM2 drug-gene conditional fitness in outlier patients. We show that fitness outlier identification can be mirrored by pharmacological perturbation. Overall, we demonstrate that the gene fitness landscape in breast PDXs is dominated by inter-patient differences. Gene fitness and essentiality analyses using in vivo cancer models are challenging due to multiple confounders. Here, the authors develop a quantitative approach to study CRISPR-transduced patient-derived xenografts, which they use to analyse in vivo gene fitness in breast cancers and the biological features that influence uncertainty in fitness estimation.

In many haplochromine cichlids, body coloration is an important communication cue during social interactions. In some cichlids, individuals can change color, but we have little information about the underlying physiological mechanisms. We examined the regulation of coloration in the color polymorphic cichlid fish Astatotilapia burtoni where males are either blue or yellow. Previous studies implicated the melanocortin system, a neuroendocrine center that regulates pigmentation and the stress response, in regulating the color polymorphism in this species. We found that both blue and yellow males express a high density of yellow xanthophores. Dispersal of xanthophore pigments in both yellow and blue morphs occurred within minutes in a dose-dependent manner. Similarly, exogenous α-melanocyte stimulating hormone (α-MSH, a melanocortin hormone) increased yellowness of the body in a dose-independent fashion. We observed many color changes in males housed in social communities with the proportion of yellow males increasing over the 2-week experimental period. However, color phenotype or color change was not influenced by experimental alteration of the stability of the social hierarchy. The effects of α-MSH suggest that the melanocortin system contributes to the polymorphism in coloration in A. burtoni but the role of social interactions and social stress in regulating color remains unclear.

CDC-like kinase phosphorylation of serine/arginine-rich proteins is central to RNA splicing reactions. Yet, the genomic network of CDC-like kinase-dependent RNA processing events remains poorly defined. Here, we explore the connectivity of genomic CDC-like kinase splicing functions by applying graduated, short-exposure, pharmacological CDC-like kinase inhibition using a novel small molecule (T3) with very high potency, selectivity, and cell-based stability. Using RNA-Seq, we define CDC-like kinase-responsive alternative splicing events, the large majority of which monotonically increase or decrease with increasing CDC-like kinase inhibition. We show that distinct RNA-binding motifs are associated with T3 response in skipped exons. Unexpectedly, we observe dose-dependent conjoined gene transcription, which is associated with motif enrichment in the last and second exons of upstream and downstream partners, respectively. siRNA knockdown of CLK2-associated genes significantly increases conjoined gene formation. Collectively, our results reveal an unexpected role for CDC-like kinase in conjoined gene formation, via regulation of 3′-end processing and associated splicing factors. The phosphorylation of serine/arginine-rich proteins by CDC-like kinase is a central regulatory mechanism for RNA splicing reactions. Here, the authors synthesize a novel small molecule CLK inhibitor and map CLK-responsive alternative splicing events and discover an effect on conjoined gene transcription.

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability 1 – 4 patterned by distinct mutational processes 5 , 6 , tumour heterogeneity 7 – 9 and intraperitoneal spread 7 , 8 , 10 . Immunotherapies have had limited efficacy in HGSOC 11 – 13 , 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. Homologous recombination-deficient HRD-Dup ( BRCA1 mutant-like) and HRD-Del ( BRCA2 mutant-like) tumours harboured inflammatory signalling and ongoing immunoediting, reflected in loss of HLA diversity and tumour infiltration with highly differentiated dysfunctional CD8 + T cells. By contrast, foldback-inversion-bearing tumours exhibited elevated immunosuppressive TGFβ signalling and immune exclusion, with predominantly naive/stem-like and memory T cells. Phenotypic state associations were specific to anatomical sites, highlighting compositional, topological and functional differences between adnexal tumours and distal peritoneal foci. Our findings implicate anatomical sites and mutational processes as determinants of evolutionary phenotypic divergence and immune resistance mechanisms in HGSOC. Our study provides a multi-omic cellular phenotype data substrate from which to develop and interpret future personalized immunotherapeutic approaches and early detection research. Multi-modal analysis of genomically unstable ovarian tumours characterizes the contribution of anatomical sites and mutational processes to evolutionary phenotypic divergence and immune resistance mechanisms.

How cell-to-cell copy number alterations that underpin genomic instability 1 in human cancers drive genomic and phenotypic variation, and consequently the evolution of cancer 2 , remains understudied. Here, by applying scaled single-cell whole-genome sequencing 3 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. Single-cell whole-genome sequencing shows that 'foreground' cell-to-cell structural variation and alterations in copy number are associated with genomic diversity and evolution in triple-negative breast and high-grade serous ovarian cancers.

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. Pervasive whole-genome doubling events in nuDNA associated with stoichiometrically balanced adaptations in mtDNA copy number, implying that mtDNA-to-nuDNA ratio, rather than mtDNA copy number itself, mediated downstream phenotypes. Finally, multimodal analysis of DLP+ and single-cell RNA sequencing identified both somatic loss-of-function and germline noncoding variants in mtDNA linked to heteroplasmy-dependent changes in mtDNA copy number and mitochondrial transcription, revealing phenotypic adaptations to disrupted nuclear/mitochondrial balance. Amplification-free single-cell whole-genome sequencing shows that genomic, evolutionary and biophysical factors collectively drive cell-to-cell variation in mitochondrial DNA copy number.

Disease progression is a substantial challenge in patients with non-Hodgkin lymphoma (NHL) undergoing chimeric antigen receptor T cell (CAR-T) therapy. Here we present InflaMix (INFLAmmation MIXture Model), an unsupervised quantitative model integrating 14 pre-CAR-T infusion laboratory and cytokine measures capturing inflammation and end-organ function. Developed using a cohort of 149 patients with NHL, InflaMix revealed an inflammatory signature associated with a high risk of CAR-T treatment failure, including increased hazard of death or relapse (hazard ratio, 2.98; 95% confidence interval, 1.60–4.91; P  < 0.001). Three independent cohorts comprising 688 patients with NHL from diverse treatment centers were used to validate our approach. InflaMix consistently and reproducibly identified patients with a higher likelihood of disease relapse and mortality, and it provided supplementary predictive value beyond established prognostic markers, including tumor burden. Moreover, InflaMix exhibited robust performance in cases with missing data, maintaining accuracy when considering only six readily available laboratory measures. These findings show that InflaMix is a valuable tool for point-of-care clinical decision-making in patients with NHL undergoing CAR-T therapy. A preinfusion circulatory inflammation biomarker-based signature predicts the likelihood of treatment failure in patients with non-Hodgkin lymphoma who were treated with CAR-T cell therapy, with an inflammatory cluster assignment being prognostic of clinical response and survival outcomes.

Over time, cancer genomes accumulate mutations from various sources. Some mutations result from exogenous mutagens, such as UV radiation, while others reflect endogenous processes. Each source can impart characteristic patterns of mutation – mutation signatures – which can be detected using computational techniques. Loss of DNA repair mechanisms can leave specific mutation signatures in cancer cells, offering insights into tumour etiology, features for prognostic and biologic stratification and vulnerabilities to be exploited therapeutically. Whole genome sequencing methods enable detection of the full catalogue of mutations in a genome, facilitating signature discovery. To identify cancers with deficient DNA-repair, accurate methods are needed for detecting mutation signatures and their activities within individual cancers. We introduce a class of methods, topic models, that outperform standard approaches for signature analysis. We highlight a particular novel formalism for improved signature inference, based on multi-modal correlated topic models, which can at once infer signatures from both single nucleotide and structural variation counts. We show how introducing correlated structure both within and between modes of mutation can increase accuracy of signature discovery. Using 943 breast and ovarian cancers, we refine the landscape of point and structural variation signatures in these histotypes, and describe the previously poorly-understood correspondence between mutational processes in high grade serous ovarian cancer and triple negative breast cancer. We further show how mutational processes stratify these patients into clinically relevant subgroups. Our results emphasize the need to achieve a detailed picture of the historical and ongoing impacts of mutational processes in these cancers. With >26,000 single cell genomes from a subset of these cancers, we map the copy number variation properties of DNA repair deficiency with unprecedented detail. In a controlled experiment, we show that DNA repair-deficient cells have increased rates of aneuploidy and micronuclei formation. We also show that FBI and HRD cancer cells are significantly affected by different kinds of genomic instability, and describe the cell-to-cell variability of copy number breakpoints for the first time in cancer cells. Our results illustrate how mutational processes can significantly impact the manner in which genomic architectures are continually altered, and impinge upon tumour evolution.