Disruption of metazoan gene regulatory networks in cancer alters the balance of co-expression between genes of unicellular and multicellular origins.

BACKGROUND: Metazoans inherited genes from unicellular ancestors that perform essential biological processes such as cell division, metabolism, and protein translation. Multicellularity requires careful control and coordination of these unicellular genes to maintain tissue integrity and homeostasis. Gene regulatory networks (GRNs) that arose during metazoan evolution are frequently altered in cancer, resulting in over-expression of unicellular genes. We propose that an imbalance in co-expression of unicellular (UC) and multicellular (MC) genes is a driving force in cancer. RESULTS: We combine gene co-expression analysis to infer changes to GRNs in cancer with protein sequence conservation data to distinguish genes with UC and MC origins. Co-expression networks created using RNA sequencing data from 31 tumor types and normal tissue samples are divided into modules enriched for UC genes, MC genes, or mixed UC-MC modules. The greatest differences between tumor and normal tissue co-expression networks occur within mixed UC-MC modules. MC and UC genes not commonly co-expressed in normal tissues form distinct co-expression modules seen only in tumors. The degree of rewiring of genes within mixed UC-MC modules increases with tumor grade and stage. Mixed UC-MC modules are enriched for somatic mutations in cancer genes, particularly amplifications, suggesting an important driver of the rewiring observed in tumors is copy number changes. CONCLUSIONS: Our study shows the greatest changes to gene co-expression patterns during tumor progression occur between genes of MC and UC origins, implicating the breakdown and rewiring of metazoan gene regulatory networks in cancer development and progression.

A risk-reward examination of sample multiplexing reagents for single cell RNA-Seq.

Single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for understanding cellular heterogeneity and function. However the choice of sample multiplexing reagents can impact data quality and experimental outcomes. In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, across diverse sample types such as human peripheral blood mononuclear cells (PBMCs), mouse embryonic brain and patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We compared multiple demultiplexing algorithms which differed in performance depending on data quality. We find that minor improvements to laboratory workflows such as titration and rapid processing are critical to optimal performance. We also compared the performance of fixed scRNA-Seq kits and highlight the advantages of the Parse Biosciences kit for fragile samples. Highly multiplexed scRNA-Seq experiments require more sequencing resources, therefore we evaluated CRISPR-based destruction of non-informative genes to enhance sequencing value. Our comprehensive analysis provides insights into the selection of appropriate sample multiplexing reagents and protocols for scRNA-Seq experiments, facilitating more accurate and cost-effective studies.

The microtubule inhibitor eribulin demonstrates efficacy in platinum-resistant and refractory high-grade serous ovarian cancer patient-derived xenograft models.

Background: Despite initial response to platinum-based chemotherapy and PARP inhibitor therapy (PARPi), nearly all recurrent high-grade serous ovarian cancer (HGSC) will acquire lethal drug resistance; indeed, ~15% of individuals have de novo platinum-refractory disease. Objectives: To determine the potential of anti-microtubule agent (AMA) therapy (paclitaxel, vinorelbine and eribulin) in platinum-resistant or refractory (PRR) HGSC by assessing response in patient-derived xenograft (PDX) models of HGSC. Design and methods: Of 13 PRR HGSC PDX, six were primary PRR, derived from chemotherapy-naïve samples (one was BRCA2 mutant) and seven were from samples obtained following chemotherapy treatment in the clinic (five were mutant for either BRCA1 or BRCA2 (BRCA1/2), four with prior PARPi exposure), recapitulating the population of individuals with aggressive treatment-resistant HGSC in the clinic. Molecular analyses and in vivo treatment studies were undertaken. Results: Seven out of thirteen PRR PDX (54%) were sensitive to treatment with the AMA, eribulin (time to progressive disease (PD) ⩾100 days from the start of treatment) and 11 out of 13 PDX (85%) derived significant benefit from eribulin [time to harvest (TTH) for each PDX with p < 0.002]. In 5 out of 10 platinum-refractory HGSC PDX (50%) and one out of three platinum-resistant PDX (33%), eribulin was more efficacious than was cisplatin, with longer time to PD and significantly extended TTH (each PDX p < 0.02). Furthermore, four of these models were extremely sensitive to all three AMA tested, maintaining response until the end of the experiment (120d post-treatment start). Despite harbouring secondary BRCA2 mutations, two BRCA2-mutant PDX models derived from heavily pre-treated individuals were sensitive to AMA. PRR HGSC PDX models showing greater sensitivity to AMA had high proliferative indices and oncogene expression. Two PDX models, both with prior chemotherapy and/or PARPi exposure, were refractory to all AMA, one of which harboured the SLC25A40-ABCB1 fusion, known to upregulate drug efflux via MDR1. Conclusion: The efficacy observed for eribulin in PRR HGSC PDX was similar to that observed for paclitaxel, which transformed ovarian cancer clinical practice. Eribulin is therefore worthy of further consideration in clinical trials, particularly in ovarian carcinoma with early failure of carboplatin/paclitaxel chemotherapy.

cellsig plug-in enhances CIBERSORTx signature selection for multidataset transcriptomes with sparse multilevel modelling.

MOTIVATION: The precise characterization of cell-type transcriptomes is pivotal to understanding cellular lineages, deconvolution of bulk transcriptomes, and clinical applications. Single-cell RNA sequencing resources like the Human Cell Atlas have revolutionised cell-type profiling. However, challenges persist due to data heterogeneity and discrepancies across different studies. One limitation of prevailing tools such as CIBERSORTx is their inability to address hierarchical data structures and handle nonoverlapping gene sets across samples, relying on filtering or imputation. RESULTS: Here, we present cellsig, a Bayesian sparse multilevel model designed to improve signature estimation by adjusting data for multilevel effects and modelling for gene-set sparsity. Our model is tailored to large-scale, heterogeneous pseudobulk and bulk RNA sequencing data collections with nonoverlapping gene sets. We tested the performances of cellsig on a novel curated Human Bulk Cell-type Catalogue, which harmonizes 1435 samples across 58 datasets. We show that cellsig significantly enhances cell-type marker gene ranking performance. This approach is valuable for cell-type signature selection, with implications for marker gene validation, single-cell annotation, and deconvolution benchmarks. AVAILABILITY AND IMPLEMENTATION: Codes and the interactive app are available at https://github.com/stemangiola/cellsig; and the database is available at https://doi.org/10.5281/zenodo.7582421.

A Matched Molecular and Clinical Analysis of the Epithelioid Haemangioendothelioma Cohort in the Stafford Fox Rare Cancer Program and Contextual Literature Review.

BACKGROUND: Epithelioid haemangioendothelioma (EHE) is an ultra-rare malignant vascular tumour with a prevalence of 1 per 1,000,000. It is typically molecularly characterised by a WWTR1::CAMTA1 gene fusion in approximately 90% of cases, or a YAP1::TFE3 gene fusion in approximately 10% of cases. EHE cases are typically refractory to therapies, and no anticancer agents are reimbursed for EHE in Australia. METHODS: We report a cohort of nine EHE cases with comprehensive histologic and molecular profiling from the Walter and Eliza Hall Institute of Medical Research Stafford Fox Rare Cancer Program (WEHI-SFRCP) collated via nation-wide referral to the Australian Rare Cancer (ARC) Portal. The diagnoses of EHE were confirmed by histopathological and immunohistochemical (IHC) examination. Molecular profiling was performed using the TruSight Oncology 500 assay, the TruSight RNA fusion panel, whole genome sequencing (WGS), or whole exome sequencing (WES). RESULTS: Molecular analysis of RNA, DNA or both was possible in seven of nine cases. The WWTR1::CAMTA1 fusion was identified in five cases. The YAP1::TFE3 fusion was identified in one case, demonstrating unique morphology compared to cases with the more common WWTR1::CAMTA1 fusion. All tumours expressed typical endothelial markers CD31, ERG, and CD34 and were negative for pan-cytokeratin. Cases with a WWTR1::CAMTA1 fusion displayed high expression of CAMTA1 and the single case with a YAP1::TFE3 fusion displayed high expression of TFE3. Survival was highly variable and unrelated to molecular profile. CONCLUSIONS: This cohort of EHE cases provides molecular and histopathological characterisation and matching clinical information that emphasises the molecular patterns and variable clinical outcomes and adds to our knowledge of this ultra-rare cancer. Such information from multiple studies will advance our understanding, potentially improving treatment options.

Single-cell RNA sequencing captures patient-level heterogeneity and associated molecular phenotypes in breast cancer pleural effusions.

BACKGROUND: Malignant pleural effusions (MPEs) are a common complication of advanced cancers, particularly those adjacent to the pleura, such as lung and breast cancer. The pathophysiology of MPE formation remains poorly understood, and although MPEs are routinely used for the diagnosis of breast cancer patients, their composition and biology are poorly understood. It is difficult to distinguish invading malignant cells from resident mesothelial cells and to identify the directionality of interactions between these populations in the pleura. There is a need to characterize the phenotypic diversity of breast cancer cell populations in the pleural microenvironment, and investigate how this varies across patients. METHODS: Here, we used single-cell RNA-sequencing to study the heterogeneity of 10 MPEs from seven metastatic breast cancer patients, including three Miltenyi-enriched samples using a negative selection approach. This dataset of almost 65 000 cells was analysed using integrative approaches to compare heterogeneous cell populations and phenotypes. RESULTS: We identified substantial inter-patient heterogeneity in the composition of cell types (including malignant, mesothelial and immune cell populations), in expression of subtype-specific gene signatures and in copy number aberration patterns, that captured variability across breast cancer cell populations. Within individual MPEs, we distinguished mesothelial cell populations from malignant cells using key markers, the presence of breast cancer subtype expression patterns and copy number aberration patterns. We also identified pleural mesothelial cells expressing a cancer-associated fibroblast-like transcriptomic program that may support cancer growth. CONCLUSIONS: Our dataset presents the first unbiased assessment of breast cancer-associated MPEs at a single cell resolution, providing the community with a valuable resource for the study of MPEs. Our work highlights the molecular and cellular diversity captured in MPEs and motivates the potential use of these clinically relevant biopsies in the development of targeted therapeutics for patients with advanced breast cancer.

sccomp: Robust differential composition and variability analysis for single-cell data.

Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and microbial community composition, which can be compared between conditions to identify biological drivers. This strategy has been critical to revealing markers of disease progression, such as cancer and pathogen infection. A dedicated statistical method for differential variability analysis is lacking for cellular omics data, and existing methods for differential composition analysis do not model some compositional data properties, suggesting there is room to improve model performance. Here, we introduce sccomp, a method for differential composition and variability analyses that jointly models data count distribution, compositionality, group-specific variability, and proportion mean-variability association, being aware of outliers. sccomp provides a comprehensive analysis framework that offers realistic data simulation and cross-study knowledge transfer. Here, we demonstrate that mean-variability association is ubiquitous across technologies, highlighting the inadequacy of the very popular Dirichlet-multinomial distribution. We show that sccomp accurately fits experimental data, significantly improving performance over state-of-the-art algorithms. Using sccomp, we identified differential constraints and composition in the microenvironment of primary breast cancer.

A systematic review of computational methods for designing efficient guides for CRISPR DNA base editor systems.

In only a few years, as a breakthrough technology, clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas) gene-editing systems have ushered in the era of genome engineering with a plethora of applications. One of the most promising CRISPR tools, so-called base editors, opened an exciting avenue for exploring new therapeutic approaches through controlled mutagenesis. However, the efficiency of a base editor guide varies depending on several biological determinants, such as chromatin accessibility, DNA repair proteins, transcriptional activity, factors related to local sequence context and so on. Thus, the success of genetic perturbation directed by CRISPR/Cas base-editing systems relies on an optimal single guide RNA (sgRNA) design, taking those determinants into account. Although there is 11 commonly used software to design guides specifically for base editors, only three of them investigated and implemented those biological determinants into their models. This review presents the key features, capabilities and limitations of all currently available software with a particular focus on predictive model-based algorithms. Here, we summarize existing software for sgRNA design and provide a base for improving the efficiency of existing available software suites for precise target base editing.

Taurine deficiency as a driver of aging.

Aging is associated with changes in circulating levels of various molecules, some of which remain undefined. We find that concentrations of circulating taurine decline with aging in mice, monkeys, and humans. A reversal of this decline through taurine supplementation increased the health span (the period of healthy living) and life span in mice and health span in monkeys. Mechanistically, taurine reduced cellular senescence, protected against telomerase deficiency, suppressed mitochondrial dysfunction, decreased DNA damage, and attenuated inflammaging. In humans, lower taurine concentrations correlated with several age-related diseases and taurine concentrations increased after acute endurance exercise. Thus, taurine deficiency may be a driver of aging because its reversal increases health span in worms, rodents, and primates and life span in worms and rodents. Clinical trials in humans seem warranted to test whether taurine deficiency might drive aging in humans.

Targeting homologous recombination deficiency in uterine leiomyosarcoma.

BACKGROUND: Uterine leiomyosarcoma (uLMS) is a rare and aggressive gynaecological malignancy, with individuals with advanced uLMS having a five-year survival of < 10%. Mutations in the homologous recombination (HR) DNA repair pathway have been observed in ~ 10% of uLMS cases, with reports of some individuals benefiting from poly (ADP-ribose) polymerase (PARP) inhibitor (PARPi) therapy, which targets this DNA repair defect. In this report, we screened individuals with uLMS, accrued nationally, for mutations in the HR repair pathway and explored new approaches to therapeutic targeting. METHODS: A cohort of 58 individuals with uLMS were screened for HR Deficiency (HRD) using whole genome sequencing (WGS), whole exome sequencing (WES) or NGS panel testing. Individuals identified to have HRD uLMS were offered PARPi therapy and clinical outcome details collected. Patient-derived xenografts (PDX) were generated for therapeutic targeting. RESULTS: All 13 uLMS samples analysed by WGS had a dominant COSMIC mutational signature 3; 11 of these had high genome-wide loss of heterozygosity (LOH) (> 0.2) but only two samples had a CHORD score > 50%, one of which had a homozygous pathogenic alteration in an HR gene (deletion in BRCA2). A further three samples harboured homozygous HRD alterations (all deletions in BRCA2), detected by WES or panel sequencing, with 5/58 (9%) individuals having HRD uLMS. All five individuals gained access to PARPi therapy. Two of three individuals with mature clinical follow up achieved a complete response or durable partial response (PR) with the subsequent addition of platinum to PARPi upon minor progression during initial PR on PARPi. Corresponding PDX responses were most rapid, complete and sustained with the PARP1-specific PARPi, AZD5305, compared with either olaparib alone or olaparib plus cisplatin, even in a paired sample of a BRCA2-deleted PDX, derived following PARPi therapy in the patient, which had developed PARPi-resistance mutations in PRKDC, encoding DNA-PKcs. CONCLUSIONS: Our work demonstrates the value of identifying HRD for therapeutic targeting by PARPi and platinum in individuals with the aggressive rare malignancy, uLMS and suggests that individuals with HRD uLMS should be included in trials of PARP1-specific PARPi.

Synthetic Epigenetic Reprogramming of Mesenchymal to Epithelial States Using the CRISPR/dCas9 Platform in Triple Negative Breast Cancer.

Epithelial-mesenchymal transition (EMT) is a reversible transcriptional program invoked by cancer cells to drive cancer progression. Transcription factor ZEB1 is a master regulator of EMT, driving disease recurrence in poor-outcome triple negative breast cancers (TNBCs). Here, this work silences ZEB1 in TNBC models by CRISPR/dCas9-mediated epigenetic editing, resulting in highly-specific and nearly complete suppression of ZEB1 in vivo, accompanied by long-lasting tumor inhibition. Integrated "omic" changes promoted by dCas9 linked to the KRAB domain (dCas9-KRAB) enabled the discovery of a ZEB1-dependent-signature of 26 genes differentially-expressed and -methylated, including the reactivation and enhanced chromatin accessibility in cell adhesion loci, outlining epigenetic reprogramming toward a more epithelial state. In the ZEB1 locus transcriptional silencing is associated with induction of locally-spread heterochromatin, significant changes in DNA methylation at specific CpGs, gain of H3K9me3, and a near complete erasure of H3K4me3 in the ZEB1 promoter. Epigenetic shifts induced by ZEB1-silencing are enriched in a subset of human breast tumors, illuminating a clinically-relevant hybrid-like state. Thus, the synthetic epi-silencing of ZEB1 induces stable "lock-in" epigenetic reprogramming of mesenchymal tumors associated with a distinct and stable epigenetic landscape. This work outlines epigenome-engineering approaches for reversing EMT and customizable precision molecular oncology approaches for targeting poor outcome breast cancers.

ahctf1 and kras mutations combine to amplify oncogenic stress and restrict liver overgrowth in a zebrafish model of hepatocellular carcinoma.

The nucleoporin (NUP) ELYS, encoded by AHCTF1, is a large multifunctional protein with essential roles in nuclear pore assembly and mitosis. Using both larval and adult zebrafish models of hepatocellular carcinoma (HCC), in which the expression of an inducible mutant kras transgene (krasG12V) drives hepatocyte-specific hyperplasia and liver enlargement, we show that reducing ahctf1 gene dosage by 50% markedly decreases liver volume, while non-hyperplastic tissues are unaffected. We demonstrate that in the context of cancer, ahctf1 heterozygosity impairs nuclear pore formation, mitotic spindle assembly, and chromosome segregation, leading to DNA damage and activation of a Tp53-dependent transcriptional programme that induces cell death and cell cycle arrest. Heterozygous expression of both ahctf1 and ranbp2 (encoding a second nucleoporin), or treatment of heterozygous ahctf1 larvae with the nucleocytoplasmic transport inhibitor, Selinexor, completely blocks krasG12V-driven hepatocyte hyperplasia. Gene expression analysis of patient samples in the liver hepatocellular carcinoma (LIHC) dataset in The Cancer Genome Atlas shows that high expression of one or more of the transcripts encoding the 10 components of the NUP107-160 subcomplex, which includes AHCTF1, is positively correlated with worse overall survival. These results provide a strong and feasible rationale for the development of novel cancer therapeutics that target ELYS function and suggest potential avenues for effective combinatorial treatments.

Removing unwanted variation from large-scale RNA sequencing data with PRPS.

Accurate identification and effective removal of unwanted variation is essential to derive meaningful biological results from RNA sequencing (RNA-seq) data, especially when the data come from large and complex studies. Using RNA-seq data from The Cancer Genome Atlas (TCGA), we examined several sources of unwanted variation and demonstrate here how these can significantly compromise various downstream analyses, including cancer subtype identification, association between gene expression and survival outcomes and gene co-expression analysis. We propose a strategy, called pseudo-replicates of pseudo-samples (PRPS), for deploying our recently developed normalization method, called removing unwanted variation III (RUV-III), to remove the variation caused by library size, tumor purity and batch effects in TCGA RNA-seq data. We illustrate the value of our approach by comparing it to the standard TCGA normalizations on several TCGA RNA-seq datasets. RUV-III with PRPS can be used to integrate and normalize other large transcriptomic datasets coming from multiple laboratories or platforms.

Epithelial-to-Mesenchymal Transition Supports Ovarian Carcinosarcoma Tumorigenesis and Confers Sensitivity to Microtubule Targeting with Eribulin.

Ovarian carcinosarcoma (OCS) is an aggressive and rare tumor type with limited treatment options. OCS is hypothesized to develop via the combination theory, with a single progenitor resulting in carcinomatous and sarcomatous components, or alternatively via the conversion theory, with the sarcomatous component developing from the carcinomatous component through epithelial-to-mesenchymal transition (EMT). In this study, we analyzed DNA variants from isolated carcinoma and sarcoma components to show that OCS from 18 women is monoclonal. RNA sequencing indicated that the carcinoma components were more mesenchymal when compared with pure epithelial ovarian carcinomas, supporting the conversion theory and suggesting that EMT is important in the formation of these tumors. Preclinical OCS models were used to test the efficacy of microtubule-targeting drugs, including eribulin, which has previously been shown to reverse EMT characteristics in breast cancers and induce differentiation in sarcomas. Vinorelbine and eribulin more effectively inhibited OCS growth than standard-of-care platinum-based chemotherapy, and treatment with eribulin reduced mesenchymal characteristics and N-MYC expression in OCS patient-derived xenografts. Eribulin treatment resulted in an accumulation of intracellular cholesterol in OCS cells, which triggered a downregulation of the mevalonate pathway and prevented further cholesterol biosynthesis. Finally, eribulin increased expression of genes related to immune activation and increased the intratumoral accumulation of CD8+ T cells, supporting exploration of immunotherapy combinations in the clinic. Together, these data indicate that EMT plays a key role in OCS tumorigenesis and support the conversion theory for OCS histogenesis. Targeting EMT using eribulin could help improve OCS patient outcomes. SIGNIFICANCE: Genomic analyses and preclinical models of ovarian carcinosarcoma support the conversion theory for disease development and indicate that microtubule inhibitors could be used to suppress EMT and stimulate antitumor immunity.

A G358S mutation in the Plasmodium falciparum Na+ pump PfATP4 confers clinically-relevant resistance to cipargamin.

Diverse compounds target the Plasmodium falciparum Na+ pump PfATP4, with cipargamin and (+)-SJ733 the most clinically-advanced. In a recent clinical trial for cipargamin, recrudescent parasites emerged, with most having a G358S mutation in PfATP4. Here, we show that PfATP4G358S parasites can withstand micromolar concentrations of cipargamin and (+)-SJ733, while remaining susceptible to antimalarials that do not target PfATP4. The G358S mutation in PfATP4, and the equivalent mutation in Toxoplasma gondii ATP4, decrease the sensitivity of ATP4 to inhibition by cipargamin and (+)-SJ733, thereby protecting parasites from disruption of Na+ regulation. The G358S mutation reduces the affinity of PfATP4 for Na+ and is associated with an increase in the parasite's resting cytosolic [Na+]. However, no defect in parasite growth or transmissibility is observed. Our findings suggest that PfATP4 inhibitors in clinical development should be tested against PfATP4G358S parasites, and that their combination with unrelated antimalarials may mitigate against resistance development.

Genome-wide interrogation of structural variation reveals novel African-specific prostate cancer oncogenic drivers.

BACKGROUND: African ancestry is a significant risk factor for advanced prostate cancer (PCa). Mortality rates in sub-Saharan Africa are 2.5-fold greater than global averages. However, the region has largely been excluded from the benefits of whole genome interrogation studies. Additionally, while structural variation (SV) is highly prevalent, PCa genomic studies are still biased towards small variant interrogation. METHODS: Using whole genome sequencing and best practice workflows, we performed a comprehensive analysis of SVs for 180 (predominantly Gleason score ≥ 8) prostate tumours derived from 115 African, 61 European and four ancestrally admixed patients. We investigated the landscape and relationship of somatic SVs in driving ethnic disparity (African versus European), with a focus on African men from southern Africa. RESULTS: Duplication events showed the greatest ethnic disparity, with a 1.6- (relative frequency) to 2.5-fold (count) increase in African-derived tumours. Furthermore, we found duplication events to be associated with CDK12 inactivation and MYC copy number gain, and deletion events associated with SPOP mutation. Overall, African-derived tumours were 2-fold more likely to present with a hyper-SV subtype. In addition to hyper-duplication and deletion subtypes, we describe a new hyper-translocation subtype. While we confirm a lower TMPRSS2-ERG fusion-positive rate in tumours from African cases (10% versus 33%), novel African-specific PCa ETS family member and TMPRSS2 fusion partners were identified, including LINC01525, FBXO7, GTF3C2, NTNG1 and YPEL5. Notably, we found 74 somatic SV hotspots impacting 18 new candidate driver genes, with CADM2, LSAMP, PTPRD, PDE4D and PACRG having therapeutic implications for African patients. CONCLUSIONS: In this first African-inclusive SV study for high-risk PCa, we demonstrate the power of SV interrogation for the identification of novel subtypes, oncogenic drivers and therapeutic targets. Identifying a novel spectrum of SVs in tumours derived from African patients provides a mechanism that may contribute, at least in part, to the observed ethnic disparity in advanced PCa presentation in men of African ancestry.

Tissue-resident memory T cells from a metastatic vaginal melanoma patient are tumor-responsive T cells and increase after anti-PD-1 treatment.

BACKGROUND: Vaginal melanoma (VM) is a rare cancer and has a poor response to immune checkpoint blockade (ICB). CD8+Tissue Resident Memory (TRM) T cells proliferate in response to ICB and correlate with longer survival in metastatic cutaneous melanoma. However, their capacity to respond to VM and their neoantigens is not known. METHODS: Using longitudinal samples, we explored the evolution of VM mutations by whole-exome sequencing and RNAseq, we also defined the immune context using multiplex immunohistochemistry and nanostring pan cancer immune profile. Then using fresh single cell suspensions of the metastatic samples, we explored VM T cells via mass cytometry and single cell RNAseq and T cell receptor sequencing (TCRseq). Finally, we investigated TRM, pre-TRM and exhausted T cell function against melanoma neo-antigens and melanoma differentiation antigens in vitro. RESULTS: Primary VM was non-inflamed and devoid of CD8+ TRM cells. In contrast, both metastases showed proliferating CD8+ TRM were clustered at the tumor margin, with increased numbers in the second ICB-refractory metastasis. The first metastasis showed dense infiltration of CD8+ T cells, the second showed immune exclusion with loss of melanoma cell Major histocompatibility complex (MHC)-I expression associated with downregulation of antigen presentation pathway gene expression. CD8+ TRM from both metastases responded to autologous melanoma cells more robustly than all other CD8+ T cell subsets. In addition, CD8+ TRM shared TCR clones across metastases, suggesting a response to common antigens, which was supported by recognition of the same neoantigen by expanded tumor infiltrating lymphocytes. CONCLUSIONS: In this study, we identified TRM clusters in VM metastases from a patient, but not primary disease. We showed TRM location at the tumor margin, and their superior functional response to autologous tumor cells, predicted neoantigens and melanoma differentiation antigens. These CD8+ TRM exhibited the highest tumor-responsive potential and shared their TCR with tumor-infiltrating effector memory T cells. This suggests VM metastases from this patient retain strong antitumor T cell functional responses; however, this response is suppressed in vivo. The loss of VG MHC-I expression is a common immune escape mechanism which was not addressed by anti-PD-1 monotherapy; rather an additional targeted approach to upregulate MHC-I expression is required.

StructuralVariantAnnotation: a R/Bioconductor foundation for a caller-agnostic structural variant software ecosystem.

SUMMARY: StructuralVariantAnnotation is an R/Bioconductor package that provides a framework for decoupling downstream analysis of structural variant breakpoints from upstream variant calling methods. It standardizes the representational format from BEDPE, or any of the three different notations supported by VCF into a breakpoint GRanges data structure suitable for use by the wider Bioconductor ecosystem. It handles both transitive breakpoints and duplication/insertion notational differences of identical variants-both common scenarios when comparing short/long read-based call sets that confound downstream analysis. StructuralVariantAnnotation provides the caller-agnostic foundation needed for a R/Bioconductor ecosystem of structural variant annotation, classification and interpretation tools able to handle both simple and complex genomic rearrangements. AVAILABILITY AND IMPLEMENTATION: StructuralVariantAnnotation is implemented in R and available for download as the Bioconductor StructuralVariantAnnotation package. Details can be found at https://www.bioconductor.org/packages/release/bioc/html/StructuralVariantAnnotation.html. It has been released under a GPL license.

Women with type 1 diabetes exhibit a progressive increase in gut Saccharomyces cerevisiae in pregnancy associated with evidence of gut inflammation.

AIMS: Studies of the gut microbiome have focused on its bacterial composition. We aimed to characterize the gut fungal microbiome (mycobiome) across pregnancy in women with and without type 1 diabetes. METHODS: Faecal samples (n = 162) were collected from 70 pregnant women (45 with and 25 without type 1 diabetes) across all trimesters. Fungi were analysed by internal transcribed spacer 1 amplicon sequencing. Markers of intestinal inflammation (faecal calprotectin) and intestinal epithelial integrity (serum intestinal fatty acid binding protein; I-FABP), and serum antibodies to Saccharomyces cerevisiae (ASCA) were measured. RESULTS: Women with type 1 diabetes had decreased fungal alpha diversity by the third trimester, associated with an increased abundance of Saccharomyces cerevisiae that was inversely related to the abundance of the anti-inflammatory butyrate-producing bacterium Faecalibacterium prausnitzii. Women with type 1 diabetes had higher concentrations of calprotectin, I-FABP and ASCA. CONCLUSIONS: Women with type 1 diabetes exhibit a shift in the gut mycobiome across pregnancy associated with evidence of gut inflammation and impaired intestinal barrier function. The relevance of these findings to the higher rate of pregnancy complications in type 1 diabetes warrants further study.