Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer.

High-grade serous ovarian cancer (HGSC) exhibits extensive malignant clonal diversity with widespread but non-random patterns of disease dissemination. We investigated whether local immune microenvironment factors shape tumor progression properties at the interface of tumor-infiltrating lymphocytes (TILs) and cancer cells. Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. Epithelial CD8+ TILs negatively associated with malignant diversity, reflecting immunological pruning of tumor clones inferred by neoantigen depletion, HLA I loss of heterozygosity, and spatial tracking between T cell and tumor clones. In addition, combinatorial prognostic effects of mutational processes and immune properties were observed, illuminating how specific genomic aberration types associate with immune response and impact survival. We conclude that within-patient spatial immune microenvironment variation shapes intraperitoneal malignant spread, provoking new evolutionary perspectives on HGSC clonal dispersion.

Ovarian cancer mutational processes drive site-specific immune evasion.

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability1-4 patterned by distinct mutational processes5,6, tumour heterogeneity7-9 and intraperitoneal spread7,8,10. Immunotherapies have had limited efficacy in HGSOC11-13, 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 TGFß 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.

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.

Social instability influences rank-specific patterns of oxidative stress in a cichlid fish.

In many animal societies, dominant individuals have priority access to resources. However, defending high rank can be costly, especially in unstable social hierarchies where there is more intense competition. Oxidative stress has been proposed as a potential cost of social dominance, but few studies have examined this cost in relation to social stability. We studied the cost of social dominance in the cichlid fish Astatotilapia burtoni by manipulating social stability among males in replicate naturalistic communities for 22 weeks. We found that our social stability treatment influenced status-specific patterns in 3 out of 6 measurements of oxidative stress. Specifically, dominant males experienced increased plasma oxidative damage (measured as reactive oxygen metabolites, ROMs) compared with subordinate males in stable hierarchies only. Subordinate males in unstable hierarchies had higher ROMs than their stable community counterparts, but we found no effect of social stability treatment for dominant males. However, dominant males tended to have reduced total antioxidant capacity (TAC) in the liver when compared with subordinate males in unstable hierarchies, suggesting that the cost of social dominance is higher in unstable hierarchies. There were no effects of status and treatment on gonad TAC, muscle TAC or oxidative DNA damage. We conclude that the stability of the social environment influences the relative cost of social dominance in a tissue- and marker-specific manner.

Integrated structural variation and point mutation signatures in cancer genomes using correlated topic models.

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.

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. 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.

Enhanced Feature Selection for Microbiome Data using FLORAL: Scalable Log-ratio Lasso Regression.

Identifying predictive biomarkers of patient outcomes from high-throughput microbiome data is of high interest, while existing computational methods do not satisfactorily account for complex survival endpoints, longitudinal samples, and taxa-specific sequencing biases. We present FLORAL (https://vdblab.github.io/FLORAL/), an open-source computational tool to perform scalable log-ratio lasso regression and microbial feature selection for continuous, binary, time-to-event, and competing risk outcomes, with compatibility of longitudinal microbiome data as time-dependent covariates. The proposed method adapts the augmented Lagrangian algorithm for a zero-sum constraint optimization problem while enabling a two-stage screening process for extended false-positive control. In extensive simulation and real-data analyses, FLORAL achieved consistently better false-positive control compared to other lasso-based approaches, and better sensitivity over popular differential abundance testing methods for datasets with smaller sample size. In a survival analysis in allogeneic hematopoietic-cell transplant, we further demonstrated considerable improvement by FLORAL in microbial feature selection by utilizing longitudinal microbiome data over only using baseline microbiome data.

Pilot Trial of Homebound Hematopoietic Cell Transplantation.

For eligible patients with multiple myeloma (MM) and amyloid light chain (AL) amyloidosis, high-dose chemotherapy and autologous hematopoietic cell transplantation (HCT) is a standard and widely used consolidation therapy. Autologous HCT requires specialized care at a transplantation center and investment from patients and caregivers. We studied the safety and feasibility of delivering transplantation care in a homebound setting to decrease the burden of therapy and increase access to autologous HCT. Patients with MM and AL amyloidosis undergoing autologous HCT were eligible if they resided in designated ZIP codes and had a full-time caregiver, Wi-Fi connection, HCT Comorbidity Index ≤3, and Karnofsky Performance Status score ≥80. High-dose melphalan (on day -2) and hematopoietic cell reinfusion (day 0) were administered in the outpatient clinic. Protocol-specific home care was provided from day +1 through engraftment. Patients were assessed and blood was drawn daily by advanced practice providers. Interventions were delivered by registered nurses. Attending physicians communicated daily through telemedicine. Quality of life, patient and caregiver satisfaction, and fecal microbiota profiling data were collected. Fifteen patients were enrolled and received transplantation care at home starting on day +1 following hematopoietic cell infusion. Patients remained in the program for an average of 12 days and required an average of 2 outpatient visits while receiving home care. Seven of 15 patients were admitted for a median of 4 days (range, 3 to 10 days); admission occurred on day +7 in 5 patients, on day +8 in 1 patient, and on day +12 in 1 patient for neutropenic fever in 2 patients, fever attributed to engraftment syndrome in 2 patients, diarrhea in 2 patients, and dehydration in 1 patient. Only 1 patient had a documented infection (Clostridioides difficile). One patient admitted with neutropenic fever required intensive care unit admission for a gastrointestinal bleed. Forty-seven percent of the patients experienced a grade ≥3 nonhematologic toxicity. There were no deaths on the study. Patients and caregivers reported high satisfaction with care. Microbiota diversity patterns were similar to those of autologous HCT recipients who did not receive post-HCT care at home, although a subset of the cohort maintained microbiota diversity throughout. Homebound HCT in an urban setting is safe and feasible, with less than one-half of patients requiring inpatient admission. Despite increased patient and caregiver responsibility in the homebound setting compared with an inpatient setting, patient and caregiver satisfaction was high. These results support expansion of homebound transplantation care programs.

Accurate determination of CRISPR-mediated gene fitness in transplantable tumours.

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.

CLK-dependent exon recognition and conjoined gene formation revealed with a novel small molecule inhibitor.

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.

Systematic analysis of somatic mutations impacting gene expression in 12 tumour types.

We present a novel hierarchical Bayes statistical model, xseq, to systematically quantify the impact of somatic mutations on expression profiles. We establish the theoretical framework and robust inference characteristics of the method using computational benchmarking. We then use xseq to analyse thousands of tumour data sets available through The Cancer Genome Atlas, to systematically quantify somatic mutations impacting expression profiles. We identify 30 novel cis-effect tumour suppressor gene candidates, enriched in loss-of-function mutations and biallelic inactivation. Analysis of trans-effects of mutations and copy number alterations with xseq identifies mutations in 150 genes impacting expression networks, with 89 novel predictions. We reveal two important novel characteristics of mutation impact on expression: (1) patients harbouring known driver mutations exhibit different downstream gene expression consequences; (2) expression patterns for some mutations are stable across tumour types. These results have critical implications for identification and interpretation of mutations with consequent impact on transcription in cancer.