Abstract Treatment-induced neuroendocrine prostate cancer (t-NEPC) is a lethal form of castration-resistant variant arising primarily through neuroendocrine (NE) transdifferentiation of prostate adenocarcinoma following androgen deprivation therapy (ADT) and androgen receptor pathway inhibitors (ARPI). Despite its clinical relevance, the early molecular events initiating this transition remain poorly defined. Leveraging the first and only longitudinal patient-derived xenograft (PDX) model capturing adenocarcinoma-to-NEPC transdifferentiation (LTL331/331R), we performed single-cell RNA sequencing (scRNA-seq) across seven key stages spanning pre-castration, post-castration/ transitional phases, and relapsed NEPC.Clustering analysis identified 15 major cell populations and revealed a previously unrecognized intermediate transitional cell state enriched for epithelial-mesenchymal transition (EMT), stemness, metabolic activity, and HDAC-related regulatory signatures, highlighting a unique window of lineage plasticity. Two terminal NEPC subclusters with reciprocal ASCL1/FOXA2 expression patterns reflected intratumoral heterogeneity at relapse.Transcriptional interrogation of the transitional population identified RUNX1T1 as a central regulator emerging early during plasticity. Functional assays revealed that RUNX1T1 overexpression markedly accelerates AR pathway inhibition-induced NE transdifferentiation and confers resistance to ARPI therapy in prostate adenocarcinoma models. Conversely, RUNX1T1 knockdown reduces NE-related pathway expression, suppresses NEPC cell growth, and induces apoptosis. These findings position RUNX1T1 as an essential factor for both NEPC development and progression.Mechanistically, rapid immunoprecipitation and mass spectrometry (RIME) uncovered that RUNX1T1 interacts with multiple repressive epigenetic factors including HDAC-containing complexes and heterochromatin-related genes. These results support a role for RUNX1T1 in mediating transcriptional silencing and regulatory network reprogramming during NEPC development.In summary, this study delineates the temporal evolution of t-NEPC at single-cell resolution, identifies an intermediate transitional state during NE transdifferentiation, and reveals heterogeneity within terminal NEPC. The identification of RUNX1T1 as an early and persistent driver of this trajectory positions RUNX1T1 and its associated repressive complexes as promising candidates for therapeutic intervention. Citation Format: Yuchao Ni, Mingchen Shi, Dong Lin, Yen-Yi Lin, Hui Xue, Xin Dong, Liangliang Liu, Funda Sar, Rebecca Wu, Tunc Morova, Anne Hargert, Robert Bell, Xinyao Pang, Adam Classen, Yu Wang, Junru Chen, Stephan Le Bihan, Wei Dong, Vickie Wang, Ning Xu, Nathan Lack, Martin E. Gleave, Christopher J. Ong, Gang Wang, Hao Zeng, Colin Collins, Yuzhuo Wang. RUNX1T1 as an early driver in treatment-induced neuroendocrine transdifferentiation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7249.

It is becoming increasingly recognized that high-level spinal cord injury (SCI) is associated with altered heart structure and function, as well as a significantly elevated risk for heart disease. Despite this knowledge, we know remarkably little about the temporal molecular changes that occur in the heart following SCI and how these relate to functional decline. In the present study, we addressed this shortcoming by combining bulk RNA sequencing (RNA-seq) of left ventricle (LV) tissue with matching in vivo cardiac function assessments (i.e., pressure-volume loops obtained via LV catheterization) from the same animals. We studied rats at either the acute (1 and 3d post-SCI) or chronic (12wk post-SCI) stage of SCI to establish temporal patterns and compared findings to sham-injured rats. We found that SCI induces marked, time-dependent changes in cardiac gene expression and function. Acute (1-3d) and chronic (12w) SCI display distinct, often opposing transcriptomic signatures, with thousands of genes differentially expressed versus SHAM. Acute SCI is characterized by suppressed immune, inflammatory, cell cycle, and stress-response pathways with altered metabolism. Chronic SCI shows upregulated immune signaling, impaired oxidative phosphorylation, extracellular matrix remodeling, and stress responses. Functionally, cardiac systolic dysfunction occurs early post-SCI and persists to the chronic phase. Reduced systolic function is strongly correlated with changes in immune, hypoxia, and cholesterol-related genes at the acute timepoints and with immune and hormone-signaling pathways at the chronic timepoint. Collectively, our data provide novel insight into the cardiac transcriptome post-SCI and identify the molecular pathways that most strongly correlate with functional decline.

Phenotypic switching is an emerging driver of cancer treatment resistance, yet early signals regulating this process remain unclear. Here, using longitudinal single-cell RNA sequencing, we mapped differentiation trajectories in the LTL331 prostate adenocarcinoma patient-derived xenograft (PDX) model undergoing neuroendocrine prostate cancer (NEPC) transformation post castration. Our analyses identified a key differentiation node marked by epithelial-mesenchymal transition (EMT) and repressor element-1 silencing transcription factor (REST) downregulation driven by the CXCR4-LASP1-G9a-SNAIL axis. Mechanistically, CXCR4 activation promotes nuclear translocation of LASP1 that links G9a and SNAIL via SH3/proline-rich motif and LIM/SNAG domain interactions, enabling SNAIL-mediated REST repression via promoter E-box motifs. Inhibition of CXCR4 or G9a reversed LTL331R NEPC cells toward a luminal androgen receptor-active phenotype. CXCR4-targeted radioligands enabled both imaging and inhibition of NEPC tumors in vivo. These findings highlight the CXCR4-LASP1-G9a-SNAIL axis as a key regulator of epigenetic and transcriptional reprogramming in NEPC transdifferentiation and support its therapeutic targeting in aggressive NEPC.

Treatment-induced neuroendocrine prostate cancer (t-NEPC) is a lethal, castration-resistant subtype of prostate cancer. While t-NEPC typically arises from adenocarcinoma through neuroendocrine transdifferentiation after androgen pathway inhibition, the temporal dynamics and molecular drivers of this process remain poorly understood. Here, utilizing the first-in-field patient-derived xenograft (PDX) model of adenocarcinoma-to-NEPC transdifferentiation (LTL331/331R), we performed longitudinal single-cell transcriptomic sequencing (scRNA-seq) across seven timepoints spanning pre-castration to relapsed NEPC. Our analysis demonstrated 15 distinct cell clusters, including twelve adenocarcinoma clusters and two NEPC clusters (ASCL1 high/FOXA2 low and ASCL1 low/FOXA2 high clusters). Notably, we revealed a newly-discovered, early intermediate transitional cell state during t-NEPC development distinguished by epithelial-mesenchymal transition (EMT), stem cell-related, metabolically active, and HDAC-associated regulatory signatures. Analysis of this intermediate transitional cluster led to the identification of RUNX1T1 as a pivotal transcriptional regulator of NEPC transdifferentiation. Functionally, RUNX1T1 overexpression promoted AR pathway inhibition (ARPI) -induced NE transdifferentiation and increased resistance to ARPI treatment in prostate adenocarcinoma. RUNX1T1 knockdown reverses the NE transdifferentiation, inhibits NEPC cell proliferation and induces apoptosis, and cell cycle arrest. In summary, this study identifies a critical intermediate transitional cell state during t-NEPC development and reveals the heterogeneity of terminal NEPC, offering new insights into NEPC biology and emphasizing the importance of early intervention. Moreover, the discovery of RUNX1T1 as a key early driver active in both the initial and terminal phases of NEPC progression presents promising opportunities for therapeutic intervention.

BACKGROUND: Protein-truncating mutations in the titin gene are associated with increased risk of atrial fibrillation. However, little is known about the underlying pathophysiology. METHODS: We identified a heterozygous titin truncating variant (TTNtv) in a patient with unexplained early onset atrial fibrillation and normal ventricular function. We generated patient-specific atrial- and ventricular-like induced pluripotent stem cell-derived cardiomyocytes and engineered heart tissue to evaluate the impact of the TTNtv on electrophysiology, sarcomere structure, contractility, and gene expression. RESULTS: We demonstrate that the TTNtv increases susceptibility to pacing-induced arrhythmia, promotes sarcomere disorganization, and reduces contractile force in atrial induced pluripotent stem cell-derived cardiomyocytes compared with their CRISPR/Cas9-corrected isogenic controls. In ventricular induced pluripotent stem cell-derived cardiomyocytes, this variant was associated with abnormal electrophysiology and sarcomere organization without a reduction in contractile force compared with their isogenic controls. RNA-sequencing revealed an upregulation of cell adhesion and extracellular matrix genes in the presence of the TTNtv for both atrial and ventricular engineered heart tissues. CONCLUSIONS: In a patient with unexplained atrial fibrillation, induced pluripotent stem cell-derived cardiomyocytes with a TTNtv showed structural and electrophysiological abnormalities in both atrial and ventricular models, while only atrial engineered heart tissues demonstrated reduced contractility. The observed chamber-specific effect suggests that structural disorganization and reduced contractile function may be associated with atrial myopathy in the presence of truncated titin.

Background:Studies of germline variants in prostate cancer (PCa) have largely focused on their connections to cancer predisposition. However, an understanding of how heritable factors contribute to cancer progression and metastasis remain limited. Objective:To identify low frequency to rare germline nonsynonymous variants associated with increased risk for metastatic PCa (mPCa), while providing functional validation. Design:We assembled an extreme phenotype cohort (EPC) of 52 patients diagnosed with predominantly high-grade (Gleason Score (GS) ≥ 8) PCa and > 7 years of follow-up for which localized treatment naïve tumor tissues were available. In half of the cases, the tumor had metastasized to bone, providing an even distribution of bone mPCa and non mPCa cases. Tumor and matched distant benign DNA samples were exome sequenced and analyzed for germline variants with population-wide minor allelic frequencies ≤ 2%. Findings were validated using two independent PCa germline cohorts, including a closely matched Australian study biased to aggressive disease (n = 53) and Pan Prostate Cancer Group (PPCG, n = 976). Two mPCa-promoting candidate variants in KDM6B and BRCA2 were engineered into cell lines and functionalized. Results:Germline nonsynonymous rare variants (gnsRVs) identified in 25 DNA Damage Repair (DDR) genes were significantly enriched in the mPCa patients (p=4.57e-06). Conversely, the prevalence of synonymous variants at minor allele frequencies of ≤ 2% were similar between the mPCa and non mPCa patients. The predictive power of variants in 53 non-DDR genes was validated in the Australian cohort (p=0.028) and correlated with high-risk PCa in PPCG (p=0.03). KDM6B K973Q showed functional significance despite being annotated as benign in ClinVar, while BRCA2 I1962T showed sensitivity to Olaparib. In total, six EPC variants related to DNA repair or epigenetics were found to alter enzymatic activity. Conclusions:EPCs coupled with low frequency/rare variant analyses may advance understanding of interactions between the germline and tumor in PCa. We identified a series of germline variants that were enriched among mPCa patients. Moreover, we showed that one of these variants confers a metastatic phenotype. Our findings suggest that germline testing at diagnosis may improve treatment stratification in PCa. Patient summary:The presence of specific genetic variants among men with PCa may elevate the risk of mPCa once PCa develops. Knowledge of the variant burden at time of diagnosis may enable accurate stratification of some patients for aggressive therapeutic interventions.

Fertility preservation following pediatric cancer therapy programs has become a major avenue of infertility research. In vitro spermatogenesis (IVS) aims to generate sperm from banked prepubertal testicular tissues in a lab setting using specialized culture conditions. While successful using rodent tissues, progress with human tissues is limited by the scarcity of human prepubertal testicular tissues for research. This study posits that human induced pluripotent stem cells (hiPSCs) can model human prepubertal testicular tissue to facilitate the development of human IVS conditions. Testicular cells derived from hiPSCs are characterized for phenotype markers and profiled transcriptionally. HiPSC-derived testicular cells are bioprinted into core-shell constructs representative of testis cytoarchitecture and found to capture functional aspects of prepubertal testicular tissues within 7 days under xeno-free conditions. Moreover, hiPSC-derived Sertoli cells illustrate the capacity to mature under pubertal-like conditions. The utility of the model is tested by comparing 2 methods of supplementing retinoic acid (RA), the vitamin responsible for inducing spermatogenesis. The model reveals a significant gain in activity under microsphere-released RA compared to RA medium supplementation, indicating that the fragility of free RA in vitro may be a contributing factor to the molecular dysfunction observed in human IVS studies to date.

MOTIVATION:Single-cell RNA sequencing (scRNA-seq) analysis relies heavily on effective clustering to facilitate numerous downstream applications. Although several machine learning methods have been developed to enhance single-cell clustering, most are fully unsupervised and overlook the rich repository of annotated datasets available from previous single-cell experiments. Since cells are inherently high-dimensional entities, unsupervised clustering can often result in clusters that lack biological relevance. Leveraging annotated scRNA-seq datasets as a reference can significantly enhance clustering performance, enabling the identification of biologically meaningful clusters in target datasets. RESULTS:In this article, we propose Single Cell MUlti-Source CLustering (scMUSCL), a novel transfer learning method designed to identify cell clusters in a target dataset by leveraging knowledge from multiple annotated reference datasets. scMUSCL employs a deep neural network to extract domain- and batch-invariant cell representations, effectively addressing discrepancies across various source datasets and between source and target datasets within the new representation space. Unlike existing methods, scMUSCL does not require prior knowledge of the number of clusters in the target dataset and eliminates the need for batch correction between source and target datasets. We conduct extensive experiments using 20 real-life datasets, demonstrating that scMUSCL consistently outperforms existing unsupervised and transfer learning-based methods. Furthermore, our experiments show that scMUSCL benefits from multiple source datasets as learning references and accurately estimates the number of clusters. AVAILABILITY AND IMPLEMENTATION:The Python implementation of scMUSCL is available at https://github.com/arashkhoeini/scMUSCL.

Spatial transcriptomics has transformed our understanding of gene expression by preserving the spatial context within tissues. This review focuses on the application of spatial transcriptomics in human cardiac tissues, exploring current technologies with a focus on commercially available platforms. We also highlight key studies utilizing spatial transcriptomics to investigate cardiac development, electro-anatomy, immunology, and ischemic heart disease. These studies demonstrate how spatial transcriptomics can be used in conjunction with other omics technologies to provide a more comprehensive picture of human health and disease. Despite its transformative potential, spatial transcriptomics comes with several challenges that limit its widespread adoption and broader application. By addressing these limitations and fostering interdisciplinary collaboration, spatial transcriptomics has the potential to become an essential tool in cardiovascular research. We hope this review serves as a practical guide for researchers interested in adopting spatial transcriptomics, particularly those with limited prior experience, by providing insights into current technologies, applications, and considerations for successful implementation.

Neuroendocrine transdifferentiation (NEtD) of prostate adenocarcinoma (PRAD) leads to aggressive neuroendocrine prostate cancer (NEPC). The LTL331 patient-derived xenograft (PDX) model consistently progresses to NEPC following castration, mimicking clinical responses to androgen-deprivation therapy. Here we tracked NEtD using longitudinal single-cell RNA sequencing (scRNA-seq) across eight time points in LTL331 from pre- to post-castration. Castration led to the loss of AR-high PRAD cells, expansion of AR-low populations, and emergence of an AR- and NE-negative (AR-/NE-) intermediate state that transitioned into NEPC. We delineate a model in which pre-EMT cells enriched in ciliogenesis and cell-adhesion pathways differentiate into EMT-like populations before branching into distinct ASCL1+ and ASCL1− NEPC states. The EMT-enriched intermediate, marked by progenitor and neural crest stem-cell genes, acts as a transition bridge, suggesting EMT-associated stemness underlies lineage plasticity. A terminal ASCL1-NEPC state also suggests that ASCL1 is not essential for NEPC maintenance. Gene regulatory analysis highlighted key regulators driving NEtD, including MSX1 and ASCL1 in early EMT-like and NEPC states, respectively. These transcriptional states were validated in both patient-derived bulk and scRNA-seq data. Our findings offer insights into intervention strategies to delay or prevent NEtD with the potential of identifying novel prognostic and therapeutic targets. ### Competing Interest Statement The authors have declared no competing interest. Canadian Institutes of Health ResearchCanadian Institutes of Health Research, https://ror.org/01gavpb45, 153081, 173338, 180554, 186331 Terry Fox Research InstituteTerry Fox Research Institute, https://ror.org/00mtf6c40, 1109 Canadian Cancer SocietyCanadian Cancer Society, https://ror.org/017343w90, 707683 BC Cancer FoundationBC Cancer Foundation, https://ror.org/03gqhbs95, 1PRRG012 Canadian Institutes of Health ResearchCanadian Institutes of Health Research, https://ror.org/01gavpb45, PJT-17523, PJT-153073, PJT-173331 Ministry of Health and WelfareMinistry of Health and Welfare, , 114-TDU-B222-134002 National Science and Technology CouncilNational Science and Technology Council, , 114-2634-039-001, 114-2326-B-038-001 TÜB&TAK National ObservatoryTÜB&TAK National Observatory, https://ror.org/00xfgvj95, 221Z116 United States Department of DefenseUnited States Department of Defense, , W81XWH-21-1-0234

Motivation A patient's disease phenotype can be driven and determined by specific groups of cells whose marker genes are either unknown or can only be detected at late-stage using conventional bulk assays such as RNA-Seq technology. Recent advances in single-cell RNA sequencing (scRNA-seq) enable gene expression profiling in cell-level resolution, and therefore have the potential to identify those cells driving the disease phenotype even while the number of these cells is small. However, most existing methods rely heavily on accurate cell type detection, and the number of available annotated samples is usually too small for training deep learning predictive models.Results Here, we propose the method ScRAT for phenotype prediction using scRNA-seq data. To train ScRAT with a limited number of samples of different phenotypes, such as coronavirus disease (COVID) and non-COVID, ScRAT first applies a mixup module to increase the number of training samples. A multi-head attention mechanism is employed to learn the most informative cells for each phenotype without relying on a given cell type annotation. Using three public COVID datasets, we show that ScRAT outperforms other phenotype prediction methods. The performance edge of ScRAT over its competitors increases as the number of training samples decreases, indicating the efficacy of our sample mixup. Critical cell types detected based on high-attention cells also support novel findings in the original papers and the recent literature. This suggests that ScRAT overcomes the challenge of missing marker genes and limited sample number with great potential revealing novel molecular mechanisms and/or therapies.Availability and implementation The code of our proposed method ScRAT is published at https://github.com/yuzhenmao/ScRAT.

The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.

Background Protein truncating mutations in the titin gene are associated with increased risk of atrial fibrillation (AF). However, little is known regarding the underlying pathophysiology. Methods We identified a heterozygous titin truncating variant in a patient with unexplained early-onset AF using whole exome sequencing. We used atrial and ventricular patient induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), CRISPR/Cas9 genetic correction, and engineered heart tissue (EHT) constructs to evaluate the impact of the titin truncating variant on electrophysiology, sarcomere structure, contractility, and gene expression. Results We generated atrial and ventricular iPSC-CMs from the AF patient with the titin truncating variant and a CRISPR/Cas9 genome corrected isogenic control. We demonstrate that the titin truncating variant increases susceptibility to pacing-induced arrhythmia (prevalence of arrhythmogenic phenotypes, 85.7% versus 14.2%; P = 0.03), promotes sarcomere disorganization (mean ± SEM, 66.3 ± 6.8% versus 88.0 ± 2.9%; P = 0.04) in atrial iPSC-CMs, and reduces contractile force (0.013 ± 0.003 mN versus 0.027 ± 0.004 mN; P < 0.01) in atrial EHTs compared to isogenic controls. In ventricular iPSC-CMs, this variant led to altered electrophysiology (90.0% versus 33.3%; P = 0.02) and sarcomere organization (62.0 ± 3.9% versus 82.9 ± 2.9%; P < 0.01) with no change in EHT contractility compared to isogenic controls. RNA-sequencing revealed an upregulation of cell adhesion and extracellular matrix genes in the presence of the titin truncating variant for both atrial and ventricular EHTs. Conclusions In a patient with early-onset unexplained AF and normal ventricular function, iPSC-CMs with a titin truncating variant showed structural and electrophysiological abnormalities in both atrial and ventricular preparations, while only atrial EHTs demonstrated reduced contractility. Whole transcriptome sequencing showed upregulation of genes involved in cell-cell and cell-matrix interactions in both atrial and ventricular EHTs. Together, these findings suggest titin truncating variants promote the development of AF through remodeling of atrial cardiac tissue and provide insight into the chamber-specific effects of titin truncating variants.

Heart disease is a leading cause of global morbidity and mortality. This is partly because despite an abundance of animal and in-vitro models, it has been challenging to study human heart tissue with sufficient depth and resolution to develop disease modifying therapies for common cardiac conditions. Single-nucleus RNA sequencing (snRNAseq) has emerged as a powerful tool capable of analyzing cellular function and signalling in health and disease. Employing snRNAseq to study the human heart has the potential to unlock novel disease mechanisms and pathways. However, progress on this front has been slowed by several barriers. One key challenge is the fact that human heart tissue is very resistant to shearing and stress, making tissue dissociation and nuclear isolation difficult. Here, we describe a tissue dissociation method allowing for efficient and cost-effective isolation of high-quality nuclei from flash frozen human heart tissue collected in surgical operating rooms. Flash frozen human cardiac tissue was obtained through an established cardiac tissue biobank. Human cardiac tissue was collected and flash frozen from operating rooms performing open heart surgery. A protocol to generate single nuclei preparations from human tissue samples was found through literature review. This protocol was trialed and adapted for flash frozen human cardiac tissue. Assessments of protocol efficacy were made via nuclear morphology on brightfield imaging, DAPI stained nuclear morphology on epi-fluorescence imaging, Tapestation analysis of RNA integrity and concentration, and snRNAseq of isolated single nuclei to assess for cell type variability. Preliminary snRNAseq results are presented. Our results show that this modified protocol can reliably dissociate human cardiac tissue and isolate a high concentration of single nuclei. The preliminary snRNAseq results of isolated single nuclei using this protocol demonstrate high cell type variability. Our protocol addresses the challenge of nuclear isolation from frozen human hearts and allows for snRNAseq of the human heart. Preliminary snRNAseq results show that this protocol can isolate high concentrations of single nuclei and from a diverse array of cell types. This suggests that sequencing findings from nuclei isolated using this protocol may be more representative of the in-vivo cellular composition of the human heart. This paves the way for an improved understanding of the human heart in health and disease. Ultimately, this will be key to uncovering signalling pathways and networks amenable to therapeutic intervention and the development of novel biomarkers and disease-modifying therapies.

Heart disease is the leading cause of global morbidity and mortality. This is in part because, despite an abundance of animal and in vitro models, it has been a challenge to date to study human heart tissue with sufficient depth and resolution to develop disease-modifying therapies for common cardiac conditions. Single-nucleus RNA sequencing (snRNA-seq) has emerged as a powerful tool capable of analyzing cellular function and signaling in health and disease, and has already contributed to significant advances in areas such as oncology and hematology. Employing snRNA-seq technology on flash-frozen human tissue has the potential to unlock novel disease mechanisms and pathways in any organ. Studying the human heart using snRNA-seq is a key priority for the field of cardiovascular sciences; however, progress to date has been slowed by numerous barriers. One key challenge is the fact that the human heart is very resistant to shearing and stress, making tissue dissociation and nuclear isolation difficult. Here, we describe a tissue dissociation method allowing the efficient and cost-effective isolation of high-quality nuclei from flash-frozen human heart tissue collected in surgical operating rooms. Our protocol addresses the challenge of nuclear isolation from human hearts, enables snRNA-seq of the human heart, and paves the way for an improved understanding of the human heart in health and disease. Ultimately, this will be key to uncovering signaling pathways and networks amenable to therapeutic intervention and the development of novel biomarkers and disease-modifying therapies. © 2022 Wiley Periodicals LLC. Basic Protocol: Human heart tissue dissociation and nuclear isolation for snRNA-seq.

Abstract Background Androgen receptor (AR) is critical to the initiation, growth, and progression of prostate cancer. Once activated, the AR binds to cis-regulatory enhancer elements on DNA that drive gene expression. Yet, there are 10–100× more binding sites than differentially expressed genes. It is unclear how or if these excess binding sites impact gene transcription. Results To characterize the regulatory logic of AR-mediated transcription, we generated a locus-specific map of enhancer activity by functionally testing all common clinical AR binding sites with Self-Transcribing Active Regulatory Regions sequencing (STARRseq). Only 7% of AR binding sites displayed androgen-dependent enhancer activity. Instead, the vast majority of AR binding sites were either inactive or constitutively active enhancers. These annotations strongly correlated with enhancer-associated features of both in vitro cell lines and clinical prostate cancer samples. Evaluating the effect of each enhancer class on transcription, we found that AR-regulated enhancers frequently interact with promoters and form central chromosomal loops that are required for transcription. Somatic mutations of these critical AR-regulated enhancers often impact enhancer activity. Conclusions Using a functional map of AR enhancer activity, we demonstrated that AR-regulated enhancers act as a regulatory hub that increases interactions with other AR binding sites and gene promoters.

Well-differentiated papillary mesothelioma (WDPM) is an uncommon mesothelial proliferation that is most commonly encountered as an incidental finding in the peritoneal cavity. There is controversy in the literature about whether WDPM is a neoplasm or a reactive process and, if neoplastic, whether it is a variant or precursor of epithelial malignant mesothelioma or is a different entity. Using whole exome sequencing of five WDPMs of the peritoneum, we have identified distinct mutations inEHD1,ATM,FBXO10,SH2D2A,CDH5,MAGED1, andTP73shared by WDPM cases but not reported in malignant mesotheliomas. Furthermore, we show that WDPM is strongly enriched with C > A transversion substitution mutations, a pattern that is also not found in malignant mesotheliomas. The WDPMs lacked the alterations involvingBAP1,SETD2,NF2,CDKN2A/B,LASTS1/2,PBRM1, andSMARCC1that are frequently found in malignant mesotheliomas. We conclude that WDPMs are neoplasms that are genetically distinct from malignant mesotheliomas and, based on observed mutations, do not appear to be precursors of malignant mesotheliomas.

Background Caenorhabditis elegans provides a genetically tractable model organism to investigate the network of genes involved in fat metabolism and how regulation is perturbed to produce the complex phenotype of obesity. C. elegans possess the full range of desaturases, including the Δ9 desaturases expressed by fat-5, fat-6 and fat-7 . They regulate the biosynthesis of monounsaturated fatty acids, used for the synthesis of lipids including phospholipids, triglycerides and cholesteryl esters. Results Liquid chromatography mass spectrometry (LC-MS), gas chromatography mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR) spectroscopy were used to define the metabolome of all the possible knock-outs for the Δ9 desaturases, including for the first time intact lipids. Despite the genes having similar enzymatic roles, excellent discrimination was achievable for all single and viable double mutants highlighting the distinctive roles of fat-6 and fat-7 , both expressing steroyl-CoA desaturases. The metabolomic changes extend to aqueous metabolites demonstrating the influence Δ9 desaturases have on regulating global metabolism and highlighting how comprehensive metabolomics is more discriminatory than classically used dyes for fat staining. Conclusions The propagation of metabolic changes across the network of metabolism demonstrates that modification of the Δ9 desaturases places C.elegans into a catabolic state compared with wildtype controls.

Introduction: Colonoscopy is the accepted gold standard for the detection of colorectal cancer. The aim of the current study was to prospectively compare high definition plus (HD+) colonoscopy with i-Scan functionality (electronic staining) vs. standard video colonoscopy. The primary end-point was the detection of patients having colon cancer or at least one adenoma.Methods: A total of 220 patients due to undergo screening colonoscopy, postpolypectomy surveillance or with a positive occult blood test were randomized in a 1 : 1 ratio to undergo HD+ colonoscopy in conjunction with i-Scan surface enhancement (90i series, Pentax, Tokyo, Japan) or standard video colonoscopy (EC-3870FZK, Pentax). Detected colorectal lesions were judged according to type, location, and size. Lesions were characterized in the HD+ group by using further i-Scan functionality (p-and v-modes) to analyze pattern and vessel architecture. Histology was predicted and biopsies or resections were performed on all identified lesions.Results: HD+ colonoscopy with i-Scan functionality detected significantly more patients with colorectal neoplasia (38 %) compared with standard resolution endoscopy (13 %) (200 patients finally analyzed; 100 per arm). Significantly more neoplastic (adenomatous and cancerous) lesions and more flat adenomas could be detected using high definition endoscopy with surface enhancement. Final histology could be predicted with high accuracy (98.6%) within the HD+ group.Conclusions: HD+ colonoscopy with i-Scan is superior to standard video colonoscopy in detecting patients with colorectal neoplasia based on this prospective, randomized, controlled trial.

Endoflag (Endopix Ltd., Israel) is a new software-based adaptive image enhancement algorithm (filtering and logic), that enhances the surface detail and vessel architecture of the colonic mucosa without introducing misleading artifacts. The real-time post processed Endoflag image is displayed simultaneously with the unprocessed white light image during ongoing colonoscopy. Aim of the prospective randomized trial was to test whether colonoscopy in conjunction with Endoflag is superior in detecting intraepithelial neoplasias (IN) compared to standard white light colonoscopy.